Protein Tyrosine Phosphorylation in Haematopoietic Cancers ...

Protein Tyrosine Phosphorylation in Haematopoietic

Cancers and the Functional Significance of Phospho-

Lyn SH2 Domain

By

Lily Li Jin

A thesis submitted in conformity with the requirements for the degree of Ph.D. in

Molecular Genetics, Graduate Department of Molecular Genetics, in the University of

Toronto

© Copyright by Lily Li Jin (2015)

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Protein Tyrosine Phosphorylation in Haematopoietic Cancers

and the Functional Significance of Phospho-Lyn SH2 Domain

Lily Li Jin

2015

Ph.D. in Molecular Genetics

Graduate Department of Molecular Genetics

University of Toronto

Abstract

Protein-tyrosine phosphorylation (pY) is a minor but important protein post-translational

modification that modulates a wide range of cellular functions and is involved in cancer.

Dysregulation of tyrosine kinases (TKs) and protein-tyrosine phosphatases (PTPs) have

been observed in multiple myeloma (MM) and acute myeloid leukemia (AML) and is a

subject of study. Using recently developed mass spectrometry-based proteomics

techniques, quantitative PTP expression and cellular pY profiles were generated for MM

cell lines and mouse xenograft tumors, as well as primary AML samples. Integrated

comprehensive analyses on these data implicated a subset of TKs and PTPs in MM and

AML, with valuable insights gained on the dynamic regulation of pY in biological

systems. In particular, I propose a model that describes the cellular pY state as a

functional output of the total activated TKs and PTPs in the cell. My results show that the

global pY profile in the cancer models is quantitatively related to the cellular levels of

activated TKs and PTPs. Furthermore, the identity of the implicated TK/PTPs is system-

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dependent, demonstrating context-dependent regulation of pY. To further understand pY

regulation, I studied the phosphorylation of a conserved tyrosine in the Src homology 2

(SH2) domains of Src family kinases, which was frequently observed in human cancer

specimens and regulated in cancer-derived cell lines. Using the Lyn SH2 domain as a

model, I discovered that when this tyrosine (Y194) is phosphorylated, the domain has

reduced ability to interact in vitro with phosphopeptides and phosphoproteins. Sequence

analysis of the binding motifs revealed that phosphorylation at Y194 decreased the

selectivity of Lyn SH2 for the third residue C-terminal to the pY of the ligand. Together,

these data show that tyrosyl phosphorylation alters the substrate binding profile of Lyn

SH2 and may potentially affect Lyn kinase signaling. This may be a general mechanism

for all Src family kinases and represents another layer of the complexity of pY regulation.

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List of Abbreviations

AML acute myeloid leukemia

AP affinity purification

ATP adenosine triphosphate

CLL chronic lymphocytic leukemia

EGF epidermal growth factor

EGFR epidermal growth factor receptor

ESI electrospray ionization

FGFR3 fibroblast growth factor receptor 3

HER2 human epidermal growth factor receptor 2

HRG HER2/heregulin

IGF-1 insulin-like growth factor 1

IGF1R IGF-1 receptor

IL-6 interleukin 6

IMAC immobilized metal affinity chromatography

INSR insulin receptor

IP immunoprecipitation

IPI international protein index

ITD internal tandem duplication

Kd dissociation constants

KMS Kawasaki Medical School

LC MS/MS liquid chromatography tandem mass spectrometry

MAPK mitogen-activated protein kinase

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MGUS monoclonal gammopathy of undetermined significance

MM multiple myeloma

MS mass spectrometry

nRTK non-receptor tyrosine kinase

NSCLC non-small cell lung cancer

PDGF platelet derived growth factor

PLSR partial least squares regression

PTB protein tyrosine binding

PTP protein tyrosine phosphatase

pY tyrosine phosphorylation

ROS reactive oxygen species

rt room temperature

RTK receptor tyrosine kinase

SA Streptavidin

SFK Src family kinases

SH2 Src homology 2

SILAC stable isotope labelling by amino acids in cell culture

SRM selected reaction monitoring

STAT signal transduction and activator of transcription

TK tyrosine kinase

XIC extracted ion current chromatography

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Table of Contents

List of Abbreviations ................................................................................................. iv

Table of Contents ....................................................................................................... vi

List of Tables .............................................................................................................. x

List of Figures ............................................................................................................ xi

List of Appendices .................................................................................................... xii

Chapter 1 Introduction .................................................................................................... 1

1.1 Protein Tyrosine Phosphorylation: Function and Dysregulation in

Haematopoietic Cancers ............................................................................................. 1

1.1.1 Enzymes and Domains Involved in pY-Mediated Functions ........................ 1

1.1.1.1 Tyrosine Kinases ..................................................................................... 2

1.1.1.2 Src Family Kinases ................................................................................. 3

1.1.1.3 Protein Tyrosine Phosphatases ............................................................... 4

1.1.1.4 Src Homology 2 Domain ........................................................................ 5

1.1.1.4.1 Structure and Functions of SH2 Domains ........................................... 5

1.1.1.4.2 Genetic Mutations of SH2 Domains in Human Diseases .................... 7

1.1.2 Biological Function of Phosphorylated Tyrosines ......................................... 9

1.1.3 Dysregulation of Protein Tyrosine Kinases and Phosphatases in

Haematopoietic Cancers ....................................................................................... 11

1.1.3.1 Multiple Myeloma ................................................................................ 11

1.1.3.2 Acute Myeloid Leukemia ..................................................................... 13

1.2 Mass Spectrometry Based Proteomics ................................................................ 15

1.2.1 Mass Spectrometry for Proteomics Studies ................................................. 16

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1.2.2 Label-Free Quantification by Mass Spectrometry ....................................... 16

1.2.2.1 Measurement by Intensity of MS1 Ion Current .................................... 17

1.2.2.2 Selected Reaction Monitoring ............................................................... 18

1.2.3 Peptide Enrichment ...................................................................................... 18

1.2.3.1 Enrichment of Tyrosyl Phosphorylated Peptides .................................. 18

1.2.3.2 Enrichment of Oxidized Cysteine-Containing Peptides (qPTPome) .... 19

1.3 Key Statistical Analysis Used in this Thesis ....................................................... 20

1.3.1 Partial Least Squares Regression ................................................................ 20

1.4 Specific Aim for this Thesis ............................................................................... 21

Chapter 2 Comprehensive Analysis of Protein Phosphotyrosine in Multiple Myeloma

....................................................................................................................................... 22

2.1 Abstract ............................................................................................................... 23

2.2 Introduction ......................................................................................................... 23

2.3 Western Analysis Showed Distinct Expression, Glycosylation, Phosphorylation

of pY Signaling Molecules in MM Samples ............................................................. 27

2.4 pY Profiling Revealed Distinctive Differences between MM Cultured Cell lines

and Xenograft Tumors .............................................................................................. 30

2.5 Co-Variance Analysis of PTP and pY Profiles Implicated a Subset of PTP in pY

Regulation ................................................................................................................. 39

2.6 Correlation Heatmap Revealed Regulation “Hotspots” ...................................... 42

2.7 Discussion and Conclusion ................................................................................. 46

2.8 Materials and Methods ........................................................................................ 54

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Chapter 3 Comprehensive Analysis of Protein Phosphotyrosine in Acute Myeloid

Leukemia ....................................................................................................................... 62

3.1 Abstract ............................................................................................................... 63

3.2 Introduction ......................................................................................................... 63

3.3 pY Profiling Revealed Distinctive Features in Patient Subgroups and Implicated

a Subset of TKs in pY Regulation ............................................................................ 66

3.4 Integrated Analysis of PTP Expression and Cellular pY Implicated PTPs in

AML pY Regulation ................................................................................................. 74

3.6 Discussion and Conclusion ................................................................................. 76

3.6 Materials and Methods ........................................................................................ 81

Chapter 4 Determination of the Functional Consequences of Tyrosine-Phosphorylation

of the Lyn SH2 Domain ................................................................................................ 84

4.1 Abstract ............................................................................................................... 85

4.2 Introduction ......................................................................................................... 85

4.3 A Conserved Tyrosine in SFK SH2 Domains Is Phosphorylated in Cancer

Samples and Cancer-Derived Cell Lines .................................................................. 86

4.4 SFK SH2 Domain Phosphorylation Is Regulated ............................................... 89

4.5 Lyn SH2 Domain Phosphorylation Modulates Its Binding to pY Peptides ........ 89

4.6 Lyn SH2 Domain Phosphorylation Modulates Its Binding to pY-Containing

Proteins ..................................................................................................................... 98

4.7 Discussion and Conclusion ............................................................................... 104

4.8 Materials and Methods ...................................................................................... 108

Chapter 5 Summary and Future Directions ................................................................ 117

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5.1 Summary and Future Directions of the Comprehensive Protein-pY Regulation

Analysis in MM Samples ........................................................................................ 117

5.2 Summary and Future Directions of the Comprehensive Protein-pY Regulation

Analysis in AML Samples ...................................................................................... 120

5.3 Summary and Future Directions of the Functional Study of Lyn Y194

Phosphorylation ...................................................................................................... 124

5.4 Concluding Remarks ......................................................................................... 125

Appendices .................................................................................................................. 127

References ................................................................................................................... 142

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List of Tables

Table 2.1. Molecular characteristics of MM cell lines ..................................................... 27

Table 2.2. Number of proteins, peptides, and pY sites identified in MM cells and tumors

........................................................................................................................................... 33

Table 2.3. Proteins and sites corresponding to regulation “Hotspots” ............................. 45

Table 3.1. AML patient information corresponding to primary samples ......................... 65

Table 3.2. Proteins and sites associated with boxed regions in Figure 3.2 B ................... 71

Table 4.1. Phosphopeptides bound to Lyn SH2 or pSH2 identified by AP-MS ............... 93

Table 4.2. SH2/pSH2-binding phosphoproteins identified by peptide AP ..................... 103

Table 4.3. Fold change of SH2 or PTB domain-containing proteins bound to Lyn SH2

and pSH2 ......................................................................................................................... 103

Table 5.1. Summary of PTPs and TKs implicated in MM and AML ............................. 123

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List of Figures

Figure 1.1. A proposed model for the regulation and functional effect of cellular pY ..... 21

Figure 2.1. MM cell lines have distinctive molecular features ......................................... 29

Figure 2.2. pY profile reveals difference between cell and tumor and an abundance of TK

A-loop phosphorylations ................................................................................................... 32

Figure 2.3. Quantitative pY profile distinguishes cell from tumor ................................... 36

Figure 2.4. Cellular pY variation can be predicted based on TK activation levels .......... 38

Figure 2.5. PTP expression profiles predict cellular pY ................................................... 41

Figure 2.6. PTP and TK activation is positively correlated with subsets of pY ............... 44

Figure 3.1. Characterization of pY in AML primary samples .......................................... 67

Figure 3.2. PTP expression and TK activation are correlated with cellular pY ............... 70

Figure 3.3. Cellular pY variation can be predicted based on PTP expression or TK

activation levels ................................................................................................................ 73

Figure 4.1. SFK SH2 domain phosphorylation was detected in AML, CLL, MM and is

regulated by phosphatase .................................................................................................. 88

Figure 4.2. Purification of phosphorylated Lyn SH2 domain ........................................... 91

Figure 4.3. Lyn pSH2 shows reduced affinity for pY peptides compared to SH2 ........... 95

Figure 4.4. Binding curves of Lyn SH2/pSH2 with phospho-peptide probes .................. 97

Figure 4.5. Lyn SH2 phosphorylation modulates its binding affinity for phosphoproteins

......................................................................................................................................... 101

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List of Appendices

Appendix Table 1. MS ion current intensities of pY peptides in MM samples .............. 127

Appendix Table 2. MS ion current intensities of PTP-derived peptides in MM samples

......................................................................................................................................... 129

Appendix Table 3. MS ion current intensities of pY peptides quantified in AML ........ 130

Appendix Table 4. MS ion current intensities of PTP-derived peptides in AML .......... 133

Appendix Table 5. Phosphoproteins bound to Lyn SH2 or pSH2 identified by AP-MS

......................................................................................................................................... 134

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Chapter 1 Introduction

1.1 Protein Tyrosine Phosphorylation: Function and Dysregulation in

Haematopoietic Cancers

Protein tyrosine phosphorylation (pY) is defined by the addition of a covalently

bonded phosphate group to the hydroxyl of a tyrosine. It is a reversible protein

posttranslational modification that is involved in a plethora of cellular processes

including growth factor signaling, cell cycle progression, differentiation in development,

gene regulation and transcription, oncogenic transformation, angiogenesis, and apoptosis

(reviewed in 1, 2, 3). These biological functions are regulated through the concerted

action of tyrosine kinases (TKs), protein tyrosine phosphatases (PTPs), and scaffold

proteins, adaptors, among others (4, 5). Functional disruption of the regulatory molecules

can induce physiological consequences and is linked to cancer (6). Targeting some of the

dysregulated mechanisms has proven to be an effective clinical strategy (7, 8). Therefore,

understanding the regulation of pY in disease systems can have significant impacts and

lead to improvements in therapeutic treatment regimes.

1.1.1 Enzymes and Domains Involved in pY-Mediated Functions

The reversible phosphorylation of tyrosine is mediated by two classes of enzymes:

TKs that facilitate the attachment of the phosphate group and PTPs that remove it. The

reciprocal actions of TKs and PTPs are constantly regulated in cells to ensure appropriate

pY signaling. Through diverse regulation mechanisms, the phosphorylation and

dephosphorylation of cellular protein tyrosines are tightly controlled.

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1.1.1.1 Tyrosine Kinases

TKs are enzymes that catalyze the transfer of the gamma phosphate of adenosine

triphosphate (ATP) to the amino acid tyrosine of a substrate protein. There are two

classes of TKs. Receptor tyrosine kinases (RTKs) are type I transmembrane proteins that

contain an N-terminal extracellular domain for ligand binding, a single transmembrane

region, and a C-terminal intracellular region that possesses the catalytic domain and

protein binding sites. The second class of TKs comprises non-receptor tyrosine kinases

(nRTKs) that reside in the cytoplasm. A total of 90 TKs are encoded by the human

genome, comprising a subset of the human “kinome”. Among the TKs, 58 (subdivided

into 20 classes) are RTKs and 32 are nRTKs (9).

The catalytic domains of TKs share similar features. They comprise of two lobes: a

larger C-terminal lobe composed primarily of α helices that participates in substrate

binding, and a smaller N-terminal lobe containing mainly β sheets and an α helix. The

two lobes form a deep cleft, or the active site, where ATP and substrates bind. There are

two polypeptide regions within the active site that are especially important for catalysis: a

glycine-rich region that is critical for ATP binding and a segment sandwiched between

the conserved sequences DFG and APE, termed the activation loop, or “A-loop”. For

TKs, the A-loop typically contains 1 to 3 tyrosines, which, upon phosphorylation,

stimulate the catalytic ability of the TK. These tyrosine sites are sometimes

autophosphorylation sites, providing a means for auto-activation (10, 11).

TKs phosphorylate their substrates through regulated protein-protein interactions

(4). The identity of the substrate is highly selective depending on the TK, and the

phosphorylation event itself is rigidly controlled. A large number of TKs only become

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active and phosphorylate their substrates if triggered by a cellular event (12-14). Thus,

through controlling the activation of TKs, cellular tyrosine phosphorylations are regulated.

1.1.1.2 Src Family Kinases

Src family kinases (SFKs) comprise the largest family of nRTKs. There are eight

members of SFK in the human kinome: Src, Yes, Fyn, Fgr, Lck, Hck, Blk, and Lyn,

which share at least 85% sequence homology and almost identical structures (15). SFKs

possess several functional domains including a Src homology 2 (SH2) domain for protein

binding, substrate recognition, and intra-molecular interactions; a catalytic domain; and a

C-terminal tail region involved in auto-inhibitory regulation (15, 16).

The kinase activity of SFKs is intrinsically regulated by tyrosyl phosphorylations.

The classic regulation mechanisms of SFKs include 1) phosphorylation of a conserved

tyrosine within the A-loop of their catalytic domains (Src residue Y416), which enhances

their catalytic activities (17, 18); and 2) tyrosine-phosphorylation of the C-terminal tail

(Src residue Y527), which negatively regulates their enzymatic capabilities. As revealed

by the crystal structure of the inactive Src, the phosphorylated C-terminal tail binds intra-

molecularly to the SH2 domain, which maintains the protein in its inactive conformation

(19, 20). Interestingly, a study reported that a third phosphorylation (Y213) in the SH2

domain of Src was able to activate Src in the presence of the inhibitory C-terminal

phosphorylation, presumably by impeding the intra-molecular interactions between the

C-terminal tail and the SH2 domain (21).

SFKs are involved in a plethora of cellular processes due to their critical role in

mediating signal transduction downstream of a diverse range of cell surface receptors

(reviewed in 22, 23). Activated SFKs have the ability to promote survival and

4

proliferation in transformed cells, consequently, many members of this family are

deemed oncoproteins (23, 24). In haematopoietic systems, Lck/Yes-related novel protein

tyrosine kinase (Lyn) is highly expressed and plays important roles in modulating surface

receptor signaling (13, 25); as such, Lyn has been implicated in B cell cancers (i.e.

multiple myeloma) (26-28) and myeloid leukemic diseases (i.e. acute myeloid leukemia)

(29).

1.1.1.3 Protein Tyrosine Phosphatases

PTPs are enzymes that catalyze the removal of phosphate from phosphorylated

tyrosines in a polypeptide. They counteract the actions of TKs and both positively and

negatively regulate signal transduction and cellular functions (30). Aberrations in PTP

functioning are associated with a number of human disorders, in particular, cancer (31).

There are 107 PTP genes encoded by the human genome, including 38 “classical PTPs”

that exclusively target pY and dual-specific PTPs that hydrolyze both phospho-

serine/threonine and pY, comprising the human “PTPome”. The classical PTPs are

further divided into 21 receptors and 17 non-receptors, which are collectively called

cysteine-based PTPs because their enzymatic activity is entirely dependent on an

invariant Cys residue within the conserved “signature motif”, [I/V]HCSXGXGR[S/T]G,

in the catalytic cleft (32).

PTPs can be inactivated by oxidation. Reactive oxygen species (ROS), in particular

H2O2, reversibly oxidize the critical cysteine in the signature motif of the catalytic cleft.

Because of its uniquely low pKa (4.5-5.5 compared to around 8.5 for typical Cys), the

invariant Cys presents as a thiolate anion in the natural pH, allowing it to function as a

nucleophile that attacks the substrate phosphate moiety and facilitates catalysis. When

5

oxidized, this Cys no longer acts as a nucleophile, which leads to the suppression of

enzymatic activity (33). This mechanism modulates endogenous PTP activities (34).

Moreover, it was shown that H2O2 production was transiently elevated following RTK

activation; and that the rapid inactivation of PTP by H2O2 was required for full RTK

phosphorylation and signal transduction (34-37). Therefore, modulation of PTP activities

by ROS is one mechanism that regulates the dephosphorylation of cellular pY.

1.1.1.4 Src Homology 2 Domain

SH2 domains are modular protein structures approximately 100 amino acids in

length that bind pY-containing polypeptides with defined amino acid sequence motifs

(38). Evolutionarily, they emerge at around the same time as TKs, supporting their role as

modulators of cellular functions engaging pY (39). There are 120 SH2 domains encoded

by the human genome, all sharing similar tertiary structures. These structures allow

specific interactions between SH2 domains and phosphorylated proteins and confer

selectivity through defined mechanisms (40). Due to the ready reversibility of protein

tyrosine phosphorylation, these interactions are inherently dynamic and regulate a variety

of pY-mediated processes.

1.1.1.4.1 Structure and Functions of SH2 Domains

The tertiary structure of the SH2 domain consists of two antiparallel β-sheets,

flanked by two α-helices (41). As revealed by X-ray crystallographic studies, pY-

containing peptides bind in an extended β-strand conformation perpendicularly to the

central β-sheets, while the pY moiety inserts into a deep recognition pocket formed by

conserved residues from strands βB, βC, βD, helix αA, and a connection loop between

6

the βB/βC strands (a.k.a. BC or phosphate-binding loop) (41-43). Alteration of residues

surrounding the pY binding pocket affects the binding of pY-containing ligands (44, 45),

indicating the importance of the conserved residues in the interaction site. In addition to

the pY binding pocket, there are several positions in the SH2 domain that the pY-adjacent

residues can bind (40). Studies using degenerate peptide libraries delineated binding

specificities of more than 70 different human SH2 domains (46, 47). Moreover, small

pY-peptides containing only 5 residues can effectively block the binding of SH2 domains

to their interaction partners (48). These data illustrate that SH2-pY interaction is largely

defined by up to five amino acid residues C-terminal to the pY, which interact with

variable binding surfaces on the SH2 domain.

For the SFK SH2 domains, three residues lying immediately C-terminal to pY

(pY+1, +2, +3) of the ligand principally determine the binding specificity (38, 47, 49). In

particular, the amino acids at pY+1 and pY+2 positions overlay a flat surface formed by

the βD4-βD6 residues, while the hydrophobic pY+3 residue inserts into a large

hydrophobic pocket bounded by the bridging loops between βE/βF (EF loop) and βG/αB

(BG loop) (41, 43, 50). Structures of SFK SH2 domains revealed that the EF and BG

loops were critically positioned in respect to the ligand-binding, in particular the pY+3

binding, pocket, such that they control substrate accessibility and dictate SH2 domain

specificity (51). Indeed, mutation of a single residue on the EF loop can greatly influence

peptide binding specificity (51-53). For example, replacing a threonine with tryptophan in

the EF loop of Src SH2 domain changed its binding specificity (prefers the pYEEI motif)

to resemble that of Grb2 (prefers the pYxN motif) (52). Thus, small molecular alterations

7

of critical residues may influence the substrate selectivity of a SH2 domain, especially by

modulating the selectivity for residues lying C-terminally to the ligand pY.

In addition to interacting with phosphorylated ligands, SH2 domains themselves can

become phosphorylated. Evidence suggests that phosphorylation alters the binding

properties of SH2 domains. For instance, phosphorylation on Lck (Y192) impaired SH2

binding to pY-peptides/protein (54); and, S690 phosphorylation in the SH2 domain of the

p85α subunit of phosphoinositide 3-kinase (PI3K) reduced pY-protein binding and was

associated with the feedback inhibition of PI3K/protein kinase B (Akt) pathway (55). In

contrast, Tensin-3 SH2 domain phosphorylation increased substrate binding and

enhanced the biological activity of Tensin-3 (56). Therefore, modulating SH2 binding

through phosphorylation may be a general mechanism that controls SH2 functions.

1.1.1.4.2 Genetic Mutations of SH2 Domains in Human Diseases

Mutations in SH2 domains have been linked to more than 10 distinct clinical

disorders (57). These mutations typically affect conserved amino acids involved in

protein stability and folding or ligand binding. The vast majority of the mutations occur

in Bruton’s tyrosine kinase (Btk), SH2 domain containing 1A (SH2D1A), and protein

tyrosine phosphatase non-receptor 11 (Ptpn11), with only a few occurring in other

proteins (57). Missense mutations within the SH2 domain of Btk cause X-linked

agammaglobulinemia, with approximately two thirds of the mutations affecting residues

involved in phosphopeptide binding and specificity (57). For example, mutations of a

conserved arginine within the pY binding pocket in αA (R288Q, R288W) and amino

acids surrounding the hydrophobic pocket for binding the ligand pY+3 residue in αB and

the BG loop (Y334S, Y361C, L369F) reduced peptide binding 3 to 200 fold (58). Other

8

types of mutations include structural and functional mutations that alter the conformation

of Btk SH2 domain, which can result in an overall change in protein stability and kinase

activity (59-61). In comparison, mutations in SH2D1A SH2 domain are mostly structural,

leading to decreased half-life of the protein; and mutations in the phosphatase Ptpn11

alter the substrate binding profiles of the variant SH2 domain in the RASopathies Noonan

syndrome and LEOPARD syndrome (62-64).

Several proteins harbouring SH2 domain mutations induce neoplastic disorders. In

particular, the gain-of-function mutants of Ptpn11 and p85α activate oncogenic pathways

and promote transformations in multiple human cancers (65-68). Ptpn11 SH2 domain

mutation occurs in approximately 30% of myelodysplastic syndrome and 2% of leukemia

patients (57); and is highly implicated for juvenile myelomonocytic leukemia (69, 70) as

well as identified in pediatric leukemias such as B cell acute lymphoblastic leukemia and

acute myeloid leukemia (AML) (65). Most of the mutations affect residues located at the

N-terminal SH2 and PTP domain interaction interface, which stabilizes the self-inhibited

conformation of Ptpn11. Disruption of the interface leads to enzyme hyperactivation (65).

Likewise, mutations in p85α cluster in the inhibitory interaction interface between its C-

terminal SH2 and the C2 domain of the PI3K catalytic subunit p110α, causing aberrant

enzyme activation (68). This kind of mutation in p85α occurs in approximately 9% of

human glioblastomas (71). In comparison, non-sense mutations in the C-terminal SH2

domain of RasGAP result in a truncated and inactive version of the protein, and were

detected in three cases of basal cell carcinomas (72). Finally, SH2D1A SH2 domain

mutations cause X-linked lymphoproliferative disorder (73). Thus, modulation of SH2

function appears to be a mechanism associated with diverse cancer pathologies.

9

1.1.2 Biological Function of Phosphorylated Tyrosines

Phosphorylation of a tyrosine can regulate the function of a protein primarily by

two means: 1) by changing its binding properties with other biomolecules, or 2) by

modulating the activity of the protein, frequently through the induction of a

conformational change in the parent protein (3, 4, 6, 74). By using these modes of actions,

pY play pivotal roles in various cellular functions ranging from surface receptor signaling

to transcriptional activation.

First, pY can change the interaction profile of its parent protein by creating a

binding site for interacting partners. Protein domains, such as SH2 and protein tyrosine

binding (PTB) domains, can selectively bind pY-containing molecules by recognizing

specific sequence motifs surrounding the pY. The selective binding of SH2/PTB domains

to pY motifs is a key mechanism that controls the dynamic assembly, localization, and

regulation of pY-mediated functions (extensively reviewed in 74, 75, 76). Through these

modular domain-based interactions, TKs, PTPs, and adaptors are joined together to form

an intricate network of proteins that regulates complex cellular functions.

Biological processes that involve the alteration of protein binding by pY include the

signal transduction pathways following growth factor stimulation, cell adhesion via

integrin signaling, or the internalization of cell surface receptors (reviewed in 6, 74). In

growth factor stimulated signaling pathways, when a growth factor receptor, usually a TK

itself, is stimulated by an extracellular ligand, it becomes autophosphorylated in its

cytoplasmic region. This event creates binding sites for downstream molecules. These

downstream molecules, usually containing an SH2 or PTB domain, are thereby recruited

to the location of the receptor and subsequently initiate a signaling cascade (4, 77). For

10

example, in the epidermal growth factor receptor (EGFR) signaling pathway, binding of

epidermal growth factor (EGF) to the receptor leads to the activation and the

autophosphorylation of the cytoplasmic Y1068 or Y1086 residues of EGFR, which recruits

the SH2 domain-containing growth factor receptor-bound protein 2 (Grb2) and ultimately

triggers the rat sarcoma (Ras)-mediated cell survival and proliferation pathways (78, 79).

In these events, binding of Grb2 to EGFR was enabled through phosphorylation of

tyrosines.

Second, pY can stimulate or inhibit the function of its residing protein. A classical

example of this is the regulation of the SFKs through tyrosine-phosphorylations in the A-

loop, C-terminal tail, and SH2 domain (Section 1.1.1.2). Additionally, pY can obstruct

ATP binding; such is the case for cyclin dependent kinase 1 (Cdk1). Phosphorylation

within the glycine loop (Y15) in the ATP interaction site of Cdk1 interferes with the

binding of ATP and “shuts off” the protein (80).

A primary role of pY in cellular regulation is the involvement in transduction of

signals in response to extracellular stimuli such as growth factors, cytokines, or stress

(77). Upon stimulation, a chain of phosphorylation events take place that successively

relay signals from the plasma membrane throughout the cytoplasm, which may

consequently result in a change in the cytoskeleton arrangement, metabolism, or gene

expression of the cell (23, 77, 81). These cellular alterations affect cell cycle progression,

differentiation, apoptosis, as well as oncogenic transformation in human diseases (3).

Therefore, through the transduction of signals, pY plays pivotal roles in many aspects of

life. Examples of major pathways that relay pY-mediated signals include mitogen-

11

activated protein kinase (MAPK) and Janus kinase (JAK)-signal transduction and

activator of transcription (STAT) pathways (reviewed in 5, 6, 74, 77).

1.1.3 Dysregulation of Protein Tyrosine Kinases and Phosphatases in

Haematopoietic Cancers

1.1.3.1 Multiple Myeloma

Multiple myeloma (MM) is the second most prevalent blood cancer and makes up

1.3% of all new cancer cases and 1.8% of cancer deaths in Canada (82). It is a cancer of

the plasma B cells. MM is characterized by the over-proliferation of malignant B cells

(myeloma cells), excessive production of immunoglobulin proteins, and formation of

multiple lesions in large bone cavities, accompanied by symptoms like anaemia, fatigue,

bone or back pain in patients. Conventional treatment for MM consists of chemotherapy

combined with haematopoietic stem cell transplantation. However, treatment of MM is

usually complicated by drug resistance and relapse. As a result, MM continues to be

universally fatal (83). Therefore, improvement in therapies is necessary to achieve better

outcomes with patients.

Fibroblast growth factor receptor 3 (FGFR3) is an RTK that is dysregulated in 15%

of MM cases due to a t(4;14)(p16;q32) translocation that re-locates the FGFR3 gene in

close proximity to the IgH locus. As a result of this translocation, the FGFR3 gene is

frequently over-expressed, occasionally harbouring activating mutations (84).

Dependencies on FGFR3 activation have been demonstrated in MM cell lines carrying

activating mutations of this RTK, where a small molecule inhibitor of FGFR3 was able to

induce apoptosis and differentiation in the MM cell lines Kawasaki Medical School 11

12

(KMS11) and KMS18, which contain the respective Y373C and G384D substitutions in

FGFR3 (85). Y373C is located in the extracellular region and mediates ligand-

independent receptor dimerization, leading to the constitutive activation of FGFR3;

whereas, G384D FGFR3 was only activated when stimulated by a ligand, but was able to

induce aberrant MAPK, STAT1, and STAT3 phosphorylations (86). Moreover, Y373C,

but not G384D, mutant induced transformation in the NIH3T3 mouse embryo fibroblast

cell line (86). These data show that mutations in FGFR3 have different grades of

activation capabilities. Furthermore, inhibiting FGFR3 activation in a KMS11 xenograft

mouse model impeded tumor growth (85), suggesting FGFR3 as a “driving” kinase for

this type of MM. Consistent with the prominent role of FGFR3 in MM cell lines and

murine model, t(4;14) translocation is associated with more aggressive diseases and poor

prognosis in MM patients (84).

Cytokines in the blood and bone marrow microenvironment can activate TK

pathways and induce MM pathogenesis. The most prominently implicated cytokines are

interleukin 6 (IL-6) and insulin-like growth factor 1 (IGF-1). IL-6 binds and activates the

IL-6 receptor, which triggers the JAK-STAT pathway causing alterations in gene

transcription. Interestingly, a key player of the JAK-STAT pathway, STAT3, is

constitutively active in primary CD138-positive MM cells, and inhibition of STAT3 leads

to apoptosis in these cells (87). Additionally, IL-6 knock-out mice failed to develop B

cell cancers, suggesting an essential role of IL-6 in B cell neoplasms (88). On the other

hand, IGF-1 binds and activates the RTK IGF-1 receptor (IGF1R), which is ubiquitously

expressed in MM and the MM-related monoclonal gammopathy of undetermined

significance (MGUS), a condition that usually preceeds MM. One study reported the

13

observation of aberrantly high expressions of IGF1R in approximately 10% of MGUS

and MM (89). Moreover, a number of studies linked the over-expression of IGF-1 or

IGF1R to poor-prognostic subgroups (89-91). In addition, cultured MM cell lines are

sensitive to the inhibition of IGF1R and its related insulin receptor (INSR) by a small

molecule inhibitor, suggesting a dependency on these RTKs for myeloma cell survival

(92). Therefore, cytokine dysregulation may induce abnormalities of pY signaling and

contribute to MM pathology.

In addition to dysregulated TKs, two PTPs are implicated in MM: Ptpn6 (a.k.a.

Shp1) and Ptp4a3 (a.k.a. Prl-3). In 79.4% of primary MM samples, the expression of

Ptpn6 is suppressed by promoter hypermethylation. Although this was not linked to

patient survival, the restoration of Ptpn6 expression by a DNA methyltransferase

inhibitor was accompanied by decreased STAT3 phosphorylation in a cultured MM cell

line, implying a role of Ptpn6 in down-regulating the JAK-STAT pathway (93).

Moreover, the Ptpn6 protein is established as a negative regulator of growth factor

signaling and oncoproteins (94-98), and the PTPN6 gene is widely described as a tumor

suppressor gene (99, 100). As a result, loss of Ptpn6 function may encourage proliferation

and promote MM pathogenesis. In contrast, amplification of Ptp4a3 mRNA and protein

levels was observed in primary myeloma cells. This is associated with tumor cell

migration, invasion, and metastasis in other types of human cancers (e.g. gastric, colon,

rectal cancers, and melanoma) (101-103). However, the function of this amplification in

MM still needs clarification.

1.1.3.2 Acute Myeloid Leukemia

14

AML is the most frequent form of leukemia and comprises approximately 25% of

leukemic cases in Western society, with an incidence of 3.7 per 100,000 persons (104). It

is a cancer of the myeloid cells, marked by the presence of at least 20% maturation-

arrested myeloblasts in the blood stream and bone marrow (105). As a result of the

abnormal accumulation of myeloblasts, AML patients experience symptoms such as

fatigue, bone pain, fever, shortness of breath, easy bruising, and unusual bleeding.

Treatment for AML traditionally includes intensive chemotherapy and haematopoietic

stem cell transplantation, but, with a low success rate. Only approximately 35-40%

younger patients (< 60 years) and 5-10% older adults (> 60 years) are cured 5 years post-

diagnosis (106). Encouragingly, TK inhibitors are undergoing extensive clinical

development for AML; and some have demonstrated promising efficacy in clinical trials

(107, 108), providing a potential alternative for patients who fail to respond to

conventional therapy.

Dysregulation of RTKs (i.e. Flt3, Kit, Met, Mer, FGFR1) is extremely prevalent in

AML (109-112), with an estimated 40-60% of AML patients harbouring abnormalities in

RTK and another 15-25% with mutations in RTK downstream effectors (i.e. Ras, Jak2)

(109, 113). Among these, activating mutations in Fms-like tyrosine kinase 3 (Flt3) have

received highest attention for their role as an important molecular marker and prognostic

factor (114-117).

Flt3 is a transmembrane receptor primarily expressed in myeloid and lymphoid

progenitor cells; and involved in growth factor signaling and hematopoiesis (118-120).

Normally, Flt3 exists as an inactive, unphosphorylated, and monomeric protein. When

stimulated, Flt3 dimerizes through its juxtamembrane region and becomes

15

phosphorylated and active. Genomic alterations leading to the constitutive activation of

Flt3 have been described in its A-loop and the juxtamembrane regions, with the most

common type of mutation being the segmental duplication of several amino acids, or

internal tandem duplication (ITD), in the juxtamembrane domain, presenting in 15-35%

of AML cases (114-117). Flt3-ITD allows ligand-independent receptor dimerization and

activation. This mutation is associated with rapid disease progression, resistance to

therapy, and poorer patient outcomes compared to the patients without Flt3-ITD (121-

123).

Compared to TKs, dysregulation of PTP in AML is less frequent. The most

commonly observed abnormal PTP is the gain-of-function mutant of Ptpn11, primarily

through genetic alterations in its SH2 domain (Section 1.1.1.4.2), which was found in

about 5% of AML patients (62). Ptpn11 is described as an oncoprotein in many cancers

(67) and is associated with Flt3-ITD-induced proliferation in bone marrow progenitors

and primary AML samples (124). Besides Ptpn11, Ptpn7 is amplified in the blasts of

some AML patients, but the functional impact of this amplification has not been clarified

(125).

1.2 Mass Spectrometry Based Proteomics

Mass spectrometry (MS) based proteomics has been developed as a sensitive

method for the large-scale characterization of sample-derived peptides (126). Due to the

nature of MS, the identification and quantification of peptides can be achieved

simultaneously. MS analysis combined with advances in separation and purification

techniques of pY-containing or PTP-derived peptides has enabled global comprehensive

analysis on pY-mediated signaling networks.

16

1.2.1 Mass Spectrometry for Proteomics Studies

MS is an analytical method that measures the mass-to-charge ratio (m/z) of the

ionized analyte in its gas phase. In proteomics research, solutions containing peptides are

first resolved on a reverse-phase chromatography column (commonly packed with C18

resin) and volatilized by an ionization source, for example, electrospray ionization (ESI)

(127). The gas-phase analyte is then transferred into a coupled mass analyzer, which

alternates between a full MS scan that performs comprehensive analysis on the analyte

(MS1 analysis) and up to a set number of MS/MS scans (or MS2 analysis), which records

the fragmentation pattern of a small subset of the analyte ions automatically determined

by the computer. The fragmentation pattern (or MS2 spectrum) can be used to infer the

peptide identity. The recorded data is then searched automatically using one or a

combination of search algorithm(s), such as MASCOT (128), SEQUEST (129), and

X!Tandem (130), against a reference database to assign amino acid sequences to

fragmented ions (reviewed in 131). A typical experiment can generate a list with

thousands of peptides. This approach of coupling liquid chromatography separation to

mass spectrometry (LC-MS/MS) is a powerful technique in proteomics for analyzing

complex biological samples (126, 132, 133).

1.2.2 Label-Free Quantification by Mass Spectrometry

Quantification by MS can be achieved through either label-based (by incorporating

chemical labels or heavy isotopes) (134-136) or label-free approaches (137). The label-

free method is relatively low-cost and can be applied to analyzing primary tissue samples,

in contrast to the label-based method such as stable isotope labelling by amino acids in

17

cell culture (SILAC) (138). In both types of approaches, MS is relatively quantitative

because the extracted quantification information can only be used to compare the same

peptide across different samples, but not different peptides within the same sample. This

is because molecularly-distinct peptides respond differently to MS detection; as a result,

the extracted quantification/molar quantity ratio is characteristic for each peptide.

However, one can overcome this difficulty by applying pre-determined correction factors

to correlate the quantification information of two distinct peptides and compare their

relative molar quantities within the same sample, as described in my previous publication

(139).

1.2.2.1 Measurement by Intensity of MS1 Ion Current

One popular approach in label-free quantification is measurement by MS1 ion

current intensity (reviewed in 137). Specifically, the height or area under the peak of the

extracted ion current chromatography (XIC) of a peptide, generated as the peptide elutes

off the reverse-phase chromatography column, is used as a quantitative measure, due to

the observation that it is linearly related to the peptide quantity (140, 141). This is a

measurement of relative quantities and has a linear range of over three orders of

magnitude (138, 139). However, since the MS2 analysis samples a subset of ions in the

analyte, frequently, a peptide with an XIC is not associated with an MS2 spectrum such

that the peptide can not be positively identified. In this case, the MS1 chromatograph of

multiple samples may be aligned by elution time and cross-referenced to combine the

MS2 spectra libraries, assigning identifications to previously unidentified

chromatographic peaks, allowing the quantification of more peptide ions. This can be

18

done in proteomics software such as MaxQuant that automatically identifies and retrieves

quantification information for peptide ions (142).

1.2.2.2 Selected Reaction Monitoring

Selected reaction monitoring (SRM) is a method used in MS in which a precursor

ion, usually a peptide, with a specific m/z is selectively isolated from a complex sample,

fragmented, and monitored for a defined fragmentation reaction product (143, 144). The

precursor and fragment ion pair is collectively called a transition. Typically more than

one transition is monitored for each targeted peptide, and the co-presence of most of the

transition-defined fragments is required to positively identify the peptide. Moreover,

quantification by SRM MS can be achieved by measuring the intensities of the ion

currents of the product ions (143, 144). This type of MS analysis is usually carried out

with a triple-quadrupole mass spectrometer (e.g. Thermo Scientific TSQ Vantage) and

has the advantage that it eliminates signals form other ion species and increases detection

sensitivity (143, 144). I previously showed that low-level (< 1%) tyrosine

phosphorylations on the SFK Lyn can be sensitively and reproducibly quantified by SRM

MS, demonstrating the utilization of SRM in monitoring protein phosphorylations (139).

1.2.3 Peptide Enrichment

1.2.3.1 Enrichment of Tyrosyl Phosphorylated Peptides

Tyrosyl phosphorylated peptides are low abundance compared to other peptide

species in a biological sample due to three reasons: 1) phosphorylated proteins merely

compose 1-2% of total proteins in a whole cell lysate extract (3); 2) only a few sites are

phosphorylated on a phosphoprotein, leaving the majority of the protein-derived peptides

19

non-phosphorylated; 3) phosphorylation usually occurs at low stoichiometry (139), such

that the non-phosphorylated peptide is in excess of its phosphorylated counterpart. As a

result, pY-specific enrichment must be performed prior to MS analysis to facilitate the

complete sampling of the collection of pY-containing molecules. The most commonly

used methods for phosphopeptide enrichment are antibody-based affinity purification,

immobilized metal affinity chromatography (IMAC), and titanium dioxide

chromatography (145). For purification of tyrosyl phosphorylated peptides, antibody-

based affinity purification has been proven to be very effective (146). An experiment

using this approach may identify up to hundreds of pY sites in a biological system.

Examples of such studies include the identification of activated RTKs and their

phosphorylated substrates without the prior knowledge of the activated pathways (147),

and characterization of downstream pY sites in induced systems (148-150).

1.2.3.2 Enrichment of Oxidized Cysteine-Containing Peptides (qPTPome)

A method was recently developed by our lab in collaboration with the group of Dr.

Benjamin Neel (Ontario Cancer Institute, Toronto) for the purpose of quantifying the

expressed PTPome in a biological system (151). This method exploits the property that

the cysteine-containing catalytic site of all classical PTPs is highly conserved, such that

an antibody developed against the signature motif of Ptpn1, with the critical cysteine

irreversibly “hyperoxidized” to sulfonic acid (VHCSO3HSAG) (152), may effectively

isolate most, if not all, classical PTPs. In particular, cellular PTPs were converted to the

hyperoxidized state, protease-digested, and subjected to immunoprecipitation with the

antibody. This process was coupled to LC MS/MS or SRM to facilitate the quantitative

profiling of isolated peptides as a measure of PTP expression (the qPTPome method). As

20

demonstrated, this approach reliably identified and quantified classical PTPs in a number

of cell lines and tissues (151). This method, combined with the pY profiling techniques,

enables a novel and comprehensive type of analysis of pY regulation in biological

systems.

1.3 Key Statistical Analysis Used in this Thesis

1.3.1 Partial Least Squares Regression

Partial least squares regression (PLSR) is a statistical method to model a set of

response variables based on a large number of predictor variables (153). It attempts to

predict response variables from predictors by simultaneously decomposing the predictor

and response variables into a shared set of orthogonal factors, or components, such that

the amount of variation in the response variables explained by the variation in the

predictor variables is maximized. The underlying model of a PLSR analysis is: X=TPT+E;

Y=UQT+F, where X is an n by m matrix of predictors, Y is an n by p matrix of responses,

T and U are n by l matrices of projections of X and Y, respectively, and P and Q are the

respective m by l and p by l orthogonal loading matrices of X and Y. E and F are matrices

of error terms, assumed to be independent random normal variables that are identically

distributed. X and Y are decomposed so as to maximize the covariance between T and U.

A popular alternative to PLSR is principal component regression (PCR), in which,

instead of decomposing both the predictor and the response variables, the principal

components of the predictor variables are used as predicting factors (154). PCR creates

models that describe the variability in the predictor variables without considering the

variability of the responses. PLSR, however, takes into account the variability of both the

21

response and the predictor variables, therefore, may create models that can fit the

response variables with fewer components. For the purpose of this thesis, PLSR was used

because a specific relationship between the predictors (TKs, PTPs) and the responses

(cellular pY) was sought after, and it was essential to consider the variability of the

responses.

1.4 Specific Aim for this Thesis

The aim of this thesis is to evaluate the hypotheses that 1) the cellular pY state is a

quantitative output of the activities of TKs and PTPs in biological systems (Chapters 2 &

3); and 2) the SH2 domains of SFKs, acting as downstream effectors of pY signaling, are

functionally modulated by phosphorylation (Chapter 4). The model being examined here

is depicted in Figure 1.1. Two human cancer models, MM and AML, were used.

Figure 1.1. A proposed model for the regulation and functional effect of cellular pY.

The cellular pY in a biological system is regulated by the concerted action of tyrosine

kinases (TKs) and protein tyrosine phosphatases (PTPs); and SH2 domains are involved

as a class of downstream effectors/readers of pY signaling, whose function in cells can

generate phenotypic output.

Y pY TK PTP

Effectors/Readers (i.e. SH2 Domains) Phenotype

22

Chapter 2 Comprehensive Analysis of Protein Phosphotyrosine

in Multiple Myeloma

A part of the work described in this chapter has been published as:

Robert Karisch,1,2,* Minerva Fernandez,2 Paul Taylor,3 Carl Virtanen,2 Jonathan R. St-

Germain,3 Lily L. Jin,3 Isaac S. Harris,2 Jun Mori,4 Tak W. Mak,2 Yotis A. Senis,4 Arne

O¨ stman,5 Michael F. Moran,3 and Benjamin G. Neel1,2 (2011) Global proteomic

assessment of the classical protein-tyrosine phosphatome and “redoxome”. Cell. 146,

826-840

The published work include pY and PTP profiling data in MM cell lines (parts of Figure

2.3 A and 2.5 A that show data for cell lines) and the PLSR analysis in MM cell lines

using PTP expression as a predictor for cellular pY (Figure 2.4 A), as Figure 7 A-C in the

publication. The mouse xenograft tumors used in this study were raised by Zhihua Li1,2

and Dr. Suzanne Trudel1,2. The PTP profiling data was provided by Robert Karisch1,2 and

Jonathan St-Germain3, and the PLSR analysis shown in Figure 2.4 A was done by Dr.

Carl Virtanen2. All other biochemical experiments and bioinformatics analyses described

in this chapter were performed by Lily Jin.

1Department of Medical Biophysics, University of Toronto, Toronto M5G 2M9, ON,

Canada 2Campbell Family Cancer Research Institute, Ontario Cancer Institute and Princess

Margaret Hospital, University Health Network, Toronto, ON M5G 1L7, Canada 3Program in Molecular Structure and Function, Hospital For Sick Children, and

Department of Molecular Genetics and McLaughlin Centre for Molecular Medicine and

Banting and Best Department of Medical Research, University of Toronto, Toronto, ON

M5G 1L7, Canada 4Centre for Cardiovascular Sciences, Institute of Biomedical Research, School of Clinical

and Experimental Medicine, College of Medical and Dental Sciences, University of

Birmingham, Birmingham B15 2TT, UK 5Cancer Center Karolinska, Department of Pathology and Oncology, Karolinska Institute,

Stockholm 17176, Sweden

23

2.1 Abstract

The cellular pY and PTP expression profiles in five MM cell lines and their

corresponding mouse xenograft tumors were examined by MS in order to assess the

effect of the total activated TKs and expressed PTPs on the systemic pY output in the

MM cancer model. Biochemical and bioinformatics analyses revealed that distinctive

physiologies were associated with MM cultured cell lines and xenograft tumors, with

different sets of TKs and PTPs implicated in cells and tumors. These results also

demonstrate an association between the activity/expression of the enzymes (i.e.

TKs/PTPs) and the cellular pY profile, supporting a model wherein the global pY output

is dependent on the TK and PTP states in the biological system.

2.2 Introduction

MM is a fatal B cell cancer that arises from transformation during the development

of blood stem cells into normal plasma B cells. The pathogenesis of MM is

heterogeneous (83, 155). One of the most important prognostic factor and oncogenic

driving mechanism in MM is the upregulation and aberrant activation of FGFR3, which

results from a t(4;14)(p16;q32) chromosomal translocation seen in approximately 15% of

MM cases. Inhibiting FGFR3 in vitro and in pre-clinical models have demonstrated

promising anti-proliferative/antitumor effects (85, 156, 157), supporting the development

of FGFR3-targeted therapy for t(4;14)-positive MM. In the recent past, another RTK

IGF1R also emerged as a potential driving kinase in MM. IGF1R was shown as an

important autocrine and paracrine factor that affected MM growth, survival, and drug

resistance (92, 158, 159), which was also aberrantly expressed in MM with its expression

24

significantly linked to disease severity (89, 90). These data, combined with the

observation that the MAPK and PI3K/Akt signaling pathways downstream of RTKs are

frequently altered and aberrantly stimulated in MM (160-162), suggest a likely role of

disrupted pY signaling in MM pathogenesis. Given that MM is still largely incurable (83),

elucidating the regulation of protein pY signaling in MM is of great importance and will

likely reveal novel oncogenic drivers for therapeutic targeting.

Five established human primary tumor-derived MM cell lines representing

heterogeneous subtypes of MM have been selected for a comprehensive study on cellular

protein pY regulation. Three cell lines (KMS11, KMS18, LP1) contain t(4;14), among

which, two (KMS11, KMS18) harbour activating FGFR3 mutations. The FGFR3

mutations carried by KMS11 and KMS18 (Y373C and K650E, respectively) have

different grades of activation capabilities with Y373C producing a more active form of

FGFR3 (Section 1.1.3.1). Correspondingly, the growth rates of KMS11 and KMS18 cells

were reduced by a FGFR3 inhibitor, while the other cell lines were insensitive to the

inhibition (85). Comparatively, the proliferation of KMS11, KMS12, and RPMI8226 cell

lines were inhibited by an IGF1R/INSR inhibitor in vitro, while that of the other cell lines

were not (92). Interestingly, LP1 cells were not sensitive to either inhibitor, thus

representing a subtype with unknown oncogenic driving TKs. These varying responses to

TK inhibitions indicate that diverse pY-mediated mechanisms are associated with the

subtypes represented by the five cell lines. The molecular characteristics described here

are summarized in Table 2.1.

Additional molecular abnormalities have been reported for these cell lines. Somatic

mutations on the oncoproteins p53 (E285K) (163) and K-Ras (G12A) (164) were

25

detected in PRMI8226 with uncharacterized functional implications. Moreover, Mdm2

was up-regulated and promotes proliferation and survival in RPMI8226 cells (165).

Furthermore, gene expression studies identified mRNA over-expression of c-maf in

KMS11, LP1, and RPMI8226 (166); c-myc in KMS11, KMS12, and LP1 (167); and

cyclin d1 in KMS12 (166). These abnormalities provide another layer of dysregulation

that may contribute to MM pathogenesis, and were also summarized in Table 2.1.

MM cells, grown as suspending cells in tissue culture, develop into solid tumors

when injected into mice, suggesting different physiologies are associated with cultured

cells and xenografts. To gain a comprehensive understanding of MM cell and tumor

biology, the five selected cell lines were inoculated into mice to produce xenograft

tumors (by Zhihua Li and Suzanne Trudel, Ontario Cancer Institute, Toronto). The cell

lines and their corresponding tumors were analyzed by Western blots (Section 2.3) and

MS, which generated quantitative profiles of 109 unique pY-containing peptides,

encompassing 106 pY sites, and 36 PTPs across ten samples using label-free

quantification. A comparison of the proteomic signatures showed distinctive differences

between the tumors and cells. Integrated analysis revealed novel relationships between

the activated TKs, total expressed PTPs, and the cellular protein pY (Sections 2.4 - 2.6).

26

Table 2.1. Molecular Characteristics of MM Cell Lines

27

2.3 Western Analysis Showed Distinct Expression, Glycosylation,

Phosphorylation of pY Signaling Molecules in MM Samples

To characterize the MM samples, the expression/phosphorylation of key pY

signaling molecules were examined by Western blots (Figure 2.1), which revealed

distinctive molecular differences among the samples: the expression of FGFR3 and Lyn

(a SFK highly implicated in B cell disorders (25)), as well as the phosphorylation of Lyn

Y508 (inhibitory) and SFK A-loop (activating), were highly varied across MM cultured

cell lines and tumors. In particular, FGFR3 expression were consistent with the genotype,

where elevated levels were seen in the t(4;14)-positive samples with the highest

expressions coincided with FGFR3 activating mutations. Whereas, Lyn Y508 and SFK A-

loop phosphorylations, while showing fluctuations across different MM subtypes, was

generally decreased and increased, respectively, in tumors compared to the cultured cells,

suggesting increased SFK activities in the tumors. Moreover, although its expression was

uniform across the samples, the activating phosphorylation of Erk 1/2 was drastically

increased in the tumors. Because Erk 1/2 is a downstream effector of MAPK signaling

that controls growth and proliferation, this data suggests a tumor-specific up-regulation of

MAPK pathways. Unlike FGFR3/Lyn and like Erk 1/2, the IGF1R/INSR expression was

ubiquitous and mostly uniform across the MM samples. However, like FGFR3, IGF1R

was heavily asparagine (N)-glycosylated in MM (Figure 2.1 A). The fact that

glycosylated-IGF1R was resistant to Endo H but not PGNase F suggests that only hybrid

and complex, but not high-mannose, oligosaccharides were attached to IGF1R.

Interestingly, IGF1R appeared under-glycosylated in KMS18 (Figure 2.1 A right, note

the downshift of the 100 kDa band) and hyper-glycosylated in the tumors compared to

28

the cell lines (Figure 2.1 A right, note the disappearance of 75 kDa bands in Lanes 6-10

compared to Lanes 1-5). Glycosylation protects proteins from degradation and impacts

localization (168), therefore, altered glycosylation implies changes in stability and

localization of the RTKs. Finally, the global protein pY profile varied across the samples,

potentially as an output of the differentially regulated pY signaling molecules (Figure 2.1

B, pY blot). Taken together, these Western data show diverse features in pY signaling

molecules/effectors not only across the cell lines, but also between cultured cells and

their cognate tumors, suggesting that distinctive protein pY regulations are at play in

these MM samples.

29

Figure 2.1. MM cell lines have distinctive molecular features

A, Western blots showing bands of FGFR3 and IGF1R before and after deglycosylation

by the glycosidase endoglycosidase H (Endo H) (removes asparagine-linked high-

mannose oligosaccharides) or PNGase F (removes asparagine-linked high-mannose,

hybrid, and complex oligosaccharides from glycoproteins). B, Western blots showing the

total pY, expressions of INSR, Lyn, and Erk 1/2, as well as the phosphorylations of A-

loop in SFKs, Y508 in Lyn, and T202/Y204 in Erk 1/2. Beta-actin was used as a loading

control.

A

B

30

2.4 pY Profiling Revealed Distinctive Differences between MM

Cultured Cell lines and Xenograft Tumors

To gain an in-depth understanding of the pY regulation in MM, comprehensive

quantitative pY profiles were generated for the ten MM samples. To this end, cell- or

tumor-derived proteolytic peptides, equalized by total protein amounts, were enriched for

pY-containing molecules by immunoprecipitation. The enriched fractions were analyzed

by MS. The MS results were searched automatically against the human International

Protein Index (IPI) database (ftp://ftp.ebi.ac.uk/pub/databases/IPI/last_release/; v3.68;

87,061 FASTA entries) for peptide identifications (see flowchart in Figure 2.2 A). This

experiment was repeated once. A total of 109 unique pY peptides, corresponding to 106

pY sites, were identified across two replicates of ten MM samples.

The total numbers of MS/MS spectra for pY peptides, as well as unique pY peptides,

unique pY sites, proteins associated with pY peptides, and kinases identified in each MM

sample are shown in Table 2.2. In the case that the identified peptide sequence is

conserved in more than one protein, only one protein is counted to represent the group. A

comparison across the cell lines showed that KMS12 had the lowest incidences of

identifications, consistent with a phenotype that lacked an association with aberrant TK

activation, while the t(4;14)-positive cell lines contained significantly more incidences of

pY identifications. Curiously, the number of pY identifications in RPMI8226 were

comparable with that of the t(4;14)-positive cell lines. Since KRAS mutation was

observed in RPMI8226 cells (164), up-regulation of the MAPK pathways, which have

been implicated in MM (162), could be one potential mechanism that gives rise to the

high count of pY identifications. A comparison between the cell and their cognate tumor

31

samples revealed only 36-54% overlap between the unique pY sites identified (Figure 2.2

B), with generally more identifications observed in cultured cells than in tumors. Motif

analysis of the 106 total pY sites revealed an enrichment of the signature A-loop-

bounding sequences DFG…APE (Figure 2.2 C). Since phosphorylation of Y within the

A-loop suggests increased catalytic activity of the parent kinase (Section 1.1.1.1), this

observation implies an abundance of activated kinases in MM. Indeed, 22 out of 109

peptides correspond to phosphorylations within the A-loop of kinases (including TKs,

Serine/Threonine kinases, and dual-specific kinases). Among these, nine peptides,

representing seven proteins, were derived from TKs (refer to Figure 2.3 B).

32

Figure 2.2. pY profile reveals difference between cell and tumor and an abundance

of TK A-loop phosphorylations

A, a flowchart showing schematic overview of experimental procedures. MM cells were

injected into mice to produce xenograft tumors by Zhihua Li (Ontario Cancer Institute)

and all other experiments were performed by Lily Jin. B, Venn diagrams of unique pY

sites identified in MM cell and tumor samples for each cell line. C, sequence logos

showing the abundance of surrounding residues (corresponding to the sizes of letters) of

106 pY sites identified in MM. The conserved A-loop-bounding sequences are

highlighted in red.

A B

C

33

Table 2.2. Number of proteins, peptides, and pY sites identified in MM cells and

tumors

34

Next, I examined the quantitative profile of the identified pY peptides (raw

quantification data in Appendix Table 1). A heatmap based on the quantification levels of

the pY peptides was created. Unsupervised hierarchical clustering separated the cell and

tumor samples into two distinct groups according to the pY profiles (Figure 2.3 A),

suggesting distinguishable differences between the cells and tumors. A closer

examination revealed that a total of ten peptides were significantly different between the

cells and tumors, with paired Student’s t-test p value < 0.05 (Figure 2.3 B), which include

the MAPK1 pY187-containing peptide that is on average 2.8-fold higher in tumors and the

tyrosine kinase 2 (Tyk2) pY292-containing peptide that is on average 3.2-fold more

abundant in cells. Moreover, the inhibitory phosphorylation (Y15) in Cdk 1/2/3 was

significantly higher (on average by 4.1-fold; p < 0.01) in cells than in tumors. Since the

Cdk’s are essential for driving each phase of a cell cycle (169), this data suggests

enhanced cell cycle progression in the tumors. Together, these data indicate that pY

signaling may be differentially regulated in MM cells and tumors through the action of

different kinases, which may be reflected on downstream molecules (e.g. Cdk 1/2/3) as

effectors of the pY regulation.

Because of the noted abundance of A-loop pY in MM, and phosphorylated A-loop

represents the activations of its parent kinase, I hypothesized that the activated TKs in

MM dictate the overall cellular pY. If this were true, unsupervised hierarchical clustering

based on the levels of the A-loop pY along should separate the cells from tumors. To this

end, I generated a heatmap based on the quantitative profiles of TK A-loop pY in MM

samples (Figure 2.3 C). As the results indicate, the samples were clustered into two

distinct groups, mostly separating the cells from tumors, suggesting that the activation of

35

subsets of TKs was responsible for the different cell and tumor pY signature. However,

KMS12 tumor and RPMI8226 cells were clustered reciprocally with the cells and tumors,

respectively. The reason may be that high-level phosphorylation in the A-loops of FGFR3

and Lyn (or Hck, which contains the same A-loop-derived tryptic peptide sequence as

Lyn) in KMS12 tumor confers a cell-like signature, while the activation of Src (or Yes,

Fyn, Lck, which contain the same A-loop-derived tryptic peptide sequence as Src) and

low phosphorylation of FGFR3 in RPMI8226 cell render it more similar to tumors.

36

Gene Site

Y Kinase Site

A B

C

Gene Site Cell/Tumor

Figure 2.3. Quantitative pY profile

distinguishes cell from tumor. A, a heatmap

showing unsupervised hierarchical clustering

based on the quantitative pY profile in MM. B,

a heatmap showing unsupervised hierarchical

clustering based on ten peptides whose levels

were found to be significantly altered between

cell and tumor samples. The gene, site, and the

cell to tumor fold change are given on the right.

C, a heatmap showing unsupervised

hierarchical clustering based on TK A-loop

phosphorylations. Alternative proteins that

contain the same A-loop derived tryptic peptide

sequence are shown in brackets.

37

To further dissect the relationship between activated TKs and cellular pY, I

analyzed the co-variation between cellular pY levels and TK A-loop phosphorylations by

PLSR (153). This analysis produced mathematical models based on the assumption that

the variations in cellular pY levels can be predicted based on the variations in TK A-loop

phosphorylations. Because my previous analysis showed distinctive pY features

associated with MM cells and tumors, the cell and tumor samples were analyzed

separately. The PLSR algorithm automatically determined three-component models for

both cells and tumors wherein 99.8% and 99.9% of variations in cellular protein pY could

be predicted based on TK A-loop phosphorylation levels in cells and tumors, respectively.

The first and second components in the model for cells were able to predict 86.5% and

9.8% of pY variations (Figure 2.4 A) and the first two components in the model for

tumors were able to predict 74% and 14% of pY variations (Figure 2.4 B), respectively.

Among all the tested TKs, FGFR3 and Ptk2 correlated best with Component 1 in cells,

and Src (or Yes, Fyn, Lck) correlated best with both Component 2 in cells and

Component 1 in tumors. Abelson Tyrosine-Protein Kinase 1 (Abl1) and FGFR3

correlated best with Component 2 in tumors, while also contributing to Component 1.

These TKs were implicated by this analysis as key modulators of pY signaling in their

perspective MM system. A comparison between the models revealed a reduced influence

of FGFR3 and a increased influence of Src (or Yes, Fyn, Lck) on the cellular protein pY

in the tumors than in the cells, consistent with the prominent role of SFKs downstream of

signaling of growth factors and cytokines that may present in the tumor

microenvironment of the animal model. These results also suggest Ptk2, Abl1, and Src

38

(or Yes, Fyn, Lck), in addition to the well-established oncogenic driver FGFR3, as

candidate cancer drivers.

Figure 2.4. Cellular pY variation can be predicted based on TK activation levels

A and B, correlation plots of the A-loop phosphorylation of TKs and the predicting

components computed by the partial least squares regression (PLSR) algorithm.

Alternative proteins containing the same A-loop derived tryptic peptide sequence are

given in brackets. Percentage in brackets indicates the portion of variation in cellular pY

predicted by the associated component.

A B

39

2.5 Co-Variance Analysis of PTP and pY Profiles Implicated a Subset

of PTP in pY Regulation

In order to assess the influence of negative enzymatic regulation on cellular pY and

develop a comprehensive understanding of pY regulation in MM, PTP expression

profiles in MM samples were produced in our lab through collaboration with Robert

Karisch, a former graduate student in Dr. Benjamin Neel’s lab (Ontario Cancer Institute,

Toronto), and by using the qPTPome method (151). The expression levels of a

complement of 36 classical PTPs were examined by SRM MS, among which, 24 were

found to be expressed in our samples (Appendix Table 2). Using the PTP expression

profile, I performed unsupervised hierarchical clustering to seek relationships among the

MM samples (Figure 2.5 A). Interesting, this analysis generally separated the cell and

tumor samples into two clusters, showing that, in addition to cellular pY and TK

activation, the regulation of PTP expressions was also different between cells and tumors.

The exceptions were LP1 tumor and KMS12 cell, which were clustered reciprocally with

the cell and tumor groups, respectively. Moreover, the cognate cell and tumor samples of

KMS12 and LP1 cell lines were paired up respectively (p < 0.05), indicating that the PTP

expressions in these cell lines were influenced more by the genotype than the growth

environment. This observation was not seen in the clusters based on pY or TK A-loop

phosphorylations, and may suggest that genotype exerts a heavier influence on PTP

expressions than on pY, which is more dynamic and responds quicker to environmental

stimuli.

To further dissect the relationship between PTPs and cellular pY, PLSR analysis

was applied to generate models wherein PTP expression levels were used as predictors

40

for cellular pY levels. Again, the cell and tumor samples were analyzed separately. The

analysis on the five cell samples was done by Dr. Carl Virtanen (Ontario Cancer Institute).

A three-component model was generated, which showed that 99.3% of variations in pY

levels were predictable based on PTP variation. In particular, Component 1 predicted

97.2% and Component 2 predicted 1.7% of variations (Figure 2.5 B). Moreover, the

fluctuation in Ptpn1, Ptpn6, and Ptpn11 expressions (correlated best with Component 1)

collectively predicted 97.2% of the variations in the pY sites analyzed. Notably, this was

a positive correlation, where increased PTP expression corresponded to increased pY

levels, which was consistent with the prominent role of Ptpn1 in RTK signaling (96, 170,

171) and Ptpn11 as a highly implicated oncoprotein in haematopoietic cancers (64, 67).

Moreover, this was the first time a correlation between total pY and PTP expression was

demonstrated in a biological system, and was published as a part of a paper in Cell (151).

Next, to understand the role of PTPs in the regulation of pY in MM tumors, I

performed a PLSR analysis and discovered that, with a three-component model, 95.5% of

pY variations in the five MM tumor samples could be predicted based on PTP expression.

In particular, Component 1 predicted 27% and Component 2 predicted 58% of variations

(Figure 2.5 C). Moreover, Ptpn9 and Ptpn11 correlated best with Component 1, and

Ptpn7 and Ptprg correlated best with Component 2, which collectively predicting a

combined 85% of variations in total pY levels. This analysis implicated these PTPs in pY

regulation in MM tumors. The fact that different sets of PTPs were implicated for cells

and tumors implies that the dephosphorylation of pY was differentially regulated, further

confirming that distinct molecular biologies were associated with xenograft tumors and

cultured cells.

41

Figure 2.5. PTP expression profiles predict cellular pY

A, a heatmap showing unsupervised hierarchical clustering based on PTP expression

profiles in MM. The z-scores of the quantification values of each PTP-derived peptide

across the ten samples were used. Black indicates no detection. B and C, correlation plots

of PTP expression and the predicting components computed by the partial least squares

regression (PLSR) algorithm.

A B

C

42

2.6 Correlation Heatmap Revealed Regulation “Hotspots”

To identify hubs of co-regulated molecules, correlation heatmaps were generated.

These heatmaps were used to define relationships that likely involve proteins within the

same pathway or functional processes. In detail, Pearson correlation coefficients between

pY levels and TK A-loop phosphorylations or PTP expressions were calculated. The

correlation matrix was then used to produce a correlation heatmap while applying

unsupervised hierarchical clustering. These heatmaps revealed high-density regions of

positive correlations, or regulation “hotspots”, highlighted by Boxes 1 through 8 (Figure

2.6 A and B). PTPs/TKs associated with these regions are highly positively correlated

with subsets of pY, suggesting a functional connection between these enzymes and the

associated pY sites (a list given in Table 2.3). The modular appearance of the hotspots

suggests the presence of distinct and independent networks of enzymatic pY regulation.

Consistently, the existence of independent signaling pathways that separately contribute

to MM biology have been repeated reported, which include the IL-6/STAT signaling axis,

MAPK pathways, and the Lyn/PI3K/Akt functional module (28, 160, 172). Within the

correlation hotspots, I noted the co-variation of Pptn1, Ptpn6, and Ptpn11 expressions

with Src A-loop phosphorylation in MM cells (Box 1), and Ptpn9, Ptpn11, and Ptpn7

expressions with MAPK protein phosphorylations in MM tumors (Box 5). I have shown

that variations in the expressions of Pptn1, Ptpn6, and Ptpn11 were able to predict 97.2%

of pY variations (Figure 2.5 B) and Src correlated with a component that was able to

explain 9.8% of pY variations (Figure 2.4 A) in the cell samples. A high degree of

correlation among these enzymes could suggest cooperation in pivotal pathways. Indeed,

regulation of Src activity by Ptpn1, Ptpn6, or Ptpn11 was reported for separate systems

43

(94, 173, 174), particularly Ptpn1 was found to contribute to the oncogenesis of colon

cancer cells through Src activation (173). One hypothesis is that Pptn1, Ptpn6, and

Ptpn11 may function through Src to regulation pY signaling in MM cell lines. In addition,

MAPK1 pY187 was significantly increased in the tumors compared to their cognate cell

samples (Figure 2.3 B) and Erk 1/2 phosphorylation was up-regulated in tumors (Figure

2.1 B), suggesting augmented activity of the MAPK pathway in tumors. The fact that

MAPK phosphorylation correlated with the PTPs (Ptpn9, Ptpn11, Ptpn7) highly

implicated in tumors (Figure 2.5 C) is consistent with a hypothesis that these enzymes

play important roles in regulating pY signaling in tumors. This analysis provides a rich

information pool from which regulatory insights can be gained and hypotheses can be

generated such that, with additional experimentation, key oncogenic drivers of MM may

be uncovered.

44

Figure 2.6. PTP and TK activation is positively correlated with subsets of pY

A and B, correlation heatmaps showing unsupervised hierarchical clustering based on the

Pearson correlation coefficients of PTP expression or TK activation with cellular pY in

MM cells (A) and tumors (B). The boxes highlight observed regions of intense positive

correlations.

45

Table 2.3. Proteins and sites corresponding to regulation “Hotspots”

Alternative proteins containing the same tryptic peptide sequence are given in brackets.

46

2.7 Discussion and Conclusion

The biochemical and bioinformatics analyses described in this chapter aimed at

assessing the enzymatic influence of TKs and PTPs on systemic pY levels in a biological

system. MM, a haematopoietic cancer in many cases linked to dysregulation in pY

signaling, was used as a model disease. Five established MM cell lines were selected for

this study to represent different subtypes of MM. Initial examinations of the pY signaling

molecules and pY profiles revealed dramatic differences between the MM cultured cell

lines and their associated xenograft tumors (Figure 2.1 and Figure 2.3 A). These results

subsequently led to analyzing the cell samples and tumors as separate biological systems.

Co-variance between the activation/expression of the TKs/PTPs and cellular protein pY

gave rise to theoretical models, which demonstrated that close to 100% of pY variations

could be predicted based on fluctuations in TK activation (Figure 2.4 A and B) and PTP

expression (Figure 2.5 B and C) levels. These results show that cellular pY levels may be

subjected to systemic regulation by enzymes in a cell, supporting my model described in

Figure 1.1.

The impact of TK on cellular pY profile is widely appreciated. Prior studies have

demonstrated the application of using pY profiles for the identification of aberrantly

activated signaling pathways (147, 175) and TKs as biomarkers and drug targets in

cancer (176, 177). Moreover, phosphoproteomics was used to identify targets of kinase

inhibitors (178-180) and downstream effectors of mutant kinases (181, 182). These data

show that the effect of TK regulation/dysregulation is manifested in the cellular pY states.

As such, the pY profiles can be used to reverse-predict key functioning TKs in a cellular

system as demonstrated here. The bioinformatics approach used in my study implicated

47

FGFR3, Ptk2, and Src (or Yes, Fyn, Lck) in MM cell lines and Src (or Yes, Fyn, Lck),

Abl1, and FGFR3 in the corresponding xenograft tumors. Particularly, my analysis

showed that almost 100% of cellular pY variations in MM were predicted based on TK

activation levels, with a single component (Component 1) predicting 86.5% and 74% in

MM cells and tumors, respectively (Figure 2.4 A and B). Among the implicated TKs,

FGFR3 is a known prognosis factor in MM whose over-expression/mutation is linked to

aggressive diseases and poor patient outcomes (183). Consistently, I showed that the

FGFR3 activation level correlated best with Component 1 in the PLSR-generated model

for cells (Figure 2.4 A) and likely contribute to pY regulation in the tumors (Figure 2.4

B). The activation of Ptk2 (also known as FAK1) co-varied with that of FGFR3 in the

cells, suggesting Ptk2 may function with FGFR3, possibly as an immediate downstream

effector of FGFR3. Increased Ptk2 levels were found in a wide range of metastatic

diseases (184) and the over-expression of Ptk2 was associated with disease progression

and extramedullary infiltration in MM (185). My data provides a potential mechanistic

link between Ptk2 and its function in MM, which may be highly related to FGFR3

dysregulation. Another implicated enzyme, Src, is a well-established oncoprotein

associated with many transformed cell types (24, 186) and a target in MM (187). Integrin

β7 knockdown in myeloma cells led to the inhibition of both Ptk2 and Src

phosphorylation, which correlated with reduced cell adhesion and migration, as well as

altered bone marrow homing (188), suggesting a role for Ptk2 and Src in the disease

progression of MM. Additionally, Fyn was required downstream of IL-6 signaling in MM

cell lines (26), demonstrating a link between Fyn and cytokine signaling in tumor

microenvironment. Notably, Src (or Yes, Fyn, Lck) is highly implicated (correlated best

48

with Component 1) in the xenograft tumors (Figure 2.4 B), consistent with a role in

disease progression and tumor biology. Finally, although it is an established driver in

chronic myeloid leukemia (189), the BCR-ABL1 gene fusion was only detected in one

instance in a MM cell line (190) and the function of Abl1 in MM is still unclear. In

summary, my analysis represents a novel approach for examining cellular pY profiles to

identify the potential driving TKs in the system. Furthermore, this analysis shortlisted

TKs that may be key regulators in the MM systems examined.

In contrast, my data did not show a strong reference to IGF1R activation in MM,

however, the immediate downstream interactors of IGF1R, insulin receptor substrate

(IRS) 1 and IRS2, were found to be phosphorylated in my samples (see Appendix Table

1). Particularly, two Y sites in IRS1 (Y612, Y632) and three Y sites in IRS2 (Y742, Y675,

Y598) were phosphorylated, with the highest levels seen in KMS18 and LP1 samples. As

described before, KMS18 and LP1 cell lines were resistant to IGF1R inhibition (Table

2.1); and the IRS proteins were known to be involved in the feedback regulation of

IGF1R, reportedly through phosphorylation of serines (191). Therefore, the high

phosphorylation in the IRS proteins in KMS18 and LP1 may reflect the corresponding

suppression of IGF1R, which may explain the insensitivity of these cell lines to IGF1R

inhibition.

Using a similar co-variance analysis approach, the impact of PTP expression on

cellular pY was examined in the MM cell and tumor systems. This method generated

theoretical models wherein 99.3% and 95.5% of pY variations could be predicted by the

changes in PTP expressions in cells and tumors, respectively, which implicated Ptpn1,

Ptpn6, and Ptpn11 in cells and Ptprg, Ptpn23, Ptpn9, and Ptpn11 in tumors (Figure 2.5 B

49

and C). Markedly, a single component alone (refer to Figure 2.5 B, Component 1 that

correlated with Ptpn1, Ptpn6, and Ptpn11) in the model for cells predicted 97.2% of pY

variations. Astonishingly, a positive relationship between the PTP expressions and pY

levels was suggested by the models.

Although PTPs were traditionally regarded as negative regulators of pY, evidence

now shows that PTPs positively regulate a number of cellular processes in various

systems (192, 193). For example, Ptpn11 is a known oncoprotein upstream of the MAPK

signaling pathway and positively regulates cell growth and proliferation (192). Moreover,

Ptpn1 activates Src by dephosphorylating the inhibitory Src Y527 site in human breast

cancer cell lines (170); and Ptp4a1 (a.k.a. Prl-1) enhances cancer cell invasion and

migration by increasing Src and Erk 1/2 pathway activation (194). Mechanistically, PTPs

can promote the activation of signaling pathways by dephosphorylating inhibitory sites

on TKs or docking sites on RTKs for binding inhibitory biomolecules. Alternatively, it

can be part of the feedback regulation and up-regulated by upstream pY signaling. By

these means, PTPs can be positively correlated with protein pY and may serve as an

indicator for predicting the cellular pY levels.

I identified six PTPs that may play a key role in regulating protein pY homeostasis

in MM samples. Three of these PTPs were implicated in MM: Ptpn6 is a reported tumor

suppressor and is hypermethylated in primary myeloma samples (93); whereas Pptn1

participates in RTK signaling (195) and its depletion in the t(4;16)-pos/FGFR3mut KMS11

cell line can lead to increased FGFR3 phosphorylation and global pY levels, suggesting

Pptn1 as a key negative regulator of FGFR3 (151). This apparent contradiction with the

finding that Ptpn1 positively correlated with protein pY in MM (Figure 2.5 B) and

50

FGFR3 phosphorylations (Figure 2.6; Table 2.3 Box 1) reflects the complexity of cellular

pY regulation: one possible explanation is that MM cells attempt to overcome the effects

of the hyper-activated FGFR3 by stimulating the expression of its negative regulator

Ptpn1. Another implicated PTP, Ptpn11, is an established oncoprotein (62, 67) and

reportedly protects MM cells against dexamethasone-induced apoptosis by acting

downstream of IL-6 (196). Moreover, Ptpn11 is required for transforming oncogenic

FGFR3-expressing NIH 3T3 cells (197). Although the remaining three PTPs were not

implicated in MM, they were associated with other malignancies:, Ptprg is reportedly a

candidate tumor suppressor (198), whereas, Ptpn9 down-regulates RTK signaling in

breast cancer cells (199). In addition, Ptpn7 is genetically amplified and over-expressed

in myeloid malignancies (125). The role of these PTPs in MM still needs elucidation.

My results show that distinctive molecular characteristics were associated with MM

cells and tumors (Figure 2.1, 2.3, 2.5 A), in agreement with this, different sets of

TKs/PTPs in MM cells and tumors were implicated as potential key regulators of the

cellular protein pY (Figure 2.3 C and D, 2.4 B and C). These data imply that tumor-

specific biologies are at play when myeloma cells are exposed to the tumor

microenvironment of the animal model. In particular, increased Erk 1/2 (Figure 2.1 B)

and MAPK1 Y187 (paired Student’s t-test p value < 0.05) phosphorylations were observed

in the tumors compared to the cultured cell lines, and MAPK 1/3 phosphorylations were

highly correlated with the PTPs (Ptpn9, Ptpn11, Ptpn7) implicated in the tumors (Table

2.3; Figure 2.6 B, Box 5). These data imply that MAPK signaling may be important for

MM tumor development. Consistently, mutations of components of the MAPK signaling

pathway are common in human cancers (200) and inhibiting p38 MAPK hampered MM

51

cell growth in the bone marrow milieu (201), supporting a pro-proliferative role of

MAPK signaling in myeloma cells in the tumor microenvironment. In further agreement,

small molecule inhibitors targeting the MAPK signaling pathway have been assessed in

clinical trials and yielded encouraging results (202). Together, these data suggest a

dependency on the up-regulation of MAPK pathway for myeloma cells residing in the

tumor microenvironment, which is a phenomenon less preserved in the cultured cell lines.

In contrast to the MAPK signaling proteins, phosphorylation of the TK Tyk2 (Y292) was

significantly increased in the cultured cells (by 1.9 to 9.1-fold) compared to their cognate

tumors (paired Student’s t-test p value < 0.05). This site was shown to be downstream of

interferon α signaling (203). Also, Tyk2 protein itself was reportedly involved in the

signaling of cytokines such as interferon and IL-6 (204-206). The fact that Tyk2 pY292

was lower in the tumors suggested a tumor suppressing role for this phosphorylation.

Consistently, enhanced tumor growth and metastasis of breast cancer cells were observed

in Tyk2(-/-) mice (207). These data support a negative regulatory role for Tyk2 pY292 in

MM tumor growth, conceivably by down-regulating signaling of cytokines.

My correlation heatmaps showed distinctive regulation hotspots where subsets of

pY sites were highly positively correlated with sub-groups of enzymes (Figure 2.6).

These data show that there may be hubs of independent pY-mediated protein networks in

MM. Consistently, past studies indicate that distinct pY-signaling pathways may

individually contribute to MM cell survival. Particularly, while knocking-down or

activating one pathway did not seem to impact another pathway, silencing of at least two

pathways were required to severely reduce cell viability (28, 160, 172). These

observations suggest redundant pY signaling in MM that must be individually addressed

52

in order to achieve a therapeutic benefit. These redundant and non-overlapping pY

signaling networks may be captured by the regulation hotspots in the correlation

heatmaps. For example, the kinases whose activating phosphorylation were highly

correlated, such as MAPK3, Src (or Yes, Fyn, Lck), and dual-specificity Y-

phosphorylation regulated kinase 1B (DYRK1B) in Box 1 and Lyn (or Hck), Abl1,

PTK2B, MAPK1, and HIPK2/3 in Box 3 (Table 2.3), could represent key enzymes of

separate pY signaling axes in MM that may share related functional consequences (i.e.

MM cell proliferation and survival), while the other proteins associated with the hotspots

may be interactors or effectors of the perspective pathways. Further experimentations

should be carried out to figure out the interplays among these proteins, which may help to

unravel the complex pY-mediated networks in MM. Moreover, the difference between

the pY-signaling networks in MM cells and tumors should be noted here, which was

demonstrated by the apparently different nature of the hotspots recognized in cells and

tumors (refer to Figure 2.6, Table 2.3).

Finally, protein pY in the diverse MM subtypes represented by the selected cell

lines is likely differentially regulated by different sets of enzymes. This is reflected by the

multi-component models generated by the PLSR approach: each component may

represent an axis of pY regulation that is maintained in a certain MM subtype. Consistent

with this notion, FGFR3 is highly implicated in the MM cells, whose activation variation

was able to explain 86.5% of the systemic pY variation, reflecting the significant role of

FGFR3 in t(4;14)-positive cell lines. Along that line, Src (or Yes, Fyn, Lck), which

correlated best with Component 2 in the same model, may be a key regulator of pY

signaling in t(4;14)-negative cell lines. Therefore, even enzymes correlated with the more

53

minor components can be explored for their potential roles in MM subtypes wherein a

driving mechanism was still unidentified.

In conclusion, I showed a strong correlation between the activated TKs/expressed

PTPs and the cellular protein pY levels, suggesting a systemic influence of the state of

these enzymes on protein pY homeostasis in MM, in support of the model proposed in

Figure 1.1. In particular, the TKs FGFR3, Ptk2, and Src (or Yes, Fyn, Lck) and PTPs

Ptpn1, Ptpn6, and Ptpn11 in cultured cells, as well as the TKs Src (or Yes, Fyn, Lck),

Abl1, and FGFR3 and PTPs Ptpn7, Ptpn9, Ptpn11, and Ptprg in xenograft tumors were

implicated in their perspective systems as best protein-predictors and potential key

regulators of cellular pY levels. My analysis also implied that the enzymatic regulation of

protein pY in MM likely contains hubs of independent networks, which may represent

individual axis of pY signaling pathways (Figure 2.6). Lastly, my data showed distinctive

differences between the pY networks of the cultured MM cell lines and their cognate

xenograft tumors, consistent with the previous demonstration that the tumor

microenvironment altered the characteristics of myeloma cells and supported tumor

growth, proliferation, and drug resistance (208). In sum, this proteomics study

demonstrated a novel approach for analyzing protein pY regulation by enzymes on the

systemic level, which generated valuable insights into the enzymatic regulation of pY in

MM.

54

2.8 Materials and Methods

Materials

For Western blotting, anti-Lyn rabbit antibody was from AbD Serotec (Oxford,

UK); FGFR3 (B-9) and β-actin (C-4) antibodies were from Santa Cruz Biotechnology

(Santa Cruz, CA); anti-phosphotyrosine antibody, clone 4G10 was from Merck Millipore

(Billerica, MA); p44/42 MAPK (Erk 1/2), IGF-1 receptor β, insulin receptor β (mouse),

phospho-p44/42 MAPK (Thr202/Tyr204), phospho-Src family (Tyr416), and phospho-

Lyn (Tyr508) antibodies were from Cell Signaling Technology (Danvers, MA).

Stabilized goat anti-rabbit and anti-mouse horseradish peroxidase (HRP) conjugated

antibodies were obtained from Thermo Fisher Scientific (Waltham, MA). Fluor-S

MultiImager for imaging and Laemmli Sample Buffer (2 x) were ordered from Bio-Rad

Laboratories (Hercules, CA). Iscove’s modified dulbecco’s medium (IMDM) was

ordered from Life Technologies (Paisley, Scotland). For immunoprecipitation (IP), anti-

pY antibody (anti-pTyr-100, PhosphoScan Kit) for phosphopeptide purification was from

Cell Signaling Technology. For MS analysis, dithiothreitol (DTT) and trypsin-TPCK (1

mg/mL) for protease digests were purchased from Cell Signaling Technology. C-18

powder (Fluka silica gel 100 C-18-Reversed-phase) for peptide desalting was ordered

from Fluka Sigma Aldrich. Sep-Pak Classic C18 Cartridge for peptide purification were

purchased from Waters (Milford, MA). All other chemical reagents were purchased from

Sigma Aldrich, and aqueous solutions were prepared using Milli-Q grade water (Merck

Millipore).

Cell lines, Cell Culture and Xenograft Tumor

55

Human MM cell lines were maintained in IMDM medium, supplemented with 5%

fetal bovine serum (FBS). To obtain xenograft tumors, four to eight week old male

NOD/SCID (Nonobese diabetic/severe combined immune deficiency) mice were

inoculated subcutaneously over the two shoulders and two hips with 107 MM cells in 200

µL 50% matrigel basement membrane matrix (DB, Franklin Lakes, NJ) at each site. The

animal was sacrificed when tumors reached 1 cm. The harvested tumors were

immediately frozen on dry ice and stored at -80 °C until usage.

Non-Denaturing Cell and Tissue Lysis

To obtain non-denatured whole cell lysates, cultured MM cells were pelletted by

centrifugation (1 000 x g, 4 °C, 5 min), washed once with phosphate buffered saline (PBS)

pH 7, resuspended in NP-40 cell lysis buffer (50 mM Tris-HCl pH 8, 150 mM NaCl, 1%

NP-40, with 1.5 µM aprotinin, 20 µM leupeptin, and 0.4 mM AEBSF) at 250-300 µL

buffer per 107 cells, and inverted at 4°C for 30 min. For MM xenograft tumors, the tumor

tissue was homogenized in 0.5-1 mL NP-40 cell lysis buffer at room temperature (rt),

then mixed at 4 °C for 30 min. The lysates were centrifuged (15 000 x g, 4 °C, 10 min) to

remove non-soluble materials. Protein concentrations were obtained by Pierce BCA

protein assay (Pierce Thermo Scientific).

Denaturing Cell and Tissue Lysis

MM cells pelleted by centrifugation (1 000 x g, 5 min) were sonicated in urea lysis

buffer (20 mM HEPES pH 8, 9 M urea, 1 mM Na3VO4, 2.5 mM sodium pyrophosphate,

1 mM β-glycerophosphate) and inverted at 4°C for 30 min. For xenograft tumors, the

MM tumors were briefly homogenized in urea lysis buffer and inverted (4°C, 30 min).

56

The lysates were cleared by centrifugation (15 000 x g, 4 °C, 10 min) and the cleared

supernatant was subjected to trypsin digestion.

In Vitro Deglycosylation of Receptor Tyrosine Kinases

A total of 14 µg whole cell lysate proteins (see Non-Denaturing Cell and Tissue

Lysis) were diluted 1:5 into 10 µl Glycoprotein Denaturing Buffer (BioLabs) and heated

at 100 °C for 10 min for denaturation. The heated proteins were incubated with 1 µl

PNGase F or Endo H (both at 500,000 U/ml) at 37 °C for 1 h. An equal volume of 2 x

Laemmli Sample Buffer was added to stop the reaction and for subsequent analysis by

Western. A negative control was similarly prepared without the addition of PNGase F or

Endo H.

Western Blotting

Proteins separated by SDS-PAGE were electrophoretically transferred to an

Immobilon-P membrane (Millipore), which was blocked in 5% BSA with shaking (rt, 1

h), incubated first with the specified primary antibody in 1% BSA (4 °C, overnight), and

then with HRP conjugated antibody in 1% BSA (diluted 1:5000 from 1 mg/ml stock; rt, 1

h). Three washes in Tris buffered saline (TBS) supplemented with 1% Tween were

performed after each antibody incubation. The membrane was detected using Immun-Star

WesternC Kit (Bio-Rad Laboratories) by manufacturer’s protocol and imaged on film

(Clonex) or in the Fluor-S MultiImager (Bio-Rad Laboratories) for relative protein

quantifications.

Protein Digestion by Trypsin

57

Proteins dissolved in buffer were reduced by adding DTT to a final concentration of

20 mM (rt, 1 h), and then alkylated by adding iodoacetamide to a final concentration of

40 mM (rt, 30 min in the dark). A total of 2% trypsin (w/w) was added and the protein

solution was rotated (rt, overnight) to ensure complete digestion. For analysis by MS, the

tryptic peptides were further subjected to peptide desalting.

Peptide Desalting

For purification of 1-10 mg peptides, peptide containing solution was acidified to a

final concentration of 1% TFA and loaded onto a Sep-Pak Classic C18 Cartridge, pre-

conditioned with 5 ml 100% acetonitrile and 7 ml 0.1% TFA. The cartridge was washed

with 12 mL 0.1% TFA (in 1 ml, 5 ml, and 6 ml installments) and eluted serially with 10%,

20%, 30%, and 40% acetonitrile in 0.1% TFA (1.4 ml each). The eluate was frozen on

dry ice and lyophilized (rt, 48 h).

Enrichment of Peptides by pY Antibody

Desalted peptides were dissolved in 100 µL IAP buffer (50 mM MOPS pH 7.2, 10

mM sodium phosphate, 50 mM NaCl) and mixed with 10 µL anti-pTyr-100 beads (4 °C,

overnight with inversion). The beads were washed three times in IAP buffer, twice in

PBS, and then eluted into 30 µL 0.15% TFA, which was analyzed by mass spectrometry.

Mass Spectrometry Analysis

For comprehensive pY and PTP profiling in MM, enriched peptides were resolved

by reverse-phase chromatography with an automated nanoliter-scale LC system (Easy-

nLC, Proxeon Biosystems A/S, Odense, Denmark), using a 0-35% gradient of HPLC

buffer A (0.1% formic acid in HPLC water) to HPLC buffer B (0.1% formic acid in

58

acetonitrile) on a homemade C-18 analytical column (75 mm × 12 cm × 6 µm tip;

Proxeon), over 120 min at a flow rate of 250 nL/min. The analytical column was coupled

with a Thermo-Fisher LTQ-Orbitrap mass spectrometer (Thermo Scientific) for data

acquisition. For the full MS scan, the target value was 3,000,000 with 120 ms maximum

injection time and 70,000 resolution at m/z 400; for MS/MS, the ion target value was

1,000,000, with 120 ms maximum injection time and 17,500 resolution at m/z 400.

MS/MS spectra were generated by collision-induced dissociation (CID) with 35%

collision energy and obtained in a data-dependent manner by automatically switching

between a full MS scan and up to 10 MS/MS scans. A dynamic ion mass exclusion list

was maintained with a 20 s time window to avoid repeated sequencing of the same ion.

Peptide Identification and Quantification based on Mass Spectrometry Data

For pY profiling in MM, MS/MS spectra were extracted by BioWorks version 3.3

(Thermo Fisher Scientific) and searched using SEQUEST (Thermo; version 27, rev. 12)

and X! Tandem (www.thegpm.org; version 2006.04.01.2), against the international

protein index (IPI) HUMAN database (v3.68, downloaded from

ftp.ebi.ac.uk/pub/databases/IPI, 87,061 protein entries), allowing 2 missed cleavages by

trypsin, with 0.5 Da fragment ion mass tolerance and 0.02 Da parent ion tolerance.

Cysteine carboxyamidomethylation (C+57.02146) was indicated as a fixed modification,

while phosphorylation of Ser/Thr/Tyr (STY+79.96633 Da) and oxidation of Met

(M+15.99491 Da) were indicated as variable modifications. The peptide identity was

validated manually in Scaffold software (version Scaffold-01_06_05, Proteome Software

Inc., Portland, OR) and only considered acceptable if with greater than 95.0% probability

as specified by the PeptideProphet (209) and ProteinProphet (210) algorithms. For

59

manual quantification of pY peptide by MS ion current intensity, the ion current

chromatograph peak of a peptide was extracted by specifying its m/z value in Xcalibur

(Thermo Fisher Scientific, Version 2.0.7 release) and was subjected to curve smoothing

with BoxCar set to 7. The integrated peak area of XIC was calculated using the Toggle

Peak Detection function in Xcalibur with default settings and was used as quantification

measure of the peptide. Out of 109 peptides, the XIC for 75 peptides (68%) were found in

both biological replicates and their derived quantification values were averaged across the

replicates.

Motif Analysis of pY Sites

Peptide sequences containing the 15 flanking residues before and after the central

pY site of the complement of 106 pY sites identified in MM samples were submitted to

an online software Seq2Logo (211) (http://www.cbs.dtu.dk/biotools/Seq2Logo/), which

generated sequence logos with the size of the letters proportionally to the corresponding

residue frequency.

Generation of Heatmaps Based on Peptide Quantifications

For MM and AML samples, the peptide intensities, extracted manually in Xcalibur

or by MaxQuant, respectively, were compared to the maximum intensities of

corresponding peptides and expressed in a range between 0 and 1. A z-score was

calculated for each quantified values (including zeros). For both MM and AML data,

unsupervised clustering was performed with Cluster 3.0 software (Version 2.11) (212).

All heatmaps were visualized and exported as image files by Java Treeview (Version

1.1.5r2; http://jtreeview.sourceforge.net/).

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For correlation heatmap, Pearson correlation coefficients of PTP expression or TK

phosphorylation levels against the phosphorylation levels of the pY sites in five cell and

five tumor samples were calculated in Microsoft Office Excel 2003

(http://www.microsoft.com/en-ca/default.aspx). Unsupervised clustering and heatmap

generation was performed using Cluster 3.0 as described above.

Partial Least Squares Regression (PLSR) Analysis

PLSR analysis was performed with the R (version 2.13.0; http://www.r-project.org/)

package PLS (http://mevik.net/work/software/pls.html). Prior to the analysis, the

profiling data were filtered to remove the PTPs or pY sites with fewer than three

measurements across all the samples. The PLSR algorithm uses the PTP expression or

TK A-loop phosphorylation levels as a predictor matrix X, and attempts to predict the

variations in cellular pY, represented as the response matrix Y. It simultaneously

decomposes the predictor and response matrices into a common set of orthogonal factors

and specific loadings using the formula: X = TPT; Y = UCT ~= TBCT, where T is the

score matrix, P is the loading matrix, B is a diagonal matrix of regression weights, and C

is a weight matrix. T and U were chosen in such a way to maximize their covariance.

“Leave-one-out’’ cross-validation automatically determined the optimal number of

components to use for the prediction. The R source code is given below:

library("pls")

Y<-read.table("PREDICTOR MATRIX TABLE", header=TRUE, sep="\t",dec=".")

Y<-as.matrix(Y)

X<-read.table("RESPONSE MATRIX TABLE", header=TRUE, sep="\t",dec=".")

X<-as.matrix(X)

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plsrresults<-plsr(Y ~ X,validation="LOO")

corrplot(plsrresults, comps=1:2, labels="names", cex=0.7, font=2)

62

Chapter 3 Comprehensive Analysis of Protein Phosphotyrosine

in Acute Myeloid Leukemia

The work described in this chapter was included in a manuscript entitled:

“Phospho-proteomic analysis of the protein-phosphotyrosine landscape in acute myeloid

leukemia”

Jiefei Tong1,8*, Mohamed Helmy6*, Florence M.G. Cavalli2,8*, Lily Jin3,8, Jonathan St-

Germain3,8, Robert Karisch4,7, Paul Taylor1,8, Mark Minden7, Michael D. Taylor2,5,8,

Benjamin G. Neel4,7, Gary D. Bader3,6, and Michael F. Moran1,3,7,8

The pY profile in AML samples was generated by Dr. Jiefei Tong1,8 (Figure 3.1 A) and

the PTP profile was generated by Rob Karisch4,7 and Dr. Jiefei Tong1,8 (Figure 3.2 A).

The bioinformatics analyses in this chapter were performed independently by Lily Jin.

1Program in Molecular Structure & Function, Hospital for Sick Children, Toronto. 2Program in Developmental & Stem Cell Biology and Arthur and Sonia Labatt Brain

Tumour Research Centre, Hospital for Sick Children, Toronto. 3Department of Molecular Genetics, University of Toronto. 4Departmet of Medical Biophysics, University of Toronto. 5Department of Laboratory Medicine and Pathobiology, University of Toronto. 6The Donnelly Centre, University of Toronto. 7Princess Margaret Cancer Centre, Toronto. 8Peter Gilgan Centre for Research and Learning, Hospital For Sick Children, 686 Bay

Street, Toronto, ON, M5G 0A4, Canada.

*Equal contributions were made by these authors.

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3.1 Abstract

To further dissect the relationship between activated TKs, expressed PTPs, and the

cellular pY, 12 human primary AML samples were obtained. MS-based proteomics

analysis generated a quantitative pY profile for the 12 samples and a PTP expression

profile for a subset (eight out of 12) of the samples. A collection of 219 unique pY sites

and 16 PTPs were quantified. Co-variance analysis showed a high degree of

correspondence between TK activation/PTP expression levels and the cellular pY, which

also implicated a subset of TKs and PTPs in pY regulation in AML.

3.2 Introduction

Dysregulation of pY signaling networks is common in cancer cells and is frequently

linked to somatic mutations and altered enzymatic functions. This is exemplified by AML,

a myeloid cancer with heterogeneous disease pathology often relating to mutations in pY

signaling molecules (Section 1.1.3.2). Inhibiting aberrantly activated TKs in AML have

demonstrated promising therapeutic potentials, implying the importance of pY signaling

in AML (213). Moreover, profiling of phosphoproteins in AML by reverse-phase protein

arrays defined protein signature groups that correlated with response and survival,

suggesting that AML may be stratified into prognostic groups with distinct

phosphorylation networks (214). Monitoring the signaling responses of single AML

cancer cells by multiparameter flow cytometry suggests extensive remodeling of the

signaling network at the single-cell level (215). These data provide a rationale for

performing proteomics studies and elucidating the molecular wirings of pY signaling in

AML.

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The reciprocal actions of TKs and PTPs constitute important steps of pY regulation.

Given the critical relationships between pY signaling and cancer (7, 8, 24, 200) (Section

1.1), it is unsurprising that a number of TKs and PTPs are highly implicated in human

malignancies: TKs are well-established targets in neoplastic disorders and 37 PTPs were

linked to cancer with approximately half described as oncoproteins and the other half as

tumor suppressors (31). Flt3 with ITD mutation and Pptn11 are well-known positive

drivers and prognostic indicators in AML (Section 1.1.3.2). Additionally, distinct pY

patterns in primary samples and cell lines (214-216) and changes in PTP expressions (217)

have been reported for AML. These data combined with the demonstration that PTP

expression profiles affect cellular pY (151) make a curious case that how the activated

TKs and expressed PTPs impact cellular pY in AML. A model depicted in Figure 1.1 was

examined in this study using AML primary samples.

Twelve human AML primary samples were obtained and analyzed by MS (patient

information given in Table 3.1). Based on the MS analysis, quantitative pY profiles were

produced for the 12 samples; due to sample limitation, PTP profiles were only generated

for eight of the 12 samples. Integrated analysis of the pY and PTP profiles revealed

interesting insights into the pY-TK-PTP interplay and implicated a number of PTPs and

TKs in AML.

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Table 3.1. AML patient information corresponding to primary samples

FAB is abbreviated for French-American-British classification; FLT3-ITD denotes Flt3

internal tandem duplication; NR, No Tx, and CR denote no response, no test, and

complete remission. Patient data was provided by Dr. Mark Minden (Princess Margaret

Cancer Centre, Toronto).

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3.3 pY Profiling Revealed Distinctive Features in Patient Subgroups

and Implicated a Subset of TKs in pY Regulation

To produce the pY profiles, whole cell lysate proteins extracted from AML samples

were digested by trypsin and enriched for pY-containing tryptic peptides through

immunoprecipitation by Dr. Jiefei Tong in our lab. The enriched peptides were analyzed

by MS, and the result files were given to me for computational analysis. The files were

searched against the UniProtKB/Swiss-Prot human protein FASTA database (2013

September release; 540,958 sequence entries) for peptide identifications. The phospho-

modified peptides were then quantified by label-free quantification in the MaxQuant

software (142). This work produced the quantitative profile for 219 pY sites on 159

proteins across 12 AML primary samples (Figure 3.1 A; Appendix Table 3). Some TKs

highly implicated for AML (e.g. Flt3, Kit, Syk) were identified: activating mutations of

Flt3 and Kit were frequently observed in AML (Section 1.1.3.2) (218) and Syk was

recently identified as an AML target (219). A sequence logo based on the 219 pY sites

suggested a prevalence of the TK A-loop phosphorylations by showing an enrichment of

the conserved A-loop-bounding signature sequences DFG…APE (Figure 3.1 B). A close

examination of the dataset revealed a collection of eight TKs whose A-loops were

tyrosine-phosphorylated, indicating stimulated kinase activities for these TKs. A heatmap

of the A-loop phosphorylations is shown in Figure 3.1 C.

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Figure 3.1. Characterization of pY in AML primary samples

A, a heatmap showing unsupervised hierarchical clustering based on the quantitative pY

profile in AML, with sample IDs labelled on top. B, sequence logo showing the

abundance of surrounding residues (corresponding to the sizes of letters) of 219 pY sites

identified in AML. The conserved A-loop-bounding sequences are highlighted in red. B,

a heatmap showing unsupervised hierarchical clustering based on TK A-loop

phosphorylations. The z-scores of the quantification values of each peptide across the

AML samples were used. Alternative proteins containing the same tryptic peptide

sequence are given in brackets. D, Bar graphs of the summed MS signal intensities of the

complement of cellular pY-containing peptides (top) and TK A-loop-derived

phosphopeptides (bottom). A Pearson’s correlation coefficient summarizing the

relationship between the top and bottom graphs is shown. ****p<0.0001.

A

Kinase Site

B

C

Group 1 Group 2

D Pearson’s coefficient=0.94****

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Unsupervised hierarchical clustering based on either the total pY or TK A-loop

phosphorylations separated the AML samples into two groups (p < 0.01): generally a

group with high phosphorylations and a group with low phosphorylations. For pY-based

clusters (Figure 3.1 A), the low-phosphorylation group (Group 1) contained seven

samples, all of which had low TK A-loop phosphorylations (Figure 3.1 C and D; sample

IDs: 240, 385, 347, 286, 454, 395, 118). Comparatively, the high-phosphorylation group

(Group 2), which comprised five samples, had relatively highly phosphorylated TK A-

loops (Figure 3.1 C and D; sample IDs: 9217, 215, 272, 135, 212). Consistent with this, a

correlation heatmap of TK phosphorylation levels against 219 cellular pY sites showed a

largely positive relationship (Figure 3.2 B; judged by the overwhelming red color in TK-

associated lanes). Moreover, the Pearson correlation coefficient between the total MS

signals generated by the complement of pY peptides (containing 219 pY sites) and TK A-

loop-derived phosphopeptides was calculated to be 0.94 (p < 0.00001) (Figure 3.1 D).

These data show that TK A-loop phosphorylations positively correspond with the levels

of cellular pY.

The eight TKs identified in the AML samples were clustered into two groups based

on their A-loop phosphorylation levels (Figure 3.1 C): a group of five TKs (Btk, Fes, Tec,

Syk, and Fgr) that are generally highly phosphorylated in the high phosphorylation group

and a group of three TKs (Abl2, Lyn, and Lck) whose A-loop phosphorylation is

generally low except in one patient (sample ID: 9127). This type of grouping scheme was

reproduced in the correlation-based cluster where the groups of five and three TKs were

included in Groups B and A (Figure 3.2 B) of the TK-associated clusters, respectively.

These data further demonstrate a correspondence between cellular pY and TKs:

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subgroups of TKs may be upstream of distinctive sets of pY sites and modulate pY

through distinct pathways. Boxes 4 and 5 in Figure 8 B highlight regions of intense

positive correlation where pY sites (listed in Table 3.2) are positively correlated with

clusters of phosphorylated TKs. These regions suggest a relationship in which the

implicated TKs are potential upstream regulators of the associated pY sites.

Taken together, these data indicate that TK activation/phosphorylation may

positively regulate the cellular pY levels. They also showed that distinctive pY features,

namely high or low overall phosphorylations, were associated with subgroups of AML

patients.

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Figure 3.2. PTP expression and TK activation are correlated with cellular pY

A, a heatmap showing unsupervised hierarchical clustering based on PTP expression

profile in eight AML samples. The z-scores of the quantification values of each PTP-

derived peptide across the AML samples were used. B, a correlation heatmap showing

unsupervised hierarchical clustering based on Pearson correlation coefficients of PTP

expression or TK phosphorylation with the levels of 219 pY sites. Boxes highlight

regions of high-density correlations. Representative pY site positively correlates with

PTP and negatively correlates with TK (MAPK pY187), or negatively correlates with PTP

and positively correlates with TK (Syk pY526), is indicated.

B A Group 1 Group 2

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Table 3.2. Proteins and sites associated with boxed regions in Figure 3.2 B

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Next, to quantitatively define the relationship between activated TKs and the

cellular pY, a PLSR analysis was performed. The algorithm automatically determined an

eight-component model that was able to predict 100% of variations of cellular pY based

on TK A-loop phosphorylation levels (as an indicator of TK activation), with the first

three components predicting 85.6% of the variations collectively. Figure 3.3 A shows the

correlation plot of TK A-loop phosphorylations with Components 1 and 2. As shown,

Syk, Fes, and Fgr correlated best with Component 1, predicting 46% of cellular pY

variations, and Abl2 and Lck (or Src, Yes, or Fyn that share the same A-loop tryptic

peptide sequence as Lck) correlated best with Component 2, predicting 29% of pY

variations. Notably, Syk, Fes, and Fgr belong to the collection of five TKs whose A-loops

are generally highly phosphorylated in the high phosphorylation group of patient samples;

and Abl2 and Lck belong to the class of three TKs that generally have low

phosphorylations in all the samples. These data indicate that two major axis of pY

regulation by different sets of TKs may be present; therefore, different pY regulation

schemes may possibly define AML subtypes. This analysis also implicates the TKs Syk,

Fes, Fgr, Abl2, and Lck (or Src, Yes, Fyn) as major pY modulators in AML, whose

activation levels were able to collectively predict 75% of pY variations.

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Figure 3.3. Cellular pY variation can be predicted based on PTP expression or TK

activation levels

A and B, correlation plots of TK A-loop phosphorylation (A) or PTP expression (B) and

the predicting components computed by the partial least squares regression (PLSR)

algorithm.

A B

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3.4 Integrated Analysis of PTP Expression and Cellular pY Implicated

PTPs in AML pY Regulation

To gain a comprehensive overview of pY regulation in AML, the TK antagonist

enzyme PTPs were quantitatively analyzed in eight AML samples (a subset of the 12

primary samples). An expression profile of the entire collection of classical PTPs (the

expressed PTPome) was generated by the MS-based qPTPome method (151), through the

combined effort of Rob Karisch (Ontario Cancer Institute, Toronto) and Dr. Jiefei Tong

in our lab. A total of 16 PTPs were shown to be expressed, for which a quantitative

profile was generated across the eight samples by label-free quantification in MS

(Appendix Table 4). The generated profiles were passed on to me for bioinformatics

analysis. Unsupervised hierarchical clustering based on the quantitative PTP expression

profiles distinguished two patient subgroups, with Group 1 containing three samples that

expressed relatively higher levels of PTP compared to Group 2, which comprised five

samples (Figure 3.2 A). The fact that this grouping of patients share little commonality

with the clustering of patients based on pY or TK A-loop phosphorylations (compare

Figure 3.2 A to Figure 3.1 A and C) shows that PTPs are not simply negative regulators

of cellular pY, but whose regulation of cellular pY involves a more complicated inter-

relation. To visualize the relationship between PTP expression and cellular pY levels, a

correlation heatmap was created. An integrated heatmap showing correlations between

TK phosphorylation/PTP expression and the levels of 219 pY sites is presented in Figure

3.2 B. Clusters of positive and negative correlations are highlighted by Boxes 1 to 5 and

the list of associated pY sites are given in Table 3.2. The pY sites showing positive

correlations with TKs and negative correlations with PTPs may be subjects of the net

75

antagonistic regulation of phosphorylation by TK and dephosphorylation by PTP. An

example of this is the A-loop phosphorylation of Syk, which was positively correlated

with TK phosphorylations but negatively correlated with the expression of PTPs such as

Ptpn11, Ptpra, and Ptpn1 (Figure 3.2 B, as indicated; Box 3). Conversely, pY sites that

negatively correlate with TK and positively correlate with PTPs may demonstrate indirect

regulation by these enzymes. An example of this is the A-loop phosphorylation of

MAPK1 (Figure 3.2 B, as indicated; Box 1). Syk is a target in AML (219) and MAPK1 is

downstream of mitogen-activated protein kinase kinase kinase 1 (MEK), another AML

target (220). These data show that AML targets/their related pathways may be

differentially modulated by TKs and PTPs. Together, these observations suggest diverse

mechanisms associated with PTP-mediated regulation of pY-containing polypeptides in

AML.

To further elucidate the relationship between PTP expression and the cellular pY, a

PLSR analysis was performed, which showed a high degree of predictability of pY levels

based on PTP expression. Only 11 out of the 16 expressed PTPs were quantified in at

least three of the AML samples and were used for this analysis. Using an automatically

determined six-component model, the fluctuations in PTP expression levels were able to

predict 100% of pY variations, with Component 1 along predicting 98.88% of pY

variations (Figure 3.3 B). Out of 11 PTPs tested by the algorithm, ten PTPs, namely

Ptpn1, Ptpn6, ptpn7, Ptpn9, Ptpn11, Ptpn12, Ptpra, Ptprc, Ptpre, and Ptpro, correlated

extremely well with Component 1. The expression levels of these PTPs almost

completely predicted the variations in cellular pY levels, demonstrating their important

role in pY regulation. Since PTPs are being considered as drug targets in AML (221, 222),

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this observation, combined with the previous notion that PTPs may modulate known

AML targets, builds up the rationale for targeting PTP in AML.

3.6 Discussion and Conclusion

Worldwide efforts have gone into defining genomic signatures for guiding the

development of personalized treatment for human cancers. This movement reflects the

acknowledgement that cancers frequently arise from genomic perturbations that change

gene dosage or function of the altered gene product (223). Prognostic gene expression

signatures were suggested for AML (224, 225); however, the utilization of cancer

genomics is limited in the clinic, partly due to a lack of supporting evidence and deep

mechanistic insights into the functions and interplay of various gene products suggested

by the signature (226). The low correspondence between mRNA levels and protein

abundances exacerbates the problem (227-230). To resolve the conundrum, proteomics

studies can be used to associate cancer gene products to functional consequences and

potentially to define cancer subclasses. Although identification of oncogenic signaling

pathways (231, 232)/therapeutic targets (233) and classification of cancer subtypes (234,

235) through phosphoproteomics have been demonstrated in the past, a relationship

between the total collection of cellular enzymes (i.e. TKs/PTPs) and phosphosites was

not comprehensively assessed until recently (151). Here I present the integrated analysis

of the expressed PTPs, activated TKs, and the cellular pY in 12 primary AML samples,

which shows a systemic impact of the expressed/activated enzymes on cellular pY sites

and provides novel insights into the collective regulation of pY by enzymes in AML.

The application of qPTPome combined with pY profiling, which showed a well-

correlated positive relationship between the expressed PTPome and the cellular pY, was

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first demonstrated in MM cell lines (151). This analysis implicated Ptpn1, Ptpn6, and

Ptpn11 in MM cell pY regulation. The extended application of this method on MM

xenograft tumors showed a drastically different molecular relationship and implicated a

different set of PTPs in pY regulation in MM tumors (refer to Figure 2.5, compare B and

C), suggesting that different regulatory pathways through PTPs are utilized in

physiologically distinct systems. Consistent with this notion, the integrated analysis in

AML primary samples revealed features distinctive to that of MM and may be unique to

AML. Remarkably, the expression levels of ten out of the 11 PTPs tested by the PLSR

algorithm collectively predicted 98.88% of variations in cellular pY. This data implies a

high-degree of dependency for cellular pY on PTPs in AML, suggesting a significant role

of PTP in pY regulation. Since the dysregulation of pY is important for AML pathology

(Section 1.1.3.2), this observation provides a rationale for targeting PTPs in AML.

The ten PTPs implicated by PLSR analysis have all been connected to human

neoplasms. Besides Ptpn11, which is a well-established oncoprotein (62, 67), eight PTPs

(Ptpn1, Ptpn6, ptpn7, Ptpn9, Ptpn12, Ptpra, Ptprc, Ptpro) were reported as potential tumor

suppressors with four of these (Ptpn1, Ptpn6, Ptpn7, Ptpra) also described as potential

oncoproteins (31). Half of the PTPs were directly linked to AML: Ptpn11 is associated

with Flt3-ITD-induced proliferation in AML bone marrow progenitors and primary

samples (124), and the gain-of-function mutant of Ptpn11 was found in approximately

5% of AML cases (62). Genetic amplification of the PTPN7 gene was observed in a

subset of AML blasts (125). Moreover, the up-regulation (i.e. Ptprc, Ptpro) and

alternative splicing (i.e. Ptpn6) of PTP mRNAs in AML primary samples were reported

(217, 236). The tumor suppressor role of the PTPs was mainly attributed to their abilities

78

to down-regulate oncogenic pY signaling. For example, both Ptpn9 and Ptpn12 were

reported to negatively regulate HER2 and EFGR signaling in breast cancer cells (199,

237); and the over-expression of Ptprc led to reduced JAK/STAT-mediated cytokine-

induced signaling (238). Conversely, PTPs may be oncogenic through the stimulation of

the activation of Src or MAPK/AKT signaling pathways (i.e. Ptpra or Ptpn1, respectively)

(239-241). Probing into the functional mechanisms of the implicated PTPs in AML may

unveil key oncogenic pathways, identify disease markers, and find cancer-driving

enzymes that may facilitate therapeutic treatment of AML. Therefore, the approach

demonstrated in this study may serve as a screening methodology for identifying

candidate PTPs that may be targeted in AML.

The other side of pY regulation to PTP-mediated dephosphorylation is

phosphorylation by TKs. Indeed, my analysis of the 219 pY sites identified in AML

revealed a complement of eight TKs, whose increased activities are represented by the

phosphorylation of their activation loop tyrosines. These TKs demonstrate highly positive

correlations with the cellular pY levels (Figure 3.1 D and 3.2 B), and the variations in the

TK activation levels were able to collectively predict 75% of the variations in pY (Figure

3.2 D). These data indicate a major influence, albeit not as big as that of the PTPs, of the

activated TKs on cellular pY, and implicate five TKs, namely Syk, Fes, Fgr, Abl2, and

Lck (or Src, Yes, Fyn). Some of the implicated TKs (Abl2, Fgr, Lck, Src, Yes, Fyn) were

products of known oncogenes (24, 242) and Fes were shown to have both oncogenic and

tumor suppressing characteristics (243). Moreover, many of the TKs (Syk, Kit, Src, Lyn)

were reported as targets in AML (219, 244-247) with their oncogenic potentials possibly

imparted by their involvement downstream of key signaling pathways. In particular, Syk

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and Fes are both involved downstream of Flt3 signaling associated with the Flt3-ITD

mutation (248, 249), and Syk was also downstream of mTOR proliferative signaling (219,

250). Additionally, Src promotes AML cell survival through STAT proteins (251) and

inhibition of Src and Kit kinases enhances targeting of AML stem cells by chemotherapy

(244). Furthermore, Fgr expression was related to early commitment and differentiation

events in the monocytic and granulocytic lineages of AML blasts (252), and Abl2 was

identified as a gene fusion partner of the ETV6/TEL oncogene in AML (253). Taken

together, these data are consistent with my discovery that these TKs may play important

roles in regulating cellular protein pY in AML on the systemic level. Therefore, this

study shows a generic approach for the discovery of candidate TKs as therapeutic targets

in cancer. This approach may also be useful for suggesting the responses of primary

AML tumors to TK inhibitors ex vivo.

The 12 AML samples were clustered into two groups based on cellular pY, a high

pY and a low pY group (Figure 3.1 A). The total level of pY seems to share a high

correlation with the total level of the TK activation in the system (Figure 3.1 D and 3.2 B).

These results suggest potential classification scheme based on cellular pY levels, which is

consistent with previous observation that phosphorylation signatures in AML can be used

to stratify patients into different prognostic groups (214).

In conclusion, the comprehensive analysis on 12 primary AML samples described

here demonstrates a systemic approach for assessing the influence of TKs/PTPs on

cellular pY. The TKs/PTPs implicated here may be critical for pY signaling in AML and

are candidate targets. Moreover, the results demonstrated in this chapter support the

model depicted in Figure 1.1 that describes cellular pY as a quantitative output of the

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total expressed PTPs and activated TKs in the system. Therefore, this study, in addition to

the study on MM cell lines and xenografts (Chapter 2), provides another line of evidence

that TKs and PTPs systemically regulate the cellular collection of pY.

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3.6 Materials and Methods

Materials

The sources of all materials used in this study are as specified in Section 2.8 under

“Materials”.

Patient Selection and Sample Preparation

PBMCs of diagnostic AML patient primary bone marrows were obtained from the

Princess Margaret Hospital leukemia repository, with REB approval. Cryopreserved

AML cell suspensions were stored in liquid nitrogen (2 x107 cells per aliquot) until usage.

Denaturing Cell Lysis

Primary PBMCs from AML patients were sonicated in urea lysis buffer (20 mM

HEPES pH 8, 9 M urea, 1 mM Na3VO4, 2.5 mM sodium pyrophosphate, 1 mM β-

glycerophosphate) and inverted (4°C, 30 min). The non-soluble material was pelleted by

centrifugation (15,000 x g, 10 min) and the cleared supernatant was subjected to trypsin

digestion (see Section 2.8 Protein Digestion by Trypsin), peptide desalting (Section 2.8

Peptide Desalting), and anti-pY enrichment (Section 2.8 Enrichment of Peptides by pY

Antibody) prior to MS analysis.

Mass Spectrometry Analysis

For pY and PTP profiling in AML, the tryptic peptides were loaded onto a 50-cm

Easy-Spray column with a 75-µm inner diameter filled with 2 µm C18 resin (Thermo

Scientific), and eluted over 120 min at 250 nl/min in a 0 to 40% HPLC buffer A (0.1%

82

formic acid in HPLC water) to buffer B (0.1% formic acid in acetonitrile) gradient with

an EASY nLC 1000 chromatography system operating at 50 °C (Thermo Scientific),

which was connected through a nano-ESI set-up to a Q Exactive or Elite mass

spectrometer (Thermo Scientific). The resolution for MS and MS/MS scans and data

acquisition protocol were as described in Section 2.8 under “Mass Spectrometry

Analysis”.

Peptide Identification and Quantification based on Mass Spectrometry Data

For pY profiling in AML, the MS raw files were searched using the MaxQuant

software (142) (version 1.3.0.5; search engine: Andromeda). The peak list and peptide

identifications were obtained by using default parameters and minimum peptide length 5,

multiplicity 1, maximum charge 5, with carboxyamidomethylation (C+57.02146)

specified as fixed modification and oxidation (M+15.99491 Da), acetylation (protein N-

terminal+42.01056 Da), and phosphorylation (STY+79.96633 Da) as variable

modifications. The peak list was searched against the most recent UniProtKB/Swiss-Prot

human protein FASTA database (2013 September release; 540,958 sequence entries). For

PTP profiling data, carboxyamidomethylation (C+57.02146) and cysteine converting to

cysteic acid (C+47.9982) was used as variable modifications with no fixed modifications;

and the second peptide identification option was enabled in Andromeda. Modifications

on peptides were determined automatically by the software; and peptide/protein MS ion

current intensities as a measure of quantification was attained in MaxQuant using the

default parameters and selecting the “match between runs” and “label-free quantification”

options. The peptide levels were further normalized to the total peptide measurement by

BCA assay (Pierce; by following the manufacturer’s protocol).

83

Generation of Heatmaps Based on Peptide Quantifications

The log 2 MS ion current intensities, z-scores, and Pearson correlation coefficients,

as indicated by the heatmap legends, were calculated in Microsoft Office Excel 2003

(http://www.microsoft.com/en-ca/default.aspx). Unsupervised hierarchical clustering

were conducted by Cluster 3.0 and visualized by Java Treeview (Version 1.1.5r2;

http://jtreeview.sourceforge.net/).

Partial Least Squares Regression (PLSR) Analysis

For descriptions of the PLSR analysis, refer to Section 2.8 under “Partial Least

Squares Regression (PLSR) Analysis”.

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Chapter 4 Determination of the Functional Consequences of

Tyrosine-Phosphorylation of the Lyn SH2 Domain

The work described in this chapter has been published as:

Lily Jin,1,4,* Leanne Wybenga-Groot,2,3,* Jiefei Tong,1 Paul Taylor,1 Mark Minden,5,6

Suzanne Trudel,5,6 C. Jane McGlade,2,3,5 and Michael F. Moran1,4,6 (2015) Tyrosine

phosphorylation of the Lyn SH2 domain modulates its binding affinity and specificity.

Mol Cell Proteomics. 14(3):695-706.

The pY profiles in primary AML and chronic lymphocytic leukemia samples were

generated by Dr. Jiefei Tong1,4,6. The protocol for purification of phosphorylated or

unphosphorylated Lyn SH2 domain was developed with the help of Dr. Jiefei Tong1,4,6

and Dr. Leanne Wybenga-Groot,2,3. All other experiments and computational analyses in

this chapter were performed by Lily Jin.

Programs in 1Molecular Structure and Function and 2Cell Biology, and 3The Arthur and

Sonia Labatt Brain Tumour Research Centre, The Hospital For Sick Children, 686 Bay

Street, Toronto, M5G 0A4, Canada

Departments of 4Molecular Genetics and 5Medical Biophysics, University of Toronto 6Princess Margaret Cancer Center, 610 University Avenue, M5G 2M9, Toronto, Canada

85

4.1 Abstract

SH2 domains bind pY-containing polypeptides and modulate cellular functions by

directing protein-protein interactions. Proteomics analysis conducted in our lab showed

frequent phosphorylation of SFK SH2 domains in blood system cancers such as AML,

chronic lymphocytic leukemia (CLL), and MM. To understand the functional impact of

SH2 domain phosphorylation, I carried out biochemical analysis using the SFK Lyn SH2

domain as a model and found that phosphorylation of the conserved residue Y194 alters

the affinity and specificity of Lyn SH2 domain to pY-containing proteins/peptides.

Analysis of the preferred binding motifs revealed a change in specificity of the SH2

domain for the pY+2/+3 residue of the ligand. These results present another layer of

regulation wherein protein-protein binding through SH2 domains is regulated by

upstream SH2 TKs and PTPs.

4.2 Introduction

SH2 domains are modular functional units of a protein that recognize specific pY-

containing motifs. They are found in various signaling molecules and are important for

signal transduction due to their ability to mediate protein-protein interactions (Section

1.1.1.4). Given the reversible nature of protein tyrosine phosphorylation (3), the

interactions of SH2 domains to pY-containing molecules are inherently dynamic,

comprising key steps through which the signaling networks within a cell are controlled

and regulated. In addition to binding proteins in trans, SH2 domains participate in

intramolecular interactions, with one example being the auto-regulation of SFKs (Section

1.1.1.2). Therefore, SH2 domains regulate signaling enzymes and are indispensible for

86

mediating signal transduction in response to extracellular stimuli. The structure of SH2

domains consists of conserved antiparallel β-sheets and two α-helices, which form

variable binding surfaces that recognize different pY motifs (Section 1.1.1.4.1). For SFKs,

the SH2 domains were found to bind most tightly to sequences containing the pYEEI

motif, in which the hydrophobic pY+3 residue inserts into a hydrophobic pocket bounded

by residues of the EF and BG loops; altering these residues can lead to changes in

substrate selectivity for the SFK SH2 domains (51-53). In addition to binding pY-

containing polypeptides, SH2 domains themselves can be phosphorylated (54-56), which

appeared to be a general mechanism for modulating the binding properties of SH2

domains. Here, I report the frequent phosphorylations of a conserved tyrosine within SFK

SH2 domains in the haematopoietic cancers AML, CLL, and MM, as well as other

cancers. In vitro binding studies using Lyn SH2 domain as a model indicate that this

phosphorylation affects phosphoprotein and phosphopeptide binding to Lyn SH2 domain.

These results suggest that SH2 domain phosphorylation may be a general mechanism for

modulating SFK functions and may constitute an additional layer in the regulation of pY-

mediated signaling.

4.3 A Conserved Tyrosine in SFK SH2 Domains Is Phosphorylated in

Cancer Samples and Cancer-Derived Cell Lines

To identify sites of protein tyrosine phosphorylations, the pY profiles for 12

primary AML (See Chapter 3) and five Revlimid-treated CLL patient samples were

generated. From these data, I observed that Lyn Y194, or the equivalent Hck Y209 and Lck

Y192, were phosphorylated in 11 out of the 12 AML samples (Figure 4.1 A). Moreover,

Lyn Y194, Lck Y192, or their equivalents Fgr Y209 or Blk Y188, were phosphorylated in five

87

CLL samples (Figure 4.1 B). Consistent with these results, published phosphoproteomic

studies reported the phosphorylation of Lyn Y194 or its equivalent SFK residues in non-

small cell lung cancer (NSCLC) cell lines and tumors, breast cancer specimens, and in

the cell lines of chronic myeloid leukemia (175, 254, 255). Together, these results show

that phosphorylation of Y194 in the SH2 domain of Lyn, or its equivalent in SFK family

members, is frequent in cancer and cancer-derived cell lines.

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Figure 4.1. SFK SH2 domain phosphorylation was detected in AML, CLL, MM and

is regulated by phosphatase

A and B, relative MS signal intensities of SFK SH2 domain phosphorylations in the

peripheral blood mononuclear cell samples harvested from 12 newly diagnosed AML (A)

and five Revlimid-treated CLL (B) patients. C, Bar graphs representing the measured Lyn

Y194 phosphorylation stoichiometry in human MM tumor-derived cell lines. The cells

were either harvested without treatment, or after treatment with pervanadate. D, Sequence

alignment of human SFK SH2 domains, with secondary structure elements corresponding

to Lyn kinase indicated on top. The residues are numbered based on Lyn. Lyn Y194 and

residues within the pY or pY+3 binding pockets are marked with a red, orange, or green

box, respectively.

D

89

4.4 SFK SH2 Domain Phosphorylation Is Regulated

To determine if SFK SH2 domain phosphorylation is regulated in cells, I measured

the absolute phosphorylation stoichiometry of Lyn Y194 in four MM cell lines, untreated

or treated with pervanadate, a pan PTP inhibitor. The measurement was performed using

an SRM-based method that I developed previously (139). Particularly, Lyn Y194 was

phosphorylated at 0.7% and 0.4% in untreated KMS18 and LP1 cells, which increased to

4.7% and 0.9% in pervanadate-treated KMS18 and LP1 cells, respectively. Consistently,

Lyn Y194 phosphorylation was not detected in untreated KMS11 and RPMI8226 cells, but

was increased to 4.3% and 2.0% in pervanadate-treated KMS11 and RPMI 8226 cells,

respectively (Figure 4.1 C). The fact that Lyn Y194 phosphorylation was increased in

pervanadate-treated cells suggests that Lyn pY194 is regulated by TK and PTP activities in

vivo.

4.5 Lyn SH2 Domain Phosphorylation Modulates Its Binding to pY

Peptides

To understand the impact of phosphorylation of the Lyn SH2 domain on its binding

to phosphorylated ligands, the binding profiles of the Lyn SH2 domain for pY peptides

was compared to that of phosphorylated Lyn SH2 domain. To this end, I purified

unphosphorylated and phosphorylated Lyn SH2 as shown in Figure 4.2 A. Specifically,

Lyn SH2 was purified from bacteria, phosphorylated in vitro, and subjected to either

IMAC or cation exchange chromatography to resolve phosphorylated and

unphosphorylated proteins. The IMAC eluate was shown to be tyrosyl phosphorylated by

Western blot analysis (Figure 4.2 B). Samples corresponding to the three cation exchange

90

chromatographic peaks were analyzed by SRM and the fractions corresponding to peak 1

was estimated to contain > 95% pY194-Lyn SH2 (Figure 4.2 C). Unphosphorylated Lyn

SH2 was obtained either by omitting the addition of Ephrin A4 (EphA4) kinase during

purification, or by collecting the appropriate chromatographic fractions. Streptavidin (SA)

immobilized phospho- or unphosphorylated Lyn SH2 domain (hereafter referred to as

pSH2 and SH2, respectively) was mixed with a pool of highly phosphorylated peptides

produced from pervanadate-treated Mv4-11 cells, an AML cell line containing the Flt3

ITD mutation, which expresses a constitutively active Flt3 protein that facilitates the

accumulation of pY. Next, bound peptides were eluted into acidic solutions for MS

analysis. To assess the enrichment potential of the SH2 domains, I also generated a

quantitative profile of cellular pY in Mv4-11 cells as background, which serves as a basis

for comparison. Three technical replicates of the pY profiling experiment identified a

total of 504 pY-containing peptides.

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Figure 4.2. Purification of phosphorylated Lyn SH2 domain

A, a flow chart showing the schematic overview of the steps involved in purifying

phospho-Lyn SH2. B, Western blots analysis of IMAC-based enrichment of phospho-

SH2. FT indicates flow-through. C, the UV 280 nm chromatography showing the

separation of phospho- and unphospho-Lyn SH2 by cation exchange column (top); and

the SRM ion currents associated with Y194- or pY194-containing peptide in 3

chromatographic peaks (bottom). D, Western blot of purified phospho- (pSH2) and

unphospho-Lyn SH2 (SH2) demonstrating the SH2 and pSH2 aliquots contain

comparable amounts of proteins.

A B D

mAu

500

400

300

200

100

0

C

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A collection of 66 pY peptides, encompassing 69 pY sites, were identified to bind

to either SH2 or pSH2. Among these, 18 singly phosphorylated peptides bound to both

SH2 and pSH2, while the remaining 48 peptides, encompassing 51 pY sites, bound to

SH2 only (Figure 4.3 A; Table 4.1). A total of 27 SH2/pSH2-binding pY sites were not

identified by the anti-pY immunoprecipitation (IP) approach that generated the total

cellular pY profile in Mv4-11 cells. Sequence logos were generated (WebLogo (256),

http://weblogo.berkeley.edu/logo.cgi) for the 69 SH2-binding and 18 pSH2-binding pY

sites, as well as the cellular collection of 531 (i.e. 504+27) pY sites identified in Mv4-11

cells (Figure 4.3 B). The sequence logos for the SH2 or pSH2 bound pY sites

demonstrate an enrichment of the canonical SFK SH2-binding motif with the sequence

pYEE[V/I/L] (47, 49, 51), while the sequence logo for the cellular pY did not show any

distinct motif. To further understand the selectivity of SH2/pSH2 domains, I calculated

the fold-enrichment of specific motifs surrounding the SH2- or pSH2-bound pY sites by

comparing to the total pY background in Mv4-11 cells, using the motif-x online statistical

software (257). This analysis showed that the SH2-bound motifs pYExI and pYExV were

enriched 28-fold and 14-fold respectively, and the pSH2-bound motif pYE was enriched

four-fold (p-values < 0.001). These data demonstrate that, while both SH2 and pSH2

were able to select for defined binding motifs, the preference of pSH2 for pYE, but not

pYExI or pYExV, shows that the specificity of the SH2 domain towards the pY+3

residue is diminished by SH2 domain phosphorylation. On the other hand, these data

suggest that SH2 phosphorylation does not influence the specificity at the pY-binding

pocket for the pY+1 residue.

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Table 4.1. Phosphopeptides bound to Lyn SH2 or pSH2 identified by AP-MS

94

To examine the impact of Lyn SH2 phosphorylation on binding selectivity, the

relative amounts of the 18 pY peptides bound to both SH2 and pSH2 were extracted by

MaxQuant software (142) based on their MS XIC signal intensities. The average

quantification values across three replicates were used to generate a binding heatmap

(Figure 4.3 C), which showed increased bindings for SH2 compared to pSH2 (3 to 779-

fold increase) for all 18 pY peptides. This data indicates that these pY peptides have

preferences for unphosphorylated Lyn SH2. Moreover, it suggests that phosphorylation

of the SH2 domain reduces its affinity for pY peptides.

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Figure 4.3. Lyn pSH2 shows reduced affinity for pY peptides compared to SH2

A, a Venn diagram of pY sites affinity-bound to Lyn SH2, pSH2, or enriched by anti-pY

IP from Mv4-11 whole cell lysate derived peptides. B, sequence logos based on the 69

SH2-binding (top) and the 18 pSH2-binding (middle) pY sites, and the collection of 531

pY sites identified in Mv4-11 cells (bottom). C, a heatmap based on the quantitative

profiles of the pY sites bound to SH2 and pSH2, ordered top to bottom by descending

fold-changes, labelled on the right by the gene name, pY site, surrounding sequences, and

fold-change. D, bar graphs showing dissociation constants (Kd) of pY peptides binding to

Lyn SH2 or pSH2. **p < 0.01.

A

B

C

D SH2

pSH2

Cellular pY

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To further assess the effect of SH2 phosphorylation, the dissociation constants (Kd)

of isolated Lyn SH2 and pSH2 for four pY-containing peptides were determined in a set

of in vitro fluorescence polarization binding assays. Two of the peptides, pYEEI and

pYEEL, contain the canonical pYEE[V/I/L] SH2-binding motif. The other two, although

do not contain the preferred motif, were derived from proteins functionally linked to Lyn

SH2 domain. These include peptides modeled after the Lyn autoinhibitory C-terminal tail

(pYQQQ) (20) and the Fc gamma receptor IIb (FcγRIIb) immunoreceptor tyrosine-based

inhibition motif (pYSLL) (258). The Kd values of isolated Lyn SH2 domain for the

pYEEI and pYEEL peptides were determined to be 0.75 (±0.2) µM and 0.94 (±0.2) µM,

respectively. This value is consistent with the 0.58 µM Kd value reported for binding a

pYEEI motif-containing peptide to Lyn SH2 (259), and the 0.3-0.6 µM Kd values

reported for binding high-affinity peptides to other SFK SH2 domains (260). As expected,

the affinity of Lyn SH2 for pYQQQ and pYSLL appeared significantly lower, with Kd

measuring 4.9 (±0.6) µM and 3 (±0.9) µM, respectively (Figure 4.4). This is consistent

with the 4 µM Kd value reported for Lck SH2 binding to a low affinity peptide

containing the pYQPG motif (260). Interestingly, the Kd values measured for all four

peptides generally decreased for pSH2 compared to SH2, with the affinity of pYEEI and

pYEEL decreasing to 1.9 ±0.2 and 2.8 ±0.5 fold less, respectively, and the affinity of

pYQQQ and pYSLL decreasing to 1.5 ±0.1 and 2.1 ±0.3 fold less, respectively (Figure

4.3 D). Significantly, all four peptides were found to have lower affinities for pSH2 than

SH2, regardless of whether they had relatively high or low affinities in binding to SH2.

These results also demonstrate that phosphorylation of the Lyn SH2 domain reduces its

affinity for binding pY-containing peptides.

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Figure 4.4. Binding curves of Lyn SH2/pSH2 with phospho-peptide probes

Representative curve from five replicates is shown with Kd for SH2 and pSH2 indicated.

Trendline was plotted automatically in the software Prism 4 (GraphPad Software:

http://www.graphpad.com/scientific-software/prism/). The average and standard

deviation of Kd across five replicates are given in Section 4.5 and shown in Figure 4.3 D.

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4.6 Lyn SH2 Domain Phosphorylation Modulates Its Binding to pY-

Containing Proteins

To see if phosphorylation impacts Lyn SH2 binding to phosphoproteins, the binding

profiles of the Lyn SH2 domain and the phosphorylated Lyn SH2 domain for pY-

containing proteins was compared. Pervanadate-treated Mv4-11 whole cell lysates were

incubated with immobilized Lyn SH2 or pSH2 to affinity-purify pY-containing proteins.

The bound proteins were either analyzed by anti-pY Western or protease-digested for MS

analysis. Remarkably, Western blot analysis showed dramatic reduction in

phosphoprotein binding for pSH2 compared to SH2 (Figure 4.5 A; compare lanes 4 and

5). Moreover, the quantitative profiles generated by MS analysis identified 539 proteins

that were significantly enriched through affinity-binding to Lyn SH2 or pSH2, compared

to the streptavidin (SA)-only negative control; among which, 36 known Lyn interactors

(GeneCards (261), www.genecards.org) were included. The MS analysis also detected

166 pY sites on these proteins. The fact that a lower number of pY sites were identified

compared to the number of bound proteins implies the affinity-enrichment of protein

complexes, such that indirect SH2-binders were also recovered by this method.

Consistent with the peptide binding experiments described in Section 4.5, fewer proteins

bound pSH2 compared to SH2 (Figure 4.5 B), suggesting that the ability of Lyn SH2 to

bind native proteins was decreased by phosphorylation at Y194. This is consistent with

previous findings that phosphorylation of the equivalent tyrosine in the SH2 domain of

Lck reduced its ability to bind proteins derived from pervanadate-treated Jurkat T cells

(54).

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Out of the 539 bound proteins, 394 bound selectively better (≥ two-fold) to either

SH2 or pSH2, exhibiting binding preferences (Appendix Table 5). Among which, 352

bound two-fold or better to SH2 and the other 42 bound two-fold or better to pSH2. I

used a hidden Markov model method (262) to predict direct binders of Lyn SH2 based on

their theoretical pY motifs. The database for theoretical pY motifs include the entire

collection of pY sites on the 394 differential proteins identified in this experiment and

catalogued in the PhosphoSitePlus online database (263) (www.phosphosite.org/),

amounting to a total of 1988 pY sites. As a result of this analysis, 66 of the 394 proteins

were predicted to bind directly to Lyn SH2, with 62 bind preferentially to SH2 and four

bind preferentially to pSH2. These 66 proteins were significantly enriched for proteins in

immune system process (g:Profiler (264) p value<0.001), including pathways in cellular

response to stimulus (42 proteins, p<0.01), signaling (41 proteins, p<0.001), and

regulation of immune system process (17 proteins, p<0.01). These data are consistent

with the prominent role of Lyn in B cell signaling (25). Among the predicted direct

binders, 16 were known Lyn interactors (Figure 4.5 C). This is a 15.8-fold enrichment (p

value<0.001) of Lyn interactors compared to a similar search against the complement of

catalogued human protein pY (PhosphoSitePlus, March 2015 download; 10240 pY

proteins) background. Comparison of the proteins and phosphopeptides captured by the

affinity purification method revealed 27 instances of overlap (20 predicted direct binders

including five know Lyn interactors), wherein a phosphopeptide and its parent native

protein were both enriched by binding SH2 or pSH2 (Table 4.2). These data suggest that

the 66 predicted interactors possibly interact with Lyn in vivo, likely through pY-

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mediated binding to Lyn SH2 domain. However, these predictions still require

experimental validation.

Conceptually, proteins containing the pY moiety-binding SH2 or PTB domains

might bind pY194 of the pSH2 domain, thus demonstrating a preferred selectivity toward

pSH2 versus SH2. However, results of this experiment indicate that all SH2/PTB

domain-containing phosphoproteins bound Lyn SH2 at least 1.7-fold better than pSH2

(Table 4.3), implying that the major mode of interaction is mediated through the pY

motifs on the phosphoproteins and the Lyn SH2 domain, and that this interaction can be

disrupted by phosphorylation of Lyn SH2.

101

A B

C

Fold change Prefer SH2 Prefer pSH2

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Figure 4.5. Lyn SH2 phosphorylation modulates its binding affinity for

phosphoproteins

A, an anti-pY Western blot showing differential binding of phosphoproteins to Lyn SH2

or pSH2. Untreated (Lane 1) or pervanadate-treated (Lane 2) Mv4-11 cells were lysed

and the whole cell lysate proteins were mixed with empty streptavidin (SA) beads (Lanes

3, 6), Lyn SH2 (Lanes 4, 7), or pSH2 (Lanes 5, 8) for affinity purification. The flow-

through (Lanes 6-8) and the bound proteins (Lanes 3-5) were indicated. Streptavidin blot

for biotin-labelled SH2 and pSH2 confirms equal loading of the proteins. B, a volcano

plot of log 10 Student’s t-test p-value (based on 6 replicates) against log 2 fold change of

abundances of protein bound to SH2 compared to pSH2. Horizontal line indicates

statistical significance cut-off. C, a schematic overview of proteins bound differentially

(2-fold or higher) to Lyn SH2 (blue) or pSH2 (green), with the darkness of color

indicating fold changes. Predicted direct Lyn-binders are in diamond-shaped nodes and

connected to Lyn SH2 by a line. Reported Lyn interactors are labelled in red. Asterisks

indicate the Student’s t-test significance levels: *p<0.05; **p<0.01; ***p<0.001.

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Table 4.2. SH2/pSH2-binding phosphoproteins identified by peptide AP

The expression “(ph)” denotes phosphorylation of the preceding residue.

Table 4.3. Fold change of SH2 or PTB domain-containing proteins bound to Lyn

SH2 and pSH2

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4.7 Discussion and Conclusion

Through proteomics approaches, I discovered that a conserved tyrosine in the SH2

domain of Lyn and other SFKs was prevalently phosphorylated in AML/CLL primary

samples and MM cell lines. Phosphorylation of the equivalent tyrosine on SFKs was

observed in other cancer systems such as non-small cell lung cancer cell lines and tumors

(175) and human epidermal growth factor receptor 2 (HER2)-overexpressing breast

tumor specimens (254), suggesting potential important roles for this phosphorylation. For

this reason, I investigated the impact of pY on the binding behaviour of SH2 domain

using Lyn SH2 domain as a model. As a result, I found that Y194 phosphorylation within

the Lyn SH2 domain reduced its binding affinity and modulated its selectivity for

phosphopeptides and phosphoproteins.

I observed increased Lyn SH2 (Y194) phosphorylation in MM cells treated with

pervanadate, a phosphatase inhibitor, indicating that Lyn pY194 was regulated.

Consistently, other groups also observed the regulation of SH2 phosphorylation in SFKs;

and this was usually associated with functional consequences. In particular, induction of

Src phospho-Y213 was observed in vivo following platelet derived growth factor (PDGF)

or HER2/heregulin (HRG) stimulation (21, 254). While phosphorylation of Src Y213 by

PDGFR in vitro potentially abolished the binding of Src C-terminal autoinhibitory motif

and led to Src activation (21), HER2/HRG stimulated Src Y213 phosphorylation promoted

Src kinase activity as well as Fak Y861 phosphorylation (254). Moreover, pY213 in Src was

found to affect its localization, building a link between Y213 phosphorylation and breast

cancer metastasis (254). Additionally, stimulation of Jurkat T cells with anti-CD3

antibodies induced phosphorylation of Lck Y192 (265). Together, these observations with

105

my results propose a model where SFK SH2 phosphorylation influences substrate

selection, protein localization, and allosteric interactions with the kinase domain or the C-

terminal tail. In agreement with this, my results show altered affinity and selectivity of

Lyn SH2 for pY-containing molecules due to SH2 phosphorylation, suggesting a role of

SH2 phosphorylation in regulating the protein-protein interaction and downstream

signalling of SFKs.

Lyn Y194 is located on the EF loop, within the consensus sequence

G[G/W][Y/F/L]YI[S/T][P/T/S]R, which is conserved in SFK SH2 domains, but not in all

SH2 domains (40). The EF loop controls the accessibility and shape of the pY+3 pocket

(51), thus, to a modest degree, regulates substrate specificity (42). Therefore, it is

reasonable to speculate that Y194 phosphorylation modulates substrate recognition for the

pY+3 residue. Indeed, my results showed that phosphorylated Lyn SH2 had a preference

for pYE but not pYExI or pYExV motif, suggesting that phospho-Y194 abolished the

selectivity for pY+3 residue binding. The fact that phosphorylation only reduced the

affinity of Lyn SH2 binding to synthetic pY peptide by 1.5-2.8 fold may reflect that pY

contributes most energy to binding, and the C-terminal flanking residues of pY (the pY+

sites) contribute less. Combined, these data suggest that Lyn Y194 phosphorylation within

the EF loop modulates substrate selectivity for the pY+3 residue while modestly reducing

the binding affinity of pY-containing ligands.

Although my data showed a generally reduced binding of pSH2 to pY-containing

molecules, for a small subset of protein ligands, the binding was increased. This subset of

42 proteins includes significantly enriched biomolecules that are involved in degenerative

joint disease (F9, COMP), prolonged partial thromboplastin time (F10, F9, DPM1),

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transport of gamma-carboxylated protein precursors from the endoplasmic reticulum to

the Golgi apparatus (F10, F9), and SMRT core complex (HDAC3, NCOR2) (g:Profiler p

value<0.05) (264). Among these, 4 of the 42 proteins (HDAC3, ZYX, GPX3, THBS1)

are products of known tumor suppressor genes (266-271). Particularly, ZYX was

predicted to interact directly with Lyn SH2 by my algorithm. The over-expression of

ZYX in Ewing tumor derived samples led to transformation events (269) potentially by

disrupting the actin polymerization process. Although a regulated interaction between

Lyn SH2 and ZYX has never been reported, my results provide a potential link between

Lyn and actin polymerization.

While my results showed increased affinity of Lyn SH2 for both high- and low-

affinity pY-peptides, phosphorylation of Src SH2 domain significantly reduced binding to

a low-affinity peptide (derived from the phosphorylated autoinhibitory C-terminal tail of

Src) without influencing binding to a high-affinity peptide (21). Furthermore,

phosphorylation of Lck SH2 reduced binding to a high-affinity peptide but without

influencing binding to a lower-affinity peptide (54). These conflicting observations

reflect that ligand-binding may be differentially modulated by SH2 phosphorylation for

SFKs, and this may serve as mechanism to control SFK substrate selection and regulate

the diverse roles of SFKs in various signaling events. Alternatively, these conflicting

results may simply be due to differences in material and methods in assessing SH2

domain-phosphopeptide interactions.

In conclusion, the modulation of Lyn SH2 binding specificities by phosphorylation

presents another layer of the complex regulation of pY signaling networks. This

mechanism is regulated by upstream TKs and PTPs, and may be a common mode of

107

modulation for SH2-containing proteins, including SFKs, to control their substrate

binding selectivity. Given the widespread nature of SH2-containing proteins and their

critical roles in signal transduction, this discovery may provide new insights into

understanding SH2-mediated signaling pathways.

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4.8 Materials and Methods

Materials

For Western blotting, anti-phosphotyrosine antibody, clone 4G10 was from Merck

Millipore. Fluor-S MultiImager for imaging and Laemmli Sample Buffer (2 x) were

ordered from Bio-Rad Laboratories. For Lyn IP, agarose conjugated anti-Lyn mouse

monoclonal antibody was obtained from Santa Cruz Biotechnology. For GST fusion

protein purification, glutathione sepharose 4B beads were from Amersham Biosciences -

GE Healthcare Life Sciences (Piscataway, NJ). For affinity purification (AP),

Streptavidin (SA) Sepharose beads conjugate was ordered from Cell Signaling

Technology and Protein A agarose Fast Flow 50% (v/v) beads were from Sigma Aldrich

(St. Louis, MO). EZ-Link Sulfo-NHS-Biotin and Biotinylation Kits was from Pierce

Thermo Scientific (Rockford, IL). Thrombin and RPMI-1640 medium were ordered from

Life Technologies. PerfectPure C-18 Tip pipette tips (ZipTip) for mini-scale peptide

desalting were bought from Eppendorf AG (Hamburg, Germany). N-terminally Alexa

Fluor 488-labeled peptides with sequences CGGGGpYEEIA (pYEEI),

THDCGpYEELLT (pYEEL; corresponds to the MS4A6A pY242 motif),

CATEGQpYQQQP (pYQQQ; corresponds to the Lyn pY508 motif), and

CENTITpYSLLM (pYSLL; corresponds to the FcγRIIb pY292 motif), where pY

represents phosphorylated tyrosine, were synthesized in SPARC BioCentre (The Hospital

for Sick Children, Toronto, ON). Protein purification was performed with a HiLoad 26/60

Superdex 75 gel filtration column using the AKTA Fast Protein Liquid Chromatography

109

(FPLC) system manufactured by Amersham Biosciences. Sources of all other materials

were as specified in Section 2.8 under “Materials”.

Patient Selection and Sample Preparation

Treatment naive symptomatic CLL patients were given escalating doses of

Revlimid: 2.5 mg daily for 21 days in Cycle 1, and after a 7-day drug-free period, 5 mg

daily for 21 days in Cycle 2. Peripheral blood mononuclear cells (PBMCs) were collected

from patients on Day 8 of Cycle 2, 4 h after taking medication. CLL patient selection and

PBMC sample collection were described previously (272). For AML samples, see

Section 3.6 under “Patient Selection and Sample Preparation”.

Cell line

The Mv4-11 AML cell line were maintained in RPMI-1640 medium supplemented

with 5% FBS.

Strains

For gene expression, Escherichia coli BL21 (DE3) cells were grown in Lysogeny

broth (LB) medium (37 °C). Ampicillin (100 mg/mL) was supplemented for plasmid-

harbouring strains.

Constructs

Residues corresponding to the SH2 domain (124 to 231) of mouse Lyn kinase were

cloned into a pGEX expression vector by Leanne Wybenga-Groot (The Arthur and Sonia

Labatt Brain Tumour Research Centre, The Hospital For Sick Children). The GST-

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EphA4 kinase construct containing residues 591-896 of the human EphA4 kinase was a

gift from Leanne Wybenga-Groot.

Treatment of Cultured Cells with Pervanadate

Equal volumes of 12 mM sodium vanadate (diluted from 100 mM stock, Cell

Signaling) and 12 mM H2O2 (diluted from 30% w/w stock, Sigma-Aldrich) were mixed

and incubated (rt, 15 min) to obtain 6 mM peroxovanadate solution. The solution was

immediately diluted 1:100 into sub-confluent cultures of MM or AML cells. The cells

were maintained in 0.06 mM peroxovanadate (37 °C, 10 min), then pelleted and

subjected to cell lysis.

Non-Denaturing Cell Lysis

To obtain non-denatured whole cell lysates, cultured AML cells were pelletted and

lysed in NP-40 cell lysis buffer as described in Section 2.8 under “Non-Denaturing Cell

and Tissue Lysis”.

Denaturing Cell Lysis

For AML/CLL primary samples, pelleted cells were sonicated in urea lysis buffer

(20 mM HEPES pH 8, 9 M urea, 1 mM Na3VO4, 2.5 mM sodium pyrophosphate, 1 mM

β-glycerophosphate) and inverted at 4°C for 30 min, then subjected to anti-pY

enrichment (see Section 2.8 Enrichment of Peptides by pY Antibody). To obtain lysate-

derived phosphopeptides, pervanadate-treated Mv4-11 cells were lysed by rocking (4 °C,

30 min) in urea-CHAPS lysis buffer (7 M urea, 4% CHAPS w/v in 50 mM Tris pH 7.5).

The non-soluble material was pelleted by centrifugation (15,000 x g, 10 min) and the

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cleared supernatant was subjected to acetone precipitation as described below, trypsin

digestion (see Section 2.8 Protein Digestion by Trypsin), and peptide desalting (see

Section 2.8 Peptide Desalting) prior to usage in AP experiments.

Acetone Precipitation and Resuspension of Proteins

Proteins dissolved in urea-CHAPS lysis buffer were mixed with 4 x volume of cold

acetone (-20 °C, overnight) pelleted by centrifugation (18,000 x g, 10 min). The protein

pellet was exposed to air (rt, 30 min) to remove the acetone and then dissolved in 1 M

urea, 50 mM ammonium bicarbonate.

Immunoprecipitation (IP) of Lyn Kinase

For anti-Lyn IP, whole cell lysate proteins in NP-40 cell lysis buffer were pre-

cleared with protein A agarose beads (5 µl per mg protein; 4°C, 2 h with inversion), and

incubated with agarose conjugated anti-Lyn antibody (2 µg per mg protein; 4 °C, 4 h with

inversion). The beads were washed three times in NP-40 cell lysis buffer, then twice in

PBS. Proteins were trypsin-digested on beads (Section 2.8 Protein Digestion by Trypsin)

and desalted with a C-18 ZipTip by following the manufacturer’s protocol. The desalted

peptides were subjected to SRM MS analysis.

Measurement of Phosphorylation Stoichiometry by SRM MS

Lyn kinase-derived tryptic peptides were monitored by SRM MS using previously

defined transitions (139). The peak areas of the XICs corresponding to the SRM signals

of Lyn Y194 or pY194-containing peptides were used to calculate the absolute

phosphorylation stoichiometry as described previously (139).

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Transformation of Protein Constructs into Bacteria

Plasmid DNAs harbouring the Lyn SH2 domain or EphA4 kinase sequences (0.1-

0.3 µg) were incubated with 100 µL competent BL21 cells on ice (30 min). The bacteria

were heat-shocked (42 °C, 45 s), incubated on ice (2 min), then mixed with 500 µL S.O.C.

medium (Life Technologies) and shaken at approximately 200 rpm (37 °C, 1 h). The

bacteria-containing medium was plated onto a LB plate supplemented with 100 mg/mL

ampicillin and incubated overnight (37 °C). Plasmid-harbouring colonies were selected

from the plate and verified by miniprep (PureLink Quick Plasmid Miniprep Kit, Life

Technologies; per manufacturer’s protocol) and sequencing.

Expression and Purification of Lyn SH2 and Phosphorylated Lyn SH2

Escherichia coli BL-21 cells containing the Lyn SH2 or EphA4 constructs were

grown in two to eight litres of LB media containing 100 µg/ml ampicillin (18 °C,

overnight; A600 = 0.6-0.8 and 0.25 mM IPTG induction). Cells were pelleted and

resuspended in lysis buffer (50 mM HEPES pH 7.5, 0.5 M NaCl, 10% glycerol, with 1.5

µM aprotinin, 20 µM leupeptin, and 0.4 mM AEBSF), followed by sonication on ice.

The cell lysate was cleared by centrifugation (10,000 x g, 30 min) and the supernatant

was mixed by nutation with glutathione-sepharose (0.5-1 ml resin per litre bacterial

culture; 4 °C, 1.5 h). Resin was washed 5 x with 20 ml wash buffer (50 mM HEPES pH

7.5, 0.5 M NaCl, 5% glycerol). For use in affinity purification (AP), resin-bound GST-

Lyn SH2 was biotinylated using the EZ-Link Sulfo-NHS-LC-Biotin kit (rt, 2 min). The

reaction was stopped by washing with TBS, pH 8. The GST tag was cleaved by thrombin

(50-100 U per litre bacterial culture; rt, overnight) in the presence of 10 mM CaCl2. Lyn

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SH2 was eluted with 5-10 ml wash buffer. In vitro phosphorylation was carried out by

mixing with glutathione-sepharose-bound GST-EphA4 in kinase reaction buffer (25 mM

MOPS pH 7.2, 12.5 mM β-glycerophosphate, 20 mM MgCl2, 25 mM MnCl2, 5 mM

EGTA, 2 mM EDTA, 0.5 mM Na3VO4, 0.5 mM DTT, 2 mM ATP) at 20:1 protein to

kinase molar ratio (rt, overnight). Lyn SH2 was dissolved in GF buffer (25 mM HEPES

pH 7.5, 0.4 M NaCl, 1 mM DTT) and isolated using a HiLoad 26/60 Superdex 75 gel

filtration column (GE Healthcare Life Sciences). Unphospho- and phospho-Lyn SH2

were resolved either by immobilized metal affinity chromatography (IMAC)

(Phosphoprotein Enrichment Kit, CloneTech) by following the manufacturer’s

instructions, or on a mono S column (GE Healthcare) with a 0-20% gradient of Buffer A

(20 mM MOPS pH 6.5, 1 mM DTT) to Buffer B (20 mM MOPS pH 6.5, 1 M NaCl, 1

mM DTT).

Affinity Purification of Phosphorylated Peptides

A total of 3 mg Mv4-11 cell lysate-derived peptides (refer to Denaturing Cell Lysis)

were mixed with equal amounts of SA-bound Lyn SH2 or pSH2, in HEPES binding

buffer (25 mM HEPES pH 7.2, 12.5 mM β-glycerophosphate, 0.5 mM DTT; 4 h, 4 °C).

The beads were washed three times in the binding buffer and twice in 25 mM HEPES, pH

7.2; and eluted with 5 mM phenylphosphate in 0.15% TFA. The eluted peptides were

desalted using a C18 ziptip as per manufacturer’s protocols, and analyzed by the Orbitrap

Elite Hybrid Ion Trap-Orbitrap mass spectrometer (for specifications of the data

acquisition procedures see Section 3.6 Mass Spectrometry Analysis). This experiment

was repeated three times and the peptide quantification values were averaged across three

replicates. By manually excluding three phosphopeptides that constantly bound SA

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negative control at high levels, 66 Lyn SH2/pSH2-binding phosphopeptides were

reported.

Affinity Purification of Phosphorylated Proteins

A total of 6 mg Mv4-11 lysate proteins (see Non-Denaturing Cell Lysis) were

mixed with equal amounts of SA-bound Lyn SH2 or pSH2 in NP-40 lysis buffer (4 °C, 4

h). The beads were washed three times in NP-40 lysis buffer and twice in 20 mM HEPES,

pH 7.2. Bound proteins were reduced, alkylated, and trypsin-digested on beads, then

eluted from the resin into 50 µl 0.15% TFA (for the trypsin digestion protocol, see

Section 2.8 Protein Digestion by Trypsin). The eluted peptides were desalted with a C18

ziptip, and analyzed by the Q Exactive Hybrid Quadrupole-Orbitrap mass spectrometer

(for specifications of the data acquisition protocol see Section 3.6 Mass Spectrometry

Analysis). Two biological repeats, each with three technical replicates, were conducted

and the protein levels were averaged across six replicates. The SH2- or pSH2-binding

proteins were defined as proteins significantly enriched in the SH2/pSH2-bound fractions,

whose levels elevated by at least 2.5 standard deviations compared to SA negative

controls (p-value < 0.0124).

SRM MS Analysis

Desalted peptides were loaded onto a homemade C-18 analytical column for

chromatographic separation using a 0 to 60% HPLC buffer A (0.1% formic acid in HPLC

water) to buffer B (0.1% formic acid in acetonitrile) gradient over 40 min (400 nL/min),

and sprayed into a TSQ Quantum Ultra triple quadrupole mass spectrometer (Thermo

Scientific) through positive-ion nano-ESI. Transitions were monitored with resolutions

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for Q1 and Q3 set to 0.4 Da and 0.7 Da at full width at half maximum (FWHM),

respectively. The collision energy used to fragment the peptides was calculated with the

formula 3.41 + 0.034 x m/z, which was deduced empirically for optimal fragmentation

(139).

Fluorescence Polarization Binding Assay

Alexa Fluor 488-labeled synthetic peptides with sequences CGGGGpYEEIA

(pYEEI), THDCGpYEELLT (pYEEL), CATEGQpYQQQP (pYQQQ), or

CENTITpYSLLM (pYSLL), where pY denotes phosphorylated tyrosine, were dissolved

in FP binding buffer (25 mM HEPES pH 7.2, 150 mM NaCl, 0.5 mM DTT) to a

concentration of 10 µM and stored at -80 °C in dark. The peptides were mixed with serial

dilutions of Lyn SH2 or pSH2 in FP binding buffer to a final concentration of 1 µM. The

fluorescence polarization (FP) was measured in a flourometer (Analyst HT, Molecular

Devices). A binding curve was plotted by Prism 4 software (GraphPad Software) and the

dissociation constant (Kd) was calculated in the software by using curve-fitting and the

one-site-binding hypothesis. This experiment was repeated five times and the average Kd

for each peptide was reported.

Prediction of Direct Binders of Lyn SH2

The HHsuite software was used to implement a profile hidden Markov model

method (262). First, a matrix predictor model was generated based on the 69 Lyn

SH2/pSH2-bound pY sites. This model was used to search against a custom database of

1988 potential pY motifs on the 398 proteins that differentially bound to

unphosphorylated and phosphorylated Lyn SH2. The custom database was created by

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joining the pY motifs on the 398 protein that was identified in my study with the

catalogued pY motifs from PhosphoSitePlus (263). The algorithm was performed with

default parameters and the following commands:

ffindex_build -s -f hhm.filelist databases/phosphosite_hhm_db

hhmake -i querySH2all.a3m

hhsearch -i data/ querySH2all.hhm -d databases/phosphosite_hhm_db -o

queryresults.txt -norealign -nopred –nodssp

Generation of Heatmaps Based on Peptide Quantifications

The log 2 MS intensities of the 18 phosphopeptides bound to both Lyn SH2 and

pSH2 were used to produce a heatmap. The peptides were arranged in descending order

based on their fold changes by comparing the quantities bound on SH2 to pSH2. The

heatmap was created in Cluster 3.0 and visualized by Java Treeview.

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Chapter 5 Summary and Future Directions

The proteomics and biochemical studies described in this thesis attempt to answer

two generic questions: 1) how the enzymes TKs and PTPs regulate cellular protein pY on

the systemic level; and 2) how the SH2 domain of SFKs, as a downstream effector of pY

signaling in a cell, are functionally modulated by pY. Although the regulation of protein

pY sites by TKs and PTPs is historically appreciated (3, 11, 32), a systemic overview at

the impact of the total cellular collections of the expressed kinome and PTPome on the

cellular pY has not been possible until recently. This type of study was facilitated by the

emergence of new proteomics techniques that enabled the quantitative analysis of

comprehensive profiles of pY and PTPs in a cellular system (151, 273). Through

integrated analysis of the PTPs and cellular pY, I was able to gain insights into the

enzymatic regulation of pY and find evidence that supported my model of a systemic

regulation of pY by the complement of enzymes TKs and PTPs in the system (Figure 1.1).

Moreover, pY sites identified in the proteomics studies led to novel hypotheses and the

probing into the functional implications of the phosphorylation of a conserved Y site in

the SH2 domain of SFKs.

5.1 Summary and Future Directions of the Comprehensive Protein-pY

Regulation Analysis in MM Samples

To answer the first question I proposed in my thesis, I examined the quantitative pY

and PTP profiles in two disease models, MM and AML. For MM, five established human

primary tumor-derived cell lines, representing different MM subtypes, and their cognate

mice xenograft tumors were analyzed. Initial Western results showed distinctive features

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across the cell lines as well as between cultured cells and their cognate tumors. The

tumor-cell difference was further confirmed by unsupervised hierarchical clustering

based on the quantitative pY profile in these samples, which led to the consideration of

cells and tumors as separate biological systems in subsequent analyses. Using the

collection of TK A-loop phosphorylations included in the pY profile as a representation

of activated TKs in the system, I showed that the levels of TK activation alone could

generally distinguish the cells from the tumors (with the exceptions of KMS12 tumor and

RPMI8226 cell), suggesting a systemic regulation of cellular pY by TKs. PLSR analysis

confirmed this notion by showing that almost 100% of pY variation could be predicted

based on the fluctuation in TK activation levels in both cell and tumor systems, while

implicating FGFR3, Ptk2, and Src (or Yes, Fyn, Lck) in cells, as well as Src (or Yes, Fyn,

Lck), Abl1, and FGFR3 in tumors as potential key regulators of pY signaling. Next, the

quantitative PTP expression profiles in these samples were examined. By using a similar

bioinformatics approach, I showed that the variations in PTP expression could almost

completely predict the pY variations in both cells and tumors, with Ptpn1, Ptpn6, and

Ptpn11 in cultured cells, and Ptpn7, Ptpn9, Ptpn11, and Ptprg in xenograft tumors

implicated as potential key PTP regulators of pY. Correlation heatmaps provided

additional evidence for a systemic influence of TKs/PTPs on cellular pY by showing

modular-based strong positive correlations between the TK and PTP enzymes and subsets

of pY. Together, these results support the initial hypothesis that the cellular protein pY is

a quantitative output of the actions of TKs and PTPs in the cellular system.

Future investigations may entail mechanistic elucidation of the functions of the

implicated TKs and PTPs in MM. Indeed, some of the highly implicated enzymes were

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already well-characterized in MM such as FGFR3 (Section 1.1.3.1). However, the vast

majority of the enzymes implicated by this study were either previously not linked to

MM or with functional implications still unclear in MM biology. Some of these enzymes,

such as Ptpn11, although were highly implicated in other types of malignancies, were not

well characterized in MM. Given their prominent oncogenic (i.e. Ptpn11, Abl1) or tumor

suppressor (i.e. Ptpn6) roles, and the fact that they were suggested as potential key

regulators of pY in MM by this study, the role of these enzymes in MM are worth

investigating. Particularly, TKs and/or PTPs implicated by correlating with different

components in the multi-component model generated by PLSR analysis could be

investigated for their potential role in varying subtypes of MM. These enzymes may

mediate key oncogenic mechanisms in MM subtypes wherein an oncogenic driver is yet

unknown. Along this line, my study also identified candidate proteins that may be

functionally linked to the implicated enzymes (i.e. proteins whose pY sites are highly

correlated with the implicated enzymes in the samples; refer to Figure 2.6 and Table 2.3).

Probing at a link between these proteins and the enzymes may be a good starting point for

a functional study. Finally, these investigations may stem the discovery of novel pivotal

pathways that can be intercepted by therapeutic intervention.

Furthermore, the difference between MM tumor and cell biology can be explored in

more detail in order to identify molecular targets that may disrupt xenograft tumor

formation. In particular, the proteins associated with the pY sites whose levels were

significantly altered between cells and tumors (Figure 2.3 B) may be targets with

antitumor or protumor activities. Moreover, Abl1 was implicated by PLSR analysis

(correlated best with Component 2, Figure 2.4 B) in tumors and it would be interesting to

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see what role it plays in MM tumor biology. Because the tumor microenvironment gives

rise to enhanced proliferation, survival, and drug resistance in myeloma cells,

understanding the tumor biology may help to develop better drugs that can alleviate

symptoms of MM and eventually lead to a cure.

Alternatively, some interesting points raised by this study could also be followed up

in future investigations. Since published reports and my data indicate the presence of

more than one independent axis of pY signaling in MM, it would be interesting to see if

other pY-mediated functional modules (besides the ones already reported) can be found

in MM. To this end, the highly co-varied enzymes and pY sites, highlighted by the

“hotspots” in the correlation heatmap (Figure 2.6), could be examined in knock-down or

over-expression studies to decipher their functional relationship and map out the

associated regulatory pathways. Additionally, machine learning could be applied to train

models using the known data which may be used to predict cellular pY levels based on

the enzymatic states of the collection of TKs and PTPs in novel samples. It would be

truly astonishing if cellular pY profile can be predicted solely based on TK and PTP

states in a system.

5.2 Summary and Future Directions of the Comprehensive Protein-pY

Regulation Analysis in AML Samples

For the second data chapter of my thesis, I set out to investigate the interplay

between cellular pY, TKs, and PTPs in another disease model, namely, AML. To this end,

12 primary samples from newly diagnosed AML patients were analyzed by MS, which

produced quantitative profiles of protein pY in the 12 samples and expressed PTPs in

eight of the 12 samples. Unsupervised hierarchical clustering based on the quantitative

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pY profile showed the presence of two patient sub-groups: groups with relatively high

and low levels of overall phosphorylation. Furthermore, I demonstrated that the total

level of Y phosphorylation in the samples were highly correlated with the summed levels

of TK A-loop phosphorylations, indicating that the activation of TKs in AML may exert a

great influence on cellular pY. Consistently, PLSR analysis showed that, with an eight-

component model, 100% of pY variations in the 12 samples could be predicted, with the

first three components collectively predicting 85.6% of the variations. These analyses

implicated two axes of TK-mediated pY regulation in AML: one through Syk, Fes, and

Fgr activation, which collectively explained 46% of pY variations, while the other axis

involved Abl2 and Lck (or Src, Yes, or Fyn), whose activation predicted 29% of pY

variations. Next, the co-variance between PTP expression and cellular pY was examined

in eight corresponding AML samples, which revealed generally positive correlations

between PTP and cellular pY levels, as well as demonstrated that cellular pY levels were

highly predictable based on PTP expression levels, with a single component predicting

98.88% of pY variations in the resultant model. This analysis implicated ten PTPs (Ptpn1,

Ptpn6, ptpn7, Ptpn9, Ptpn11, Ptpn12, Ptpra, Ptprc, Ptpre, and Ptpro) in pY regulation in

AML. Finally, this study provides an additional line of evidence in support of the

proposed model that TKs/PTPs systemically modulate cellular pY levels. The fact that

this model was demonstrated in AML in addition to MM implies that the systemic

regulation of pY could be a general phenomenon in biological systems.

Future investigations should include elucidation of the functional significances of

the TKs and PTPs implicated in this study of AML. Out of the 15 enzymes implicated by

my analysis, Ptpn11 and the majority of the TKs are already under heavy investigation,

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however, the functional significance of the TK Abl2 and PTPs Ptpn1, Ptpn6, ptpn7, Ptpn9,

Ptpn12, Ptpra, Ptprc, Ptpre, and Ptpro in AML still needs clarification. Although its close

relative Abl1 is a well-studied oncoprotein, the research on Abl2 has so far been only

focused on breast cancer, where it was found to promote invasion and suppress tumor

growth (242). The fact that ABL2 is genetically fused to the ETV6/TEL oncogene in an

AML cell line implies that it may have a cancer-promoting role in AML. Investigating

the role of Abl2 in AML would be interesting and may reveal Abl2 as an oncogenic

target. Moreover, my data showed an astonishingly high degree of predictability of

cellular pY levels based on PTP expression (Figure 3.3 B), with all of the implicated

PTPs highly correlated with Component 1 of the model that explained 99.88% of pY

variations, implying a great dependency of cellular pY on PTPs. However, the interaction

mode between these highly correlated PTPs is unclear. One hypothesis is that a single

PTP may be at the top of the regulation chain and the other PTPs are all downstream

effectors of that PTP. If this were true, disruption of one PTP may have a great

consequential effect on the other PTPs as well as the overall pY profile in AML cells.

This theory can be tested with knock-down experiments. Alternatively, the PTPs may not

be controlled by a single upstream PTP, but may share responsibilities downstream of

one or more pathways. In this case, knocking down each PTP may lead to varied partial

responses, and an examination of the nature of the responses may reveal the interaction

mode of the PTPs. For example, PTPs impacting non-overlapping subsets of pY-

protein/PTP effectors may be independent regulators; conversely, partial to complete

overlap in the sets of downstream effectors may indicate cooperation between the PTPs.

Additionally, the phenotypic consequence of PTP disruption should be assessed in order

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to understand the biological function of these PTPs in AML. Furthermore, the identities

of upstream regulators of the PTPs may be implied by the downstream effectors and

functional consequences.

Table 5.1. Summary of PTPs and TKs implicated in MM and AML

Names of alternative proteins containing the same tryptic peptide sequence are

given in brackets.

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5.3 Summary and Future Directions of the Functional Study of Lyn

Y194 Phosphorylation

For the second question I proposed to answer with this thesis, I tested the binding

properties of SFK SH2 domain using Lyn SH2 as a model. The rationale for this study

was given by the observation that a conserved Y site (equivalent to Lyn Y194) in SFK

SH2 domains was prevalently phosphorylated in AML and CLL primary samples and

appeared to be regulated by phosphatase. Affinity purification using immobilized Lyn

SH2, unphosphorylated or phosphorylated at Y194, showed that Y194 phosphorylation

reduced Lyn SH2 binding to both phosphopeptides and phosphoproteins. These results

were confirmed by fluorescence polarization binding assays using designed pY-peptide

probes containing high-affinity and relatively low-affinity motifs for binding the Lyn

SH2 domain, which showed that, regardless of their relative affinities, binding of these

peptides were reduced by Y194 phosphorylation. Analysis of the SH2 and phospho-SH2

bound motifs showed a decreased selectivity for the pY+3 residue in the SH2-binding

ligands as a result of the Y194 phosphorylation, suggesting that pY194 changed the kinetics

of binding of the pY+3 residue. Therefore, my results indicate that tyrosine

phosphorylation of Lyn SH2 domain modulates its binding affinity and specificity, which

may be a general mode of regulation for all SFKs.

Future investigations should aim at placing the regulation through SH2 domain

phosphorylation of SFK into a biological context, in other words, the upstream events

that lead to SH2 domain phosphorylation and the downstream effectors as well as the

phenotypic output should be examined. Our lab initially identified Lyn Y194 as a site

preferentially phosphorylated in KMS12 mouse xenograft tumor compared to its cognate

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cell line (139). This observation implies that Lyn pY194 could be downstream of the

various stimuli presented by the tumor microenvironment. Therefore, testing the impact

of cytokines highly implicated in MM (i.e. IL-6, FGF, or IGF-1) on Lyn Y194

phosphorylation state would be a good starting point for identifying the signaling

pathways that involve this phosphorylation. Alternatively, the proteins that I identified

would bind directly to Lyn SH2 or pSH2 in my study could be further explored for their

functional relationships to Lyn. These proteins are likely interaction partners that may be

upstream regulators or downstream effectors of Lyn. In particular, proteins that bound

differentially to Lyn SH2 and pSH2 may be involved in pathways that are modulated by

Lyn SH2 phosphorylation. Understanding their functional interplays may help to map out

the biological context of Lyn Y194 phosphorylation. Furthermore, site-directed

mutagenesis can also be used to substitute Lyn Y194 with a non-phosphorylatable residue,

such as phenylalanine. The phenotypic effect of this substitution could then be tested in

MM cells with cell assays, or in xenograft tumor systems to check its effect on MM

tumor development. Moreover, SH2 domain phosphorylation in other SFKs in various

normal and disease systems should be examined. Together, these data may draw a more

complete picture of the biological function of modulation through SFK SH2 domain

phosphorylations.

5.4 Concluding Remarks

Protein-tyrosine phosphorylation-mediated signaling, along with other regulated

physiological pathways, compose important aspects of life in that they control the growth,

division, and death decisions in the basic unit of all living organisms, the cell. It is a

process that must be tightly managed at all times to ensure that each cell carries out its

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proper function within a multi-cellular organism. A disruption of this process can lead to

uncontrolled proliferation, which usually manifests as cancer in human beings. Returning

the pY signaling to its normal state in the diseased cells may restore the person back to

health. Proteomics studies allow a quick and comprehensive look at pY signaling and

related enzymatic states in a cell, which may help to decipher the regulatory pathways

and identify major disrupted enzymes in a disease system. Their coupled biochemical

studies, such as that demonstrated in Chapter 4, can help to gain mechanistic insights into

the regulation that may lay the foundation for therapeutic interventions. Together, these

studies serve to advance our current understanding of pY signaling and life, and may later

prove beneficial for finding a cure in the clinic.

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Appendices Appendix Table 1. MS ion current intensities of pY peptides in MM samples

Alternative proteins containing the same tryptic peptide sequence are given in brackets.

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Appendix Table 1. MS ion current intensities of pY peptides in MM samples (cont.)

129

Appendix Table 2. MS ion current intensities of PTP-derived peptides in MM

samples

Data generated by Rob Karisch (OCI).

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Appendix Table 3. MS ion current intensities of pY peptides quantified in AML

Data generated by Jiefei Tong (Sickkids).

131

Appendix Table 3. MS ion current intensities of pY peptides quantified in AML

(Cont.)

132

Appendix Table 3. MS ion current intensities of pY peptides quantified in AML

(Cont.)

133

Appendix Table 4. MS ion current intensities of PTP-derived peptides in AML

Data generated by Rob Karisch (OCI).

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Appendix Table 5. Phosphoproteins bound to Lyn SH2 or pSH2 identified by AP-

MS

Gene Names

Uniprot ID

p-Value

Number of

Unique Peptides

Sequence Coverage SH2/pSH2

Average Intensity (6 reps) Standard Deviation

SH2 pSH2 SH2 pSH2 HCLS1 P14317 0 37 66.3 6.3 16987581024 2838976137 1144390833 1483467486 SKAP2 O75563 1.15E-226 16 51.3 18.7 321871279 17313558 34465553 5208847 DOK3 Q7L591 0 35 75.8 4.0 5177539368 1335978492 458582067 524453653 BTK Q06187 0 55 80.7 3.3 5547891542 1726701097 487142969 628955242 DOK2 O60496 0 31 74.8 4.4 10416378972 2373099001 1267147339 735124459 DOK1 Q99704 0 32 75.5 7.9 3032616782 390732629 489207357 132707572 TRIP10 Q15642 0 30 51.9 13.0 548626301 43182949 77143874 14852033 PRAM1 Q96QH2 0 39 77 23.0 413618525 17844953 68150408 4007082 FYB O15117 0 25 35 20.8 411325049 19754163 66562845 5345012 CSK P41240 0 30 77.6 9.4 1006609640 108182699 196375784 42288553 NEDD9 Q14511 1.20E-125 20 34.3 25.9 69490885 3049647 14710357 1959709 PLCG2 P16885 8.20E-83 19 21 6.1 37969640 6849295 6428818 3687036 TEC P42680 2.76E-68 19 36.9 15.1 30984280 2326707 8075896 1479901 PAG1 Q9NWQ8 0 30 69.2 10.1 1789170625 174668294 463359784 66050016 SYK P43405 0 45 79.7 28.5 718148932 31417821 212823426 22128831 INPP5D Q92835 1.39E-79 9 10.2 12.8 22492988 1772201 6678950 850675 DBNL Q9UJU6 0 26 58.4 8.1 1724184085 201318360 752595150 69861149 BANK1 Q8NDB2 1.15E-07 2 3.7 17.0 3114314 0 1485787 0 KHDRBS1 Q07666 9.46E-84 9 27.8 3.4 131681145 40416836 28448384 18416149 CSNK2B P67870 4.18E-25 6 37.7 1.9 19299428 10330173 3343639 2333940 PTPRC P08575 3.82E-29 7 6.1 2.5 10700110 4068946 3892616 1389089 LCP2 Q13094 2.76E-228 26 44.5 5.6 198250476 32158678 95227632 10422642 PTK2 Q05397 7.96E-154 22 28.9 163.5 53647710 689143 30781957 392998 HNRNPK P61978 0 24 60.1 1.9 383707403 218405803 134282831 139239003 PTPN6 P29350 2.90E-266 27 55.9 2.7 111190035 38735158 46796959 8640541 PTK2B Q14289 0 39 50.7 14.7 123229002 7795343 81128830 4603447 CTTN Q14247 0.000698 2 4.9 15.0 2071777 127962 1410803 52240 DOK3 Q7L591 0 17 57.6 5.4 3560868 657451 2036387 458040 DBNL Q9UJU6 0 26 58.5 4.1 12335205 3654226 7408677 2896502 RASA1 P20936 1.13E-36 11 16.9 7.5 11384875 1353006 7996652 949647 GAB2 Q9UQC2 1.61E-26 3 6.4 17.0 5563535 290350 4413842 173686 PRKCD Q05655 1.94E-13 4 8.5 2.2 5382278 2353387 3185354 1033564 SHC1 P29353 7.05E-12 5 11 3.8 4145970 876801 3196331 918049 DOK3 Q7L591 0 10 46.5 2.9 35739258 13498847 38437049 14600609 PECAM1 P16284 3.91E-27 6 10.8 5.5 9539211 1893218 10131408 1207850 DBNL Q9UJU6 0 25 58.8 3.9 9291536 1083599 4928513 714566 FCGR2A P12318 2.96E-06 2 14.8 10.6 5733179 0 3725791 0 UBA52 P62987 1.06E-50 4 28.1 0.6 9780069 1535316 11932829 1231975 FAM168B A1KXE4 1.47E-37 3 51.8 81.4 13840041 0 6107811 0 PPHLN1 Q8NEY8 0.00019 3 6.1 65.5 3027807 0 1366340 0 AGTRAP Q6RW13 7.10E-07 1 13.8 16.2 4247461 0 2968401 0 PSTPIP1 O43586 1.11E-06 2 5.8 10.5 2520507 0 1267105 0 PSD4 Q8NDX1 2.05E-11 2 2.6 4.8 607169 0 334255 0 TAF1;TAF1L P21675 0.000116 2 1.4 3.5 813890 0 642258 0 ATXN2 Q99700 8.23E-06 3 3.3 8.9 1648788 0 1213217 0 LILRB1 Q8NHL6 3.41E-57 7 20.7 53.4 21223224 0 18415786 0 SLC12A4 Q9UP95 4.22E-06 2 1.8 23.5 2503682 0 1820512 0 FGFR1OP O95684 2.26E-26 2 9 6.5 2804544 0 2569298 0 CTNND1 O60716 1.41E-152 16 23.5 100.2 33727806 184923 23890365 113845 LASP1 Q14847 1.07E-21 5 18.6 40.7 6935300 114873 3349222 64658 CLEC10A Q8IUN9 1.72E-24 5 23.1 49.3 20873940 400846 10879798 163645 LY9 Q9HBG7 9.52E-49 5 11.1 55.0 27644246 551386 4636312 481044 PDLIM1 O00151 0 19 83 89.3 415656279 8900508 242985757 9052856 LAT O43561 3.16E-26 5 38.2 43.9 26121546 598343 7292214 312994 HGS O14964 1.83E-38 12 14.9 47.4 26019789 596378 23861158 407106 RFC1 P35251 5.28E-12 6 7.4 24.4 21297163 552257 18477722 375521 DBR1 Q9UK59 6.16E-26 7 15.3 29.6 8235239 230026 4526188 131522 PVRL2 Q92692 3.67E-79 8 21.2 29.8 26109661 822971 18364379 882686 LDB1 Q86U70 5.45E-28 8 25.5 53.4 19997852 632738 4144959 645380 TBC1D5 Q92609 0 31 47.9 48.6 210227339 7242024 103746183 7367329 BICD2 Q8TD16 0 33 45.8 28.3 182706908 6931024 33150882 3246673 AMPD2 Q01433 8.68E-198 32 38.1 28.8 150469349 5764409 37356910 3320740 SIRPA;SIRPB1 P78324 9.57E-06 3 6.7 15.0 4729190 184531 2635780 106998 PIK3R2 O00459 2.35E-19 5 11.1 25.1 4253465 175871 1597527 132105

ARHGAP27 Q6ZUM4 5.03E-224 23 33.4 33.2 91372473 4193212 27702773 3641805 SSBP4 Q9BWG4 1.72E-17 3 11.2 35.0 5161113 245016 1614588 144914 GIT1 Q9Y2X7 3.29E-238 26 44.4 20.9 157286272 7767527 40415022 4080290 ANKS1A Q92625 5.19E-268 24 32.4 19.4 109371068 5574497 21025195 2453382

135

PEAK1 Q9H792 4.33E-08 2 1.5 14.9 2509981 127943 596015 52232 PKP4 Q99569 6.62E-65 14 17.1 40.7 20272323 1036734 8149908 631249 SSBP3 Q9BWW4 6.14E-39 7 29.6 20.7 35010872 1809587 4617943 1351264 STAM Q92783 9.77E-87 8 24.1 42.2 27782624 1500675 24244000 926414 VPS26B Q4G0F5 3.27E-62 13 42.6 17.5 50489378 2753023 33220257 1427675 ARAP3 Q8WWN8 2.15E-34 9 9.1 50.4 14359502 791221 3513492 433892 LST1 O00453 0.000336 1 11.5 15.9 3309569 183325 2240025 74842 SEC23A Q15436 1.64E-190 15 27.2 29.3 25114233 1418116 5998727 1847456 POLR2B P30876 1.84E-38 8 10.1 20.9 9502869 546096 3790237 352444 SH2D3C Q8N5H7 2.06E-103 18 25.6 24.4 40438000 2381504 14722456 2438797 GPN1 Q9HCN4 4.61E-31 6 24.1 22.1 3698466 219838 3430458 89749 ARHGEF7 Q14155 0 28 40.2 15.9 120324815 7574940 18500873 2901619 TXNIP Q9H3M7 4.31E-10 4 13 11.2 2489446 158460 2217008 159589 BICD1 Q96G01 3.14E-27 7 8.2 8.8 4031446 270314 2437141 141920 VPS29 Q9UBQ0 3.33E-57 7 44.6 13.7 28487522 1966385 13731050 915034 CD84 Q9UIB8 1.02E-106 11 42 14.4 69769503 4934745 10377776 2683349 PHLPP1 O60346 3.29E-296 31 29.6 17.8 69413363 4949852 43260081 4459139 VPS26A O75436 6.22E-96 11 41.3 16.5 32500575 2343287 24058116 2260860 WDR48 Q8TAF3 5.40E-28 7 13 28.2 10861747 802765 3932806 439905 MILR1 Q7Z6M3 2.37E-97 9 23 13.0 69049081 5135458 24922236 2516801 SEC24B O95487 0 39 42.7 13.4 778094741 58746517 114175813 19938904 ARHGEF6 Q15052 0 35 56.7 12.9 306887039 23854170 22955976 7291979 ACTN1 P12814 0 69 77.7 12.8 8200089799 641959076 3276714382 280646644 CEBPB P17676 3.64E-47 6 22 12.1 20422118 1624621 6861159 924216 GIT2 Q14161 0 32 54.5 12.7 207464777 16588182 24322922 6009712 RINL Q6ZS11 9.87E-40 5 19.9 13.8 8317131 688511 1217817 422814 POLR2M P0CAP2 4.30E-08 3 9 8.6 976218 82700 576420 44768 PTPN18 Q99952 1.77E-154 7 24.3 12.5 32696164 2833376 18520643 2073925 BRE Q9NXR7 1.22E-108 15 56.9 11.7 119760232 10524684 47556224 5658709 ETF1 P62495 3.39E-292 20 57.4 11.5 185577061 16487946 156124259 14103486 RBM4;RBM4B Q9BWF3 7.39E-27 8 28 9.3 8531464 759328 5666390 341544 NFIC P08651 2.31E-136 7 22 8.8 13880280 1237696 10265277 540086 LPXN O60711 1.51E-126 12 34.5 11.1 73698061 6578191 52121976 4811488 VPS35 Q96QK1 0 30 46.5 10.6 239218731 21635929 141737498 12366275 SEC23B Q15437 0 40 72.5 10.9 961943837 88504852 125079894 21430513 KEAP1 Q14145 6.93E-09 3 5.6 14.6 3159926 290891 1990938 155484 BRCC3 P46736 0 14 46.2 11.3 161457835 15466166 66655062 8892402 TTC7A Q9ULT0 1.82E-73 15 24.7 13.0 35958622 3454035 20703702 2874529 CPSF6 Q16630 0 19 32.7 9.7 391105739 37867453 161102114 12608633 FAM175B Q15018 9.10E-268 20 60.2 10.6 266442307 25808236 49503934 12318308 PAIP1 Q9H074 2.92E-122 12 29 9.9 107051493 10411637 36700972 3534575 FBXO30 Q8TB52 1.19E-17 6 9 14.8 6450965 654983 5240675 361377 PXN P49023 3.13E-22 5 16.5 9.9 9061291 935371 6057518 720212 LRRC25 Q8N386 4.54E-13 3 11.5 8.3 10014818 1058301 6176165 707037 BABAM1 Q9NWV8 0 13 55.3 9.5 83612768 8882660 8245369 2012579 YTHDF3 Q7Z739 4.36E-206 23 41.4 9.4 130405243 14015117 20528387 7930567 PI4KA P42356 0 64 40.5 10.4 226248774 24325198 83828569 15234036 SHMT2 P34897 3.68E-154 18 50.2 9.6 73103700 7939087 29378011 4557273 NUP35 Q8NFH5 3.80E-24 6 25.8 9.3 11328759 1243846 5117666 500060 PTPN11 Q06124 0 25 56.8 8.5 169891899 19068896 61297290 6519653 SEC24A O95486 9.79E-41 7 7.3 10.0 32015826 3598620 10589789 2502693 NUDT21 O43809 0 16 79.3 8.2 484392790 55461583 233891220 23386583 EFNB1 P98172 1.84E-26 2 9 8.6 7443494 857063 2483879 457554 EIF3J O75822 0 18 64.3 7.9 338782698 40482382 135647332 12369116 SMC2 O95347 1.79E-21 9 7.9 8.4 18515653 2215956 9844512 1253478 ASH1L Q9NR48 0.000723 1 0.3 58.5 147158307 17692481 38897250 10906146 NEK9 Q8TD19 1.09E-76 10 15.9 9.1 17752811 2189644 13124745 1901515 TYROBP O43914 1.69E-21 2 26.5 7.6 7363243 919473 3080018 499443 CPSF7 Q8N684 8.62E-90 13 24.1 7.7 46745236 5872743 15066739 1961687 CD300LF Q8TDQ1 7.58E-11 4 17.4 11.5 7068682 906999 5909315 370281 PRIM1 P49642 1.94E-13 4 15.5 16.2 4352202 562079 3792213 313038 SEC16A O15027 0 59 44.2 9.8 725871269 95082660 223882300 76384055 MGRN1 O60291 9.94E-41 10 25.7 6.9 17188679 2271887 10627037 1597013 MTR Q99707 1.87E-67 19 22.5 7.5 38054587 5096430 13057258 3085678 EML4 Q9HC35 0 54 65.4 7.6 2265335725 304953121 425707499 123022188 HSH2D Q96JZ2 1.88E-54 9 39.5 9.3 31411383 4234376 12582438 3332748 PRKAR1A P10644 8.61E-77 11 34.9 7.7 22784516 3083827 5427537 2248908 FNDC3B Q53EP0 3.93E-135 14 19.1 7.1 57599109 7827307 19048598 3717366 POLA1 P09884 3.26E-19 7 5.9 7.9 5434358 744987 5052598 482223 SUPT6H Q7KZ85 1.60E-10 5 4.5 8.7 3914099 543800 2819612 409097 EZR P15311 5.57E-228 30 50 8.1 75578477 10691616 66654289 10431344 BAG4 O95429 5.79E-53 6 17.9 6.7 13654417 1961850 5062662 1561752 SPTLC2 O15270 5.07E-88 9 23.3 9.4 21359084 3078665 13706592 3092344 EMD P50402 5.75E-247 14 53.5 7.6 306380606 45190362 96909211 29911141 TRNAU1AP Q9NX07 6.16E-69 6 24 6.7 40708923 6060531 4877161 2026383 PSTPIP2 Q9H939 0 20 57.8 8.2 326276191 50018819 117789538 43684846 YTHDF2 Q9Y5A9 4.63E-139 11 21.6 6.0 26447040 4100387 14095934 1913619 FUNDC1 Q8IVP5 1.64E-06 2 18.7 7.5 3002684 476893 2791134 286772 ROCK2 O75116 5.63E-78 20 18.8 5.1 26990333 4308810 20410976 3384085

136

FBXW11;BTRC Q9UKB1 3.00E-67 12 24.5 6.7 38898350 6247169 11738431 3183598 FLT3 P36888 7.49E-74 14 19.6 6.2 43235960 6945399 7755656 2353219 KATNAL2 Q8IYT4 0.000218 1 2.2 6.1 24400222 3934346 6953336 2371436 MTMR14 Q8NCE2 5.15E-18 4 12.9 4.9 6958369 1140895 5067349 639602 KIAA1429 Q69YN4 1.64E-218 33 28 6.0 88137874 14678675 39332956 6859805 PJA2 O43164 1.64E-43 6 12.6 8.4 11075471 1857148 2588521 1871721 CARD9 Q9H257 1.00E-217 19 45 5.5 100875650 17064765 53684182 7427602 OCIAD1 Q9NX40 1.04E-21 5 26.1 5.8 8208581 1390577 4844492 807443 SS18 Q15532 0.000289 2 7.2 6.1 6089670 1047036 1604020 575146 PHF10 Q8WUB8 4.91E-16 5 13.3 7.4 12246592 2128091 3711683 1753709 LAT2 Q9GZY6 6.24E-155 9 58 6.1 144906753 25199842 20191357 11792383 WTAP Q15007 7.46E-256 14 43.4 6.4 129067309 22832997 31654470 15110847 ARAP1 Q96P48 1.88E-116 23 20.1 9.6 42916757 7669122 11118445 8190282 SNX1 Q13596 8.63E-95 14 30.8 5.4 53128084 9557496 31985196 6258635 CEBPA P49715 1.50E-06 2 6.1 6.6 4358760 787974 2264095 494967 FOXP1 Q9H334 3.37E-08 1 1.6 4.3 1749136 317812 928866 215752 CBLL1 Q75N03 3.29E-24 5 15.3 6.6 8517955 1555062 6683243 1376828 WBP2 Q969T9 3.37E-102 7 31.4 5.3 68500163 12597136 46010039 8852023 EML2 O95834 1.42E-76 8 13.2 5.3 29355351 5411327 6666712 4135714 CARD6 Q9BX69 3.03E-05 2 2.7 6.6 1247325 236360 817360 96494 NCOR1 O75376 4.32E-100 15 8.1 5.4 30746808 6005139 5274827 2517377 SEC13 P55735 6.46E-302 11 49.7 5.3 124537818 24440802 30211453 12202080 TIMM44 O43615 7.24E-13 4 10.8 5.0 4694643 925454 1357486 518839 SPTLC1 O15269 2.30E-59 8 23 4.8 18851025 3722148 7044586 1958544 LRP6 O75581 0.000836 1 0.6 28.6 274073104 54443310 156668150 55590624 SUN2 Q9UH99 2.31E-203 20 38.1 4.6 94285278 18969219 46670431 6486406 HSP90AB2P Q58FF8 4.38E-250 16 27 24.3 24292159 4962092 13058787 3715877 WASF2 Q9Y6W5 2.48E-20 5 13.3 4.7 8252797 1726232 4112575 992948 PRKACA P17612 7.30E-14 5 22.5 4.3 6921268 1523552 4688496 665475 WDR82 Q6UXN9 1.38E-250 15 62 4.4 196732561 44304839 42819669 13862088 PDCD6IP Q8WUM4 1.75E-49 12 17.1 3.5 18932559 4378703 12977159 2586608 CSNK2A1;hCG_21984 P68400 5.17E-115 13 51.9 4.1 115839728 27175972 73190552 9801056 HVCN1 Q96D96 5.57E-25 5 25.3 4.2 21076058 5013075 7784336 2457891 CLASP2 O75122 4.62E-41 14 16.5 4.1 13026611 3111271 3494992 1143548 CLNS1A P54105 2.55E-213 9 65.8 4.2 118265031 28320940 20482206 11552190 COPR5 Q9NQ92 2.12E-20 3 25 4.7 5375919 1299127 2527067 846671 ZC3H4 Q9UPT8 0 36 41 4.3 601809972 146109409 106558034 72892702 VCP P55072 0 44 65.8 3.7 570210603 140150880 280609041 35537981 SH3GL1 Q99961 6.88E-09 4 16.8 21.2 6510442 1633507 3384599 920000 STK4 Q13043 1.38E-10 3 9.9 7.1 3014405 759411 1801747 498240 PSMD2 Q13200 1.65E-132 22 34.5 3.8 44587753 11320473 24844238 6046360 ETV6 P41212 8.16E-08 3 9.1 4.2 3490402 886777 939015 540107 BET1 O15155 1.91E-11 1 15.3 3.6 3607968 918793 1682103 509034 ZC3H13 Q5T200 8.20E-90 20 14.1 4.1 38457230 9941464 13487600 5067708 ARIH2 O95376 5.35E-24 4 12.6 3.4 7461266 1933114 4313110 969931 PIK3AP1 Q6ZUJ8 2.89E-192 17 32.3 4.4 91283660 24000227 20533948 17311456 CSNK1A1 P48729 3.38E-40 7 23 6.4 17742903 4676442 5515036 5004885 POLR2L P62875 0.000293 2 29.9 2.7 1670630 441222 936308 288381 ATRN O75882 2.12E-30 6 6.7 3.6 10362112 2742088 7350845 2449211 SRPR P08240 1.47E-25 8 17.4 3.8 12354451 3298489 5428663 2128420 CDC37 Q16543 8.08E-155 15 44.7 3.6 141278200 39230046 85252649 25347532 PRMT3 O60678 1.58E-47 8 22.4 3.5 16852725 4694871 12985986 3688210 POLR2I P36954 5.67E-280 8 84.8 3.5 408489922 113986854 137535271 40928707 FAM126A Q9BYI3 3.20E-22 3 9.2 12.9 6468885 1814035 3905037 1060870 NACC1 Q96RE7 6.09E-22 6 14.6 3.6 10847949 3069022 2830113 1815915 PDCD4 Q53EL6 3.31E-276 18 51.8 3.1 189267677 53547580 110055169 25341567 GPN3 Q9UHW5 1.67E-08 3 16 2.9 2923716 831316 2055321 527190 SMARCAD1 Q9H4L7 1.14E-76 13 19.2 3.3 33170218 9627338 17434659 4421561 LIN7C Q9NUP9 1.37E-90 10 53.3 3.4 67410011 19633409 11794271 5117156 VAV2 P52735 1.45E-23 6 9.6 3.8 6683552 1961203 4995155 1732870 CNN2 Q99439 1.68E-96 10 43.4 3.1 56100400 16737618 26956485 5015061 GTF3C4 Q9UKN8 1.32E-05 3 4.5 3.1 887819 266228 690617 152899 PPIL4 Q8WUA2 7.75E-50 10 30.9 3.2 30417586 9138964 11711670 3840654 THEMIS2 Q5TEJ8 0 29 66.9 3.3 1104022460 338119323 176830484 109663990 MRPL15 Q9P015 2.30E-09 3 12.5 3.0 2819234 885902 2476150 838287 VAV1 P15498 0 39 48.8 3.5 198483698 62377007 22338270 33518306 INTS3 Q68E01 2.51E-139 18 24.8 3.0 41610522 13078601 27074175 7408227 PDPK1;PDPK2 O15530 8.85E-115 18 39.6 3.5 79268877 24952246 12687896 16596311 TBCB Q99426 3.70E-60 10 47.1 3.6 24928351 7866873 3847521 5879518 ARAF P10398 8.54E-42 10 21.8 3.0 24111919 7710004 11486048 3396781 DIEXF Q68CQ4 8.23E-298 34 56 3.1 197471721 63364293 42454008 17309128 GRB2 P62993 4.73E-293 18 78.8 3.1 809857435 263873449 60229040 96967160 PSMD12 O00232 1.82E-43 10 29.4 8.1 20155385 6739866 11923524 7145798 SEC24C P53992 5.77E-15 3 3.9 2.9 3560453 1205676 1242201 413831 GPX4 P36969 1.52E-18 4 22.3 2.9 13004822 4416468 5369116 1645904 LTV1 Q96GA3 3.00E-26 5 13.3 2.8 7361326 2502521 2769644 1073719 C17orf62 Q9BQA9 9.48E-08 3 17.6 3.0 3829113 1322568 1140813 1109903

137

EIF3K Q9UBQ5 9.60E-117 12 71.1 2.7 124219468 43633545 46790669 11841624 PSMC1 P62191 1.96E-119 13 41.6 2.9 26001870 9144192 20951321 7370708 C20orf111 Q9NX31 2.81E-66 8 43.8 3.0 19334851 6867308 7618494 4530362 DLG1 Q12959 2.57E-13 2 4.2 3.9 1923465 685035 986635 354710 GIGYF2 Q6Y7W6 1.28E-29 5 4.7 2.3 2365122 850021 1556773 464823 MAPK15 Q8TD08 3.13E-05 1 1.5 3.0 6180175 2235242 858299 1574032 SH2D2A Q9NP31 0.000207 1 3 5.9 1190744 433441 773713 176952 UXT;DCK Q9UBK9 5.80E-05 2 10.2 3.8 1947178 712370 1096543 398852 CD33 P20138 9.17E-85 7 23.1 2.9 37543091 13955419 12762362 8154556 PITX1 P78337 5.55E-57 7 25.8 2.8 21185059 8000223 5179607 5464947 NOLC1 Q14978 2.02E-174 28 34.4 2.6 13054514 4944939 11719060 4574775 PCID2 Q5JVF3 3.35E-34 7 16.3 2.6 9127805 3553426 1869075 1620913 PARF Q3YEC7 1.65E-157 14 26.6 2.4 56518031 22074510 23173588 7747230 AP3M1 Q9Y2T2 6.39E-62 9 34.4 2.3 29127455 11445904 17347349 3218181 FXR1 P51114 1.82E-157 14 31.9 3.3 39349309 15567363 9478921 13073469 EIF3M Q7L2H7 0 17 54.8 2.2 133658619 53504741 81864232 16188355 SKP1 P63208 3.79E-83 13 73.6 2.7 190713738 76583070 34275261 43523382 OSBPL8 Q9BZF1 4.62E-26 7 10.3 2.3 10194086 4232881 7470043 3220389 YWHAZ P63104 2.50E-231 17 72.7 2.4 152747228 63567272 38714760 16532610 GTF2A1 P52655 4.04E-53 3 18.9 2.4 8867303 3762196 5594353 2361646 PSMC4 P43686 1.34E-67 15 54.3 2.1 41699618 17881535 27226868 11703820 LSM12 Q3MHD2 8.08E-06 2 10.6 2.4 5802254 2514863 1832308 1501333 CFL1 P23528 9.33E-260 15 78.9 2.4 203696244 88959656 26515152 51275079 YWHAQ P27348 2.68E-254 16 56.7 2.3 127247601 56295207 22274488 23357173 LENG8 Q96PV6 1.40E-69 11 19 2.4 20790276 9298238 7675078 5047601 ELAC1 Q9H777 2.11E-07 3 10.5 10.5 4313619 1973660 2259147 1089931 HSPA6;HSPA7 P17066 2.97E-130 11 15.7 2.1 214383571 102080574 45440527 26843937 GNL1 P36915 6.53E-91 11 20.9 2.1 18756674 8983925 4752043 6046871 HSPA8 P11142 0 41 70.4 2.1 2482748944 1207350183 274923419 475662597 HSPA1A P08107 0 32 58.3 2.0 327073617 167515103 51648972 51488544 POLR2C P19387 8.26E-09 4 25.5 5.4 2478054 1275294 997886 839820 PXK Q7Z7A4 0.00138 1 2.8 1.8 466723 246617 362836 182212 TUBA4A P68366 0 24 74.8 1.7 37785781 20295789 19449817 7352790 YWHAB P31946 0 16 69.7 1.8 120937816 65019478 55126708 20512174 TUBB4B P68371 0 23 74.2 1.9 1243008282 669659040 256743504 231232961 TUFM P49411 0 23 66.2 2.0 364877766 204554854 169229146 153585853 CHCHD4 Q8N4Q1 0.001667 1 15.5 2.6 3780037 2144100 2312021 1138446 MGST3 O14880 3.32E-06 1 8.6 1.7 1478451 854345 961509 542192 TUBB P07437 0 22 70.5 1.7 454677708 271068596 70801178 83707720 IL1RAP Q9NPH3 1.71E-19 5 12.1 1.7 6381963 3910519 4653579 3288642 TUBA1B P68363 0 26 79.2 1.6 1288972799 806394332 218356635 229586679 PHGDH O43175 7.40E-92 12 33.2 1.6 46130408 29384473 8383525 9281664 PSMD7 P51665 1.18E-22 5 27.8 5.7 8992222 5881793 8282152 3244848 GARS P41250 1.19E-24 8 17.1 1.5 10878200 7190868 1209202 2618587 PPP2R1A P30153 9.03E-122 20 43.8 1.4 53883909 37919500 7674065 13776088 SLC25A6 P12236 1.42E-190 20 64.1 1.4 321104299 232666208 57807741 78196304 AK2 P54819 2.89E-18 3 22.6 0.4 2006169 2226218 1099353 1694860 HDAC3 O15379 3.34E-57 12 35 0.5 8897226 17594501 3645430 5437371 FBXO3 Q9UK99 2.87E-20 4 12.1 0.2 1322960 2685303 784386 922863 SSBP1 Q04837 8.03E-80 6 49.3 0.4 14190607 32408324 6852204 11297436 KLHDC10 Q6PID8 0.001393 1 2.9 0.4 38174240 96654638 16712178 37566583 MYBPH Q13203 2.01E-41 7 23.1 0.4 7277734 18987831 2881480 6409870 PFKP Q01813 5.75E-15 5 9.3 0.4 1024412 2742464 497296 1354021 UBR5 O95071 0.000628 1 0.5 0.4 17923233 25808008 9859162 15524731 AIFM1 O95831 8.51E-122 20 44.7 0.3 18993765 62866360 4135740 24394873 NCOR2 Q9Y618 4.46E-170 36 19.8 0.2 10314379 49407861 2165497 25231266 EML1 O00423 7.63E-62 1 2 0.2 1010639 6369962 546361 3387853 TAB1 Q15750 1.01E-06 4 8.5 0.04 1784842 13258908 1045321 6662222 POLDIP2 Q9Y2S7 9.64E-27 7 23.1 0.04 514253 6851650 265936 4070087 FN1 P02751 3.68E-58 13 6.3 0.01 1573190 31752722 642252 8173123 LANCL1 O43813 3.62E-139 13 47.9 0.03 3132473 113505214 2177643 37739858 F9 P00740 1.60E-31 3 11.3 0.02 304432 20164287 124284 8407594 GPX3 P22352 0.000147 1 5.3 0.1 0 1492732 0 539358 GFAP P14136 6.65E-13 4 8.2 0.1 0 1859150 0 738358 SPP2 Q13103 5.23E-05 1 5.7 0.1 0 3461572 0 1485623 F10 P00742 5.57E-23 5 9.8 0.01 0 29171044 0 12980445 THBS1 P07996 0 31 29.7 0.04 0 6708382 0 3323703 GSTP1 P09211 5.24E-154 7 48.6 0.002 0 49281245 0 26102498 NUMB;NUMBL P49757 2.17E-10 4 5.7 0.1 0 2026868 0 1235969 HSPA14 Q0VDF9 2.26E-05 2 3.5 0.01 0 15228482 0 12574877 ARFGAP3 Q9NP61 6.53E-06 2 4.3 3.5 1034692 291470 667633 164273 USP24 Q9UPU5 7.43E-96 26 13.6 7.0 33616481 3482525 28082336 2377284 ANKLE2 Q86XL3 3.06E-18 5 7.5 25.5 5163920 264518 4367369 146993 DNAJC1 Q96KC8 8.45E-09 2 4.7 11.5 2242753 194900 1743869 128612 PML P29590 0.000282 2 2.4 4.0 2790442 741066 1654200 495981 STAM2 O75886 1.96E-86 7 23.6 27.4 17767250 397978 16735922 220813 ARHGAP35 Q9NRY4 0.000638 2 1.5 8.7 6983694 502276 6845649 319231 TUBB8 Q3ZCM7 0 10 24.5 1.8 188427113 106660485 49804787 41963121

138

UGGT1 Q9NYU2 3.60E-57 11 13.1 4.0 15671370 12558605 16605746 7903509 CDC34 P49427 6.15E-12 3 12.7 23.5 3664728 0 3433212 0 RIN1 Q13671 0.001852 1 1.4 1.7 324470 65869 243828 26891 PSMD4 P55036 3.58E-118 10 41.4 2.5 16051023 5128650 15736385 4701824 CALCOCO2 Q13137 6.39E-15 4 10.1 4.4 5027890 913989 3793509 733689 LRIG2 O94898 1.06E-15 7 7.3 17.2 5292852 887318 4382268 459108 LILRB4 Q8NHJ6 2.10E-09 4 14.3 8.0 4479635 662581 4268536 365405 PTBP3 O95758 6.18E-232 9 24.6 4.7 39834002 5076490 37310574 2029685 FAM208A Q9UK61 0.001129 1 0.9 2.4 340696 101866 340676 54162 NFATC3 Q12968 6.58E-40 6 8.3 6.2 6254837 792904 5278655 160392 MTHFD2 P13995 0 25 74.6 1.4 668761825 498755526 97186462 193273873 DAP3 P51398 9.49E-49 8 27.9 1.9 19059004 8568725 14806985 5280426 LARP4 Q71RC2 9.88E-07 2 5.5 2.6 2280001 659319 2019629 504241 COMP P49747 3.06E-12 4 5.9 0.1 59923 2792253 24463 2909208 MYEOV2 Q8WXC6 6.86E-17 2 100 3.0 6087068 2197302 6369374 2294169 PRIM2 P49643 5.13E-24 6 15.1 3.6 6228186 1106066 6196862 898471 RIPK1 Q13546 8.44E-45 9 16.4 17.7 14236979 1831801 14709780 1127107 APBA1 Q02410 4.51E-37 4 5.9 2.2 6615641 2977911 5445088 2329818 POLR2A P24928 2.00E-22 9 7.7 5.1 6136203 733835 5981646 321141 UBR4 Q5T4S7 4.07E-86 20 5.8 1.6 14976503 8483130 8123804 2732446 EPS15L1 Q9UBC2 0.000228 2 2.3 4.9 1294824 403223 1003894 216471 MDH2 P40926 2.80E-26 8 32 0.7 10547223 5735211 5817307 5712420 IST1 P53990 3.32E-102 10 43.7 14.2 60538154 3103318 65879687 1825979 ELP4 Q96EB1 1.32E-07 2 6.9 9.9 3535082 360209 3612848 147055 RRS1 Q15050 7.33E-09 3 13.2 2.3 2405677 904650 1854155 896636 FBXO7 Q9Y3I1 0.000723 1 2.5 1.9 2503582 767515 1375259 431392 CAPG P40121 1.66E-28 7 32.8 9.1 14002327 1023786 7724784 685587 RAPGEF6 Q8TEU7 1.16E-08 3 3 2.7 2405440 794132 1636461 382907 REL Q04864 5.49E-06 3 8.2 3.2 5874183 0 3227793 0 RHBDD1 Q8TEB9 0.001094 1 2.9 2.2 2705513 323193 1486740 131943 LILRB2 Q8N423 2.65E-19 3 8 1.3 3823621 526802 2104106 215066 CASP14 P31944 5.54E-06 2 10.3 1.1 383150 960754 218526 536199 PTPN12 Q05209 0.00126 1 2.1 1.7 1918936 0 1061271 0 USP15 Q9Y4E8 2.00E-68 12 18.7 2.1 13510217 5115945 9565357 1805857 SEP15 O60613 1.10E-17 3 25.3 6.5 7642477 474464 4250014 289067 PPIP5K1 Q6PFW1 4.24E-18 7 7.9 1.5 12583155 1212754 6946570 684978 PSME3 P61289 1.15E-16 5 23.6 4.2 3393548 658823 3122106 368887 SIGLEC7 Q9Y286 6.83E-05 2 6.6 6.0 1936725 0 1084650 0 POLA2 Q14181 3.19E-08 1 3 1.8 4035463 534143 2240678 309124 MBD3 O95983 1.14E-29 5 33 2.3 6681968 1685804 6724232 1344952 CROCC Q5TZA2 1.00E-07 3 1.1 4.3 6177636 1035545 5744441 761383 NCF4 Q15080 0.000143 1 4.6 1.2 1480278 197185 833155 80500 NCKAP1L P55160 2.46E-24 7 7.2 4.0 2382353 593037 1753051 513971 SNX5 Q9Y5X3 9.38E-61 10 30.7 5.9 15337958 1812588 16965378 1883408 CASC3 O15234 2.25E-12 5 9.4 3.1 4621025 2557369 4479605 2723236 GBF1 Q92538 5.97E-11 3 2.2 2.5 2695997 679591 2631681 442483 PFDN2 Q9UHV9 2.42E-08 1 9.1 2.0 2570110 1271917 1327037 521645 CDV3 Q9UKY7 3.87E-46 2 14.3 5.3 7552950 561413 4240030 362351 BAG3 O95817 8.45E-12 4 11.5 6.4 4348905 225954 2464224 92245 PSMC5 P62195 9.46E-187 14 44.6 1.8 38363838 20267444 17829628 6527416 TCEB3 Q14241 0.00064 2 3.5 2.9 2536310 210529 1482652 176890 PRDX5 P30044 3.14E-06 2 11.7 2.2 1612589 817125 892695 474001 TRMT112 Q9UI30 1.12E-11 3 32.8 1.4 6300182 1181794 3466714 1218975 PDRG1 Q9NUG6 1.13E-05 1 12.8 1.4 1845346 777825 1034241 440071 PSMF1 Q92530 0.001897 1 8.9 1.6 1647121 0 948764 0 TAF4 O00268 1.64E-26 2 3 4.6 1359896 0 785343 0 UBAP2L Q14157 9.95E-48 8 11.3 4.9 9302149 1709695 9851689 1690030 DCTN2 Q13561 6.48E-35 10 36 6.2 10892583 1229969 11876254 1287731 IPO4 Q8TEX9 1.63E-06 2 3.2 1.5 1789456 582690 1005331 323524 MRPS31 Q92665 8.75E-14 5 23.5 2.9 6446176 1791991 6767162 2101548 TRAF3IP3 Q9Y228 6.56E-05 2 3.6 0.1 540822 5416980 280723 5955556 HSPA9 P38646 0 52 72.6 0.6 2105536972 3707473794 441980546 2166645670 HBS1L Q9Y450 3.10E-133 17 34.9 1.6 53403322 32714036 20735895 14966149 KRT85;KRT81;KRT83;KRT86 P78386 5.22E-09 2 3.6 0.2 0 4735164 0 2779491 USP48 Q86UV5 1.75E-10 3 4.7 2.1 2167850 728416 2356253 376215 RELA Q04206 0.000415 1 2.5 1.1 1132746 213948 693382 135960 GYS1 P13807 2.40E-09 2 4.3 1.3 5319761 1270545 2920835 1201514 RBX1 P62877 2.62E-09 2 24.1 0.6 0 874197 0 980822 MAPK14 Q16539 7.58E-09 3 14.4 2.2 2584504 786295 2338579 630731 ASCC3 Q8N3C0 4.02E-07 3 2.4 2.9 2459857 748750 1374279 462670 DIP2B Q9P265 8.90E-08 5 4.7 2.5 479235854 190724875 236286404 149444472 EEF2 P13639 0 44 60.8 0.5 285782188 579069070 47488216 324783556 FAM126B Q8IXS8 1.66E-24 5 14.3 14.8 4974303 95294 5571753 38904 U2AF1 Q01081 1.01E-211 11 56.2 2.0 12696499 4717377 11864229 3378450 FBLN1 P23142 7.80E-59 5 10.2 0.4 0 2282700 0 1368039 XPO1 O14980 2.22E-32 10 13.3 1.8 8174172 3703379 8661745 3957979 TECR Q9NZ01 8.59E-17 4 12.7 2.0 18057121 9136282 9911477 3344531 CXorf26 Q9BVG4 3.86E-05 3 12.4 0.4 627443 1605345 330104 1103402

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SH3D21 A4FU49 0.000641 1 1.6 3.8 101699213 25277920 62775617 15482647 NOM1 Q5C9Z4 0.000181 1 1.6 3.0 943319 332072 650902 174842 CAPN2 P17655 0.000395 2 5.7 1.8 1686860 1436390 956941 586404 ATXN2L Q8WWM7 8.48E-44 9 12.6 2.3 9675727 3216254 7106378 1049625 MRPL50 Q8N5N7 0.000637 1 7 14.6 2669863 0 1545476 0 HIST1H2AA;H2AFX Q96QV6 5.88E-42 5 40.5 1.3 13542688 3302804 7473879 3340284 EID1 Q9Y6B2 0.000536 1 5.3 15.7 2911721 109072 2299268 60893 ATG4B Q9Y4P1 2.55E-13 3 10.3 3.1 2754487 644688 2795544 679023 SLC4A1AP Q9BWU0 1.79E-10 5 7.9 1.8 3066964 1159876 1822744 822743 MPV17 P39210 0.000745 1 13.1 1.5 1376068 564545 784205 314279 MFAP3 P55082 0.001713 1 3 3.2 2091495 0 1310946 0 PSMB1 P20618 1.86E-79 9 43.6 1.9 39744198 16410422 22638743 9066296 DCP1B Q8IZD4 0.007063 1 2.4 0.2 4390790 5387868 2545197 2997152 PRPS1;PRPS2 P60891 7.45E-77 8 39.6 1.3 28623516 20935993 12127533 12061990 MRPL43 Q8N983 4.79E-06 2 10.2 1.9 3235164 675481 1943931 409680 RAP1B;RAP1A A6NIZ1 3.58E-09 3 16.3 0.7 1500618 2024358 1193190 1726416 PRKD1 Q15139 0.000468 1 1.2 1.2 542437 404718 304112 224146 BID P55957 1.37E-13 2 10 2.3 4375751 1941477 2702972 976603 SPEN Q96T58 3.52E-15 6 1.9 2.4 4309084 1728502 2537466 669656 BCR P11274 9.14E-08 4 3.8 3.9 2733575 0 1816934 0 EIF1AD Q8N9N8 7.27E-102 7 47.9 2.3 28388697 14102229 11427570 9269715 RFC3 P40938 1.59E-10 3 11.5 4.5 5885937 1581949 3781762 1318747 IFITM3 Q01628 9.28E-07 1 12 1.6 2653788 1640662 1191994 1112941 TAF5 Q15542 4.71E-07 3 5 1.1 2061430 666408 1305332 384252 ZDHHC5 Q9C0B5 3.05E-07 4 7.8 4.2 2442820 105901 1616464 61688 HECTD1 Q9ULT8 6.92E-18 3 1.8 4.0 1167904 561087 827225 358305 SLC25A1 P53007 2.07E-49 10 37 1.3 32954104 25642562 7115708 10453933 GTSF1 Q8WW33 3.32E-17 3 19.8 2.2 7402300 3532679 4120053 1805753 SUPT4H1 P63272 1.20E-09 2 21.4 0.9 14864057 1494963 8773021 707892 UBXN2B Q14CS0 0.00263 1 4.5 0.9 1306969 562522 731908 383692 COPS7B Q9H9Q2 6.29E-25 3 20.5 1.6 3567255 1848444 2759071 842276 SNX6 Q9UNH7 2.79E-23 5 17 1.3 8425803 1771390 4714290 993566 TBL1XR1 Q9BZK7 0 19 53.5 0.6 71049748 111109992 22615953 43844217 RPTOR Q8N122 5.15E-12 4 4.3 1.5 3703531 2273687 2013756 793245 PIK3CB P42338 3.01E-06 2 2.9 3.3 2374572 244977 1304329 127777 CTBP1 Q13363 2.08E-13 6 20.2 1.4 4226270 2652710 2453156 938646 C4A;C4B P0C0L4 1.94E-16 3 2.5 0.04 0 5511801 0 3318084 SPAG9 O60271 9.18E-06 2 1.7 8.1 1124499 126914 794682 51812 THUMPD3 Q9BV44 1.64E-06 3 10.1 1.2 1636576 818340 1996710 576597 PSMB6 P28072 5.00E-24 5 32.2 1.6 17060919 9280880 9932286 5157383 LAMP2 P13473 0.001579 1 2.9 1.5 882226 473286 523736 268148 PSMD14 O00487 3.17E-31 4 22.6 1.5 11365091 7088327 11198927 7370391 SDHB P21912 1.23E-05 1 5 2.0 1956885 1204759 1130231 666291 CSTF3 Q12996 4.44E-05 1 2.2 2.2 1361820 775653 771675 438162 ACTR1A P61163 1.05E-43 10 40.4 2.3 11886346 4343254 15099730 4548215 GPS2 Q13227 0.000205 2 5.8 0.8 1214849 1460431 637411 529686 UQCRH P07919 2.79E-28 4 38.5 1.3 14989055 9575404 9822033 2757055 EIF2B2 P49770 6.71E-13 5 20.5 2.7 4943978 1736230 4739403 857672 PTPN11 Q06124 0 25 57.1 5.7 4646169 0 2399308 0 HLA-C Q29963 1.16E-19 5 19.1 2.2 1198082 565415 730237 312861 RC3H1 Q5TC82 1.44E-05 1 1.5 7.5 2654202 0 1376963 0 GMIP Q9P107 0.000777 2 2 0.9 5206476 4761428 2097370 2414840 YARS P54577 0.000608 2 3.4 14.4 18044426 343559 9318106 140257 SASH3 O75995 0.000307 2 10 1.6 4121861 0 2166147 0 NDUFA7 O95182 1.88E-07 2 23.9 4.0 1627140 105165 864867 42934 PSAT1 Q9Y617 3.38E-05 2 5.1 3.1 1795225 0 956064 0 NT5C2 P49902 0.000673 1 2.3 1.8 1700028 676843 1164492 276320 ZGPAT Q8N5A5 3.62E-06 2 4.7 1.5 3021149 1149221 1862207 686464 ZW10 O43264 6.70E-06 2 3.7 2.9 1300438 620866 672221 253467 ZNF598 Q86UK7 0.000333 1 1.3 4.2 716013 0 388821 0 HOXA10;HOXC10;HOXD10;HOXA9 P31260 4.13E-05 2 5.1 1.8 1042916 755565 567278 308458 ATP1B3 P54709 8.15E-05 1 5 0.9 2748366 1524889 1646113 853009 C20orf4 Q9Y312 0.000679 1 3.9 2.9 983609 0 544250 0 SLTM Q9NWH9 3.08E-34 4 4.6 0.7 2535297 4601154 1035031 2376560 DPM1 O60762 1.19E-20 7 38.1 0.5 4247535 7414215 3451087 3464803 FERMT3 Q86UX7 0.001487 1 1.9 4.5 3349093 0 1897201 0 KIF5B P33176 1.25E-14 5 7.9 1.0 5123619 1293748 2902187 913945 ADD1 P35611 7.05E-15 5 9.6 0.9 7225538 2333685 4125550 2628535 ATP2A2 P16615 1.34E-25 6 9.8 1.7 7870892 4348663 4802086 1804715 PPP1R12A O14974 1.80E-206 24 29.4 0.8 4485822 7787015 1831329 4022030 MRPS15 P82914 1.64E-05 3 10.9 0.9 1320135 4544351 935361 6295152 PRDX6 P30041 8.97E-13 2 13.4 2.3 2110511 790860 1613217 468075 ZBTB33 Q86T24 2.30E-08 3 4.8 1.9 1863933 1108959 996127 778707 GAK O14976 5.49E-34 4 4.5 10.9 4992604 4520615 1778761 4289405 DUSP3 P51452 1.52E-07 2 14.6 1.8 5623762 0 3392246 0

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PRKRIP1 Q9H875 2.24E-05 2 9.8 1.5 2735125 1046130 2003142 1117223 TSSC4 Q9Y5U2 0.000378 2 6.1 6.5 2500400 108766 1437470 61742 UBR5 O95071 0.000628 1 0.5 0.8 17923233 25808008 9859162 15524731 C20orf11 Q9NWU2 2.58E-65 4 30.7 1.5 54173444 30746600 47339677 20531690 KRT77 Q7Z794 6.08E-61 10 21.5 0.9 1747738 3716327 910313 3736668 RANGAP1 P46060 3.59E-20 8 16.5 0.5 11246423 2802150 6767124 1944969 GRWD1 Q9BQ67 5.06E-52 9 29.6 1.4 39788335 27841684 15878365 9114174 NME1 P15531 2.95E-18 5 35 1.5 9947618 6718594 6045160 3836062 EIF5A;EIF5A2;EIF5AL1 P63241 7.61E-59 6 33.7 0.6 9311259 15311249 5604787 7777671 MRPL13 Q9BYD1 4.29E-25 7 42.7 7.1 9355508 1054920 11178747 1037438 GRPEL1 Q9HAV7 1.86E-10 3 16.6 1.0 6375855 6620160 3477869 4880816 SSC5D A1L4H1 0.014332 1 0.6 0.4 15156714 27977965 8728423 18567787 FUS P35637 8.76E-56 7 20.3 0.9 9964273 11265022 2538538 3267020 MAP2K3;MAP2K6 P46734 1.10E-06 2 5.4 1.8 2572420 1780911 1909470 2227501 ACBD3 Q9H3P7 3.52E-05 2 4.4 6.5 1720739 163907 1045773 86085 RANBP2 P49792 8.63E-06 2 0.8 6.5 3602033 0 2491783 0 PLD3 Q8IV08 3.47E-06 2 4.5 1.2 2116250 1177683 1297702 700263 RALA;RALB P11233 0.000856 2 8.7 1.5 2235174 1215600 1474847 677514 EXOSC5 Q9NQT4 3.38E-06 2 15.3 8.2 4808124 1278425 3079026 722900 ATP6V1A P38606 0.001212 1 2.9 1.5 1317947 263372 740101 146711 NUMA1 Q14980 3.87E-06 3 1.7 6.2 5661654 734845 10652791 964807 PRMT5 O14744 2.72E-65 16 34.2 1.7 47805799 30927005 27410632 18010800 SFXN3 Q9BWM7 5.83E-27 9 34.8 1.3 9313291 7359245 3324068 2460750 PFKL P17858 1.38E-37 11 22.2 0.7 9351891 11434607 6701463 7669507 USMG5 Q96IX5 4.56E-26 1 25.9 1.3 8993760 7248526 2033782 3605706 GEMIN6 Q8WXD5 3.86E-08 2 15.6 1.3 8178207 2441589 4973459 2835794 POLD4 Q9HCU8 0.000452 2 23.4 7.9 9878362 0 7611040 0 TERF1 P54274 5.98E-05 3 7.3 33.5 13302982 1041676 19495547 671176 LGALS1 P09382 3.24E-105 8 83.7 0.8 17241150 20392354 3962408 9628527 CNP P09543 1.30E-15 5 19 1.2 3032146 1966462 2692426 565089 HAT1 O14929 2.57E-44 6 21 1.3 18555371 14674845 4217328 6694564 NDUFS5 O43920 4.80E-09 3 34.9 0.6 3916205 927599 2833029 653162 SPG11 Q96JI7 0.041066 1 0.6 4.2 4050498 0 1653609 0 NCKIPSD Q9NZQ3 9.53E-11 4 8 2.6 13643000 705386 5569731 287973 TXN P10599 2.96E-42 7 65.7 1.0 137484873 164146811 58816608 125497396 USP9X Q93008 0.001504 1 0.4 8.3 1537065 676535 911848 434191 WARS P23381 3.39E-11 5 13 0.7 2092837 2683024 2138657 3099705 BOLA2 Q9H3K6 1.75E-91 2 29.1 1.4 6538830 4805160 4242765 3281499 BAZ1A Q9NRL2 0.000173 2 1.5 1.0 1424287 408300 805543 378895 CBFB Q13951 3.41E-20 4 26.9 4.2 4834406 1966933 4471897 2587509 SLC25A10 Q9UBX3 9.49E-11 4 20.6 0.7 2234308 3204008 963703 2292827 NMI Q13287 1.78E-14 2 8.1 1.3 1361349 471619 707585 292800 TUBB6 Q9BUF5 1.61E-124 11 37.2 2.0 13027929 7607046 13199925 7210869 PNKD Q8N490 0.000113 1 7.7 0.2 826057 3340506 473098 2358486 PPIH O43447 1.01E-06 3 14.7 6.4 2121155 4266567 2216562 2875052 PRDX2 P32119 6.22E-21 6 27.8 1.2 6063893 5322415 2350392 3070238 NKRF O15226 0.000842 2 2.8 1.1 1018837 2629020 595963 1640020 TAF2 Q6P1X5 2.96E-16 5 5.9 1.2 3204734 2293272 2915066 1263863 SLIRP Q9GZT3 1.17E-06 3 31.2 1.2 15183077 1006643 6198465 858038 TBC1D15 Q8TC07 2.19E-05 2 2.9 0.6 1252072 964846 753236 538720 AHNAK Q09666 7.47E-108 33 18.7 1.4 130801356 96309694 121406398 72893691 FTSJD2 Q8N1G2 0.000239 1 1.4 1.0 1419070 334696 735067 205593 TARBP1 Q13395 5.30E-06 2 1.2 0.2 10953502 7423545 6080666 3018108 C2orf47 Q8WWC4 1.25E-06 2 8.2 1.4 880096 654441 565465 387447 HLA-C P10321 4.72E-23 4 15.6 0.8 2625703 1266084 1448022 944466 GALK1 P51570 2.02E-09 3 8.2 1.1 4954704 4507439 4441900 4714895 C1orf63 Q9BUV0 5.81E-07 2 7.9 1.6 2690279 1768056 1834484 1338814 ZYX Q15942 2.78E-09 3 9.1 0.4 2900391 1946120 1963148 864693 FOSL2 P15408 9.94E-05 1 3.7 0.7 2683345 938074 1488999 381747 PPP3CA;PPP3CB;PPP3CC Q08209 1.65E-05 2 3.5 1.2 2513193 2075141 1350305 1174885 EIF4H Q15056 1.41E-09 3 22.6 0.7 7007716 5983066 3990802 3671574 EEF1A2 Q05639 3.99E-188 13 43.2 0.5 7493723 2954325 4479882 3418270 RBBP7 Q16576 1.76E-61 11 30.6 1.3 17931492 14146006 10254207 11393224 PSMD3 O43242 4.40E-112 15 36.9 0.6 27980492 43761129 24354868 60997058 MRPS12 O15235 5.49E-28 5 46.4 1.3 19998861 18013458 3531694 12478684 COPS7A Q9UBW8 1.41E-17 5 20.4 1.0 7314721 6448264 3970310 2887894 PSMD10 O75832 0.000173 1 4.4 2.1 1449624 695802 1392670 563476 SNRPG P62308 1.65E-23 4 67.1 0.9 11085116 12173400 3375848 5984123 TPM2 P07951 8.53E-183 13 28.2 1.2 9991816 11490411 5773782 7023937 RAC2;RAC1 P15153 4.58E-22 6 32.8 1.0 16487508 17931847 5726479 11922771 RFC2 P35250 5.64E-08 2 10.2 0.5 2102183 1764302 2271271 1148903 COG1 Q8WTW3 0.001904 1 0.8 0.3 2232998 977670 1153242 550139 TRMT2A Q8IZ69 0.000225 2 4.6 0.9 2123846 1345121 1205628 789031 GPATCH4 Q5T3I0 1.06E-05 3 8.9 2.8 6703072 4306151 2736518 1757979 ABCB5 Q2M3G0 0.002494 2 2.7 1.4 13621390 3518409 7077196 2804946 DYRK1A;DYRK1B Q13627 3.09E-06 2 3.8 0.5 2618112 2420221 1437212 1597361

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EEF1A1;EEF1A1P5 P68104 0 21 61.3 1.1 1082415951 1042579709 157362550 422879353 MED15 Q96RN5 7.08E-09 1 2.3 1.3 941843 558199 491441 349635 TAF6 P49848 0.000144 2 3.5 0.4 1899667 1589496 1174362 1358158 ERP44 Q9BS26 1.43E-09 3 12.3 0.4 2451526 1769065 1495433 1423459 STIP1 P31948 7.86E-13 5 11.2 1.0 4699245 2201251 2861011 1419258 MAT2A P31153 3.76E-08 3 8.9 0.5 1515005 1390644 819683 799256 PRDX1 Q06830 8.83E-182 13 68.8 1.1 167798160 165169370 71657120 115128408 RPS6KA3;RPS6KA6;RPS6KA1;RPS6KA2 P51812 0.000549 2 3.4 0.6 1123388 666856 658183 346279

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