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27.03.07 F:\...\070327_Talk qPCR Meeting Munich (qPCR + FFPE).ppt 1 Successful measurement of gene expression by quantitative PCR and DNA chip analysis with RNA derived of FFPE material Rolf Jaggi Department of Clinial Research Research - Univ. of Bern
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Successful measurement of gene expression by quantitative ... · cDNA synthesis random primer vs. gene-specific primers QPCR short amplicons MGB assays or LNA assay DNA chip experiments

Jul 18, 2020

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Page 1: Successful measurement of gene expression by quantitative ... · cDNA synthesis random primer vs. gene-specific primers QPCR short amplicons MGB assays or LNA assay DNA chip experiments

27.03.07 F:\...\070327_Talk qPCR Meeting Munich (qPCR + FFPE).ppt 1

Successful measurement of gene expression by

quantitative PCR and DNA chip analysis

with RNA derived of FFPE material

Rolf Jaggi

Department of Clinial Research Research - Univ. of Bern

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Contents of talk

• Material kryo-preserved 4x 25 µm thick sectionsFFPE material 5-10x 10 µm thick sections

• Methods RNA Isolation "own" protocolhomogenize in lysis bufferdigest proteinase KDe-modify chemical modifications induced by formalin

cDNA synthesis random primer vs. gene-specific primers

QPCR short ampliconsMGB assays or LNA assay

DNA chip experiments "own" primers for cDNA synthesisArrays CombiMatrix 12k

Agilent 44k

• Results QPCR single genesprofiles (expression of multiple genes)

DNA chips kryo vs. FFPEsingle genesprofiles

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Procedure/major steps for QPCR-based analyses

• Identification of marker genes from microarray studies, literature etc.

• Reduce number of test genes to minimum

• Select appropriate control genes

• Isolate RNA from FFPE sections

• Establish robust real-time assays which give reproducible results even with fragmented RNA

• Evaluate results on the basis of single genes

• Develop model (= scoring system) involving groups of genes, we used

Estrogen scoreHER2 score Prognostic scoreProliferation score

Cronin et al. Am J Pathol 164 (2), 35-42, 2002. Measurement of Gene Expression in Archival Paraffin-Embedded Tissues.

⇒ 16 test genes & 5 control genes

⇒ Recurrence Score (RS)→ prognostic for patients with primary

breast cancer (stage I or II, N0, ER+)commercial test is available (~3'000$ per test)

e.g. Oncotype DX

⇒ RS is also predictive for response to chemotherapy

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Experimental design

14 breast cancers

kryo-preserved sample

isolate total RNA = A (standard procedure)

FFPE block

isolate RNA⇒ B, Qiagen FFPE protocol⇒ C, ncLysis buffer (Applied Biosystems)⇒ D, "own" procedure (silica-based spin columns)

"matched samples"

De-modify

make gene-specific cDNATaqMan PCR (MGB assays or LNA probes)Evaluation:

Expression analysis of individual genesNormalizationDevelop models (= scoring system) of multiple genes

Estrogen-response scoreProliferation scorePrognostic score

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Experimental design

14 breast cancers

make gene-specific cDNATaqMan PCR (MGB assays or LNA probes)Evaluation:

Expression analysis of individual genesNormalizationDevelop models (= scoring system) of multiple genes

Estrogen-response scoreProliferation scorePrognostic score

kryo-preserved sample

isolate total RNA = A (standard procedure)

FFPE block

isolate RNA⇒ B, Qiagen FFPE protocol⇒ C, ncLysis buffer (Applied Biosystems)⇒ D, "own" procedure (silica-based spin columns)

"matched samples"

De-modify

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QPCR

single gene data

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RNA quality is critical: comparison of different protocols

0.2

0.5

1.0

2.0

4.0

6.0

kryo

A =

Qia

gen

B =

ncL

ysis

D =

ow

n

M (l

adde

r)

kbGAPDH

(gene-specific, single-primer)

10

15

20

25

30

35

40

2 3 6 8 10 13 14 15 16 17 18 19 20 22

cDNA

Ct

ABCD

A = kryo B = QiagenC = ncLysisD = own

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Comparison of own protocol with different commercial kits Stratagene, RecoverAll (Ambion)

GAPDH

23

25

27

29

4 1 0.25

ng RNA input

Ct

De-mod. (3)De-mod. (1)De-mod. (2)RecoverAll Stratagene FFPE Kit

IGBP5

22

24

26

28

30

4 1 0.25

ng RNA input

Ct

De-mod. (1)De-mod. (2)De-mod. (3)RecoverAll Stratagene FFPE Kit

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Comparison of results with different de-modification protocols (1)

24

28

32

36

40

no (1) (2) (3)

RNAlater De-Modification

Ct

IGBP5 longIGBP5 mediumIGBP5 short

no (1) (2) (3)

FFPE – De-modification

20

24

28

32

36

40

44

no (1) (2) (3)

RNAlater De-ModificationC

t

GUSRPLPOTFRCRPLP0

no (1) (2) (3)

FFPE – De-modification

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Comparison of estrogen receptor expression and results based on immunohistochemistry

Tumor #

ER-status (IHC)0

5

10

15

20

25

30

15 18 20 10 6 22 2 8 16 13 14 17 3 19

neg neg neg + + + + + + + + + + +

arbi

trar

y un

its (l

og2)

kryo (A_gs)

FFPE (D_gs)

ESR1 expression

AB: MGB assays

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QPCR

Multiple genes ⇒ Scores

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ERBB2 IHC = 3+

ERBB2 IHC = 3+

IHC = -ve IHC = -ve

Test Rank corr. p-valueA_gs vs D_gs 0.95 < 0.001

FFPE-derived materialkryo-preserved tumor material

Proliferation score: results from 14 tumors

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ER score ER score ER score (based on mean) (based on median) (based on geometric mean)

Normalization based on reference genes

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Array data

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QPCR DNA chips

– Limited number of features/experimentHigh sensitivity of methodWorks with degraded RNA ( used with optimized reverse transcription and qPCR assays)Large number of samples potentially available from clinical trials

– No standards for normalization

Large number of features/arrayMethod depends on good quality RNA (e.g. kryo)Established procedures fornormalization

– Samples are oftenheterogeneous

– Limited number of samples per study

– Various treatment regimens– Outcomes sometimes unknown

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Application of FFPE-derived RNA to DNA chips

fragmented RNA

FFPE material(ZR-75-1 cells)

DNA chipCombiMatrix

DNA chipCombiMatrix

cRNA modified prot.

cRNA standard prot.

intact RNA

Kryo material (ZR-75-1 cells)

DNA chipCombiMatrix

DNA chipCombiMatrix

cRNA modified prot.

cRNA standard prot.

compare kryo vs. FFPE (standard)

modified

technicalreplicates

technicalreplicates

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53785_#4b vs 4b

4

6

8

10

12

14

16

4 6 8 10 12 14 16

53785_#4a vs. 4a

4

6

8

10

12

14

16

4 6 8 10 12 14 16

CombiMatrix 12k chips: Technical replicates

standard protocol

modified protocol

Correlation: ~0.4 – 0.58

Correlation: ~0.98

technicalreplicates

technicalreplicates

compare kryo vs. FFPE

standard prot.

modified prot.

compare kryo vs. FFPE

kryo

FFPE

kryo

FFPE

Correlation: 0.82 – 0.87

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Tumor #2kryo vs. FFPE, standard protocol

Tumor #2 kryo vs. FFPE, modified protocol

Agilent chips: kryo vs. FFPE tumor RNA (Scatterplot)

Tumor #2kryo, standard protocol

Tum

or #

2FF

PE

, sta

ndar

d pr

otoc

ol

Tumor #2kryo, modified protocol

Tum

or #

2FF

PE

, mod

ified

pro

toco

l

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ER Expression in 6 tumors

ER Status + + + - + + + + + - + +

FFPE kryo/RNAlaterDNA chip

QPCR results

0

5

10

15

20

Tu#1 Tu#2 Tu#3 Tu#4 Tu#5 Tu#6 Tu#1 Tu#2 Tu#3 Tu#4 Tu#5 Tu#6

FFPE kryo

Arb

itra

ry u

nit

s (

log

2)

ESR1GAPDHRPL7ARPLPOUBB

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0.9120.9140.9240.9440.8930.4510.9470.4680.9410.779Spearman(ranks) (116)

0.930.9180.9360.920.8890.4590.8970.5810.9620.923Pearson (116)

Tu #6modif.

Tu #5modif.

Tu #4modified

Tu #3modified

Tu #2modified

Tu #2standard

Tu #1modified

Tu #1standard

ZR-75-1modified

ZR-75-1standard

Summarization of results: correlations

Agilent 44k chips 60-mer oligosall genes 41'00021 Paik genes represented by 116 spots on the chip

intact vs. fragmented RNA fom cells

kryo vs. FFPE tumor RNAfrom breast cancer

0.8350.8230.8370.7930.8140.5630.8170.5850.9050.935Spearman(ranks) (all genes)

0.8620.8570.8620.8290.8380.6220.8450.6610.9080.932Pearson (all genes)

Tu #6modif.

Tu #5modif.

Tu #4modified

Tu #3modified

Tu #2modified

Tu #2standard

Tu #1modified

Tu #1standard

ZR-75-1modified

ZR-75-1standard

41'000 genes

21 Paik genes

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• Material- kryo material 4x 25µm thick sections QPCR/DNA chip

feasible

- FFPE Material 5-10x 10µm sections QPCRtechnically demandingDNA chip

feasible specialized protocols

• Technology- RNA Isolation Homogenization

Proteinase K digestionDe-modification

- cDNA synthesis Gene-specific primers during RT

- QPCR short ampliconsMGB assays or LNA assays

Summary

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• Janine AntonovSybille MattheyAndrea OberliAnna Baltzer

• Hans Jörg Altermatt, MD Pathology Länggasse, CH-3012 Bern

• Achim Fleischmann, MD

• Vlad Popovic, PhDMauro Delorenzi, PhD

• Support: Bernese Cancer League (BKL)Swiss Cancer League (SKL)International Breast Cancer Study Group (IBCSG)Applied Biosystems, Rotkreuz, Switzerland

Collaborators