Page 1
Page 1 of 24
Genomics of ovarian cancer progression reveals
diverse metastatic trajectories including intraepithelial metastasis to the fallopian tube
Mark A. Eckert1, Shawn Pan1, Kyle M. Hernandez2, Rachel M. Loth1, Jorge Andrade2, Samuel L.
Volchenboum2,3, Pieter Faber4, Anthony Montag5, Ricardo Lastra5, Marcus E. Peter6, S. Diane
Yamada1, and Ernst Lengyel1
1Departments of Obstetrics and Gynecology/Section of Gynecologic Oncology, 2Center for Research
Informatics, 3Pediatrics, 4University of Chicago Genomics Facility, 5Pathology, The University of
Chicago, Chicago, IL
6Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
Corresponding Author: Ernst Lengyel, Department of Obstetrics and Gynecology/Section of
Gynecologic Oncology, The University of Chicago, Chicago, IL 60637, USA E-mail:
[email protected] ; Phone: 773-834-0740; Fax: 773-702-5411.
Running title: Genomic changes in STIC
Keywords: ovarian cancer, genomics, phylogenetics, in situ, metastasis
Financial Support: This work was supported by a Marsha Rivkin Foundation award (M. Eckert), a
National Cancer Institute grant - CA111882 (E. Lengyel), a Harris Family Foundation award (S.D.
Yamada), and a University of Chicago Comprehensive Cancer Center Team Science award (E.
Lengyel and S. Volchenboum).
The authors disclose no potential conflicts of interest.
Word count: 4590
Total number of figures: 4 main figures; 6 supplementary figures
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 2
Page 2 of 24
Total number of tables: 6 supplementary tables
Abstract
Accumulating evidence has supported the fallopian tube rather than the ovary as the origin for
high grade serous ovarian cancer (HGSOC). To understand the relationship between putative
precursor lesions and metastatic tumors, we performed whole exome sequencing on specimens from
eight HGSOC patient progression series consisting of serous tubal intraepithelial carcinomas (STIC),
invasive fallopian tube lesions, invasive ovarian lesions, and omental metastases. Integration of copy
number and somatic mutations revealed patient-specific patterns with similar mutational signatures
and copy number variation profiles across all anatomic sites, suggesting that genomic instability is an
early event in HGSOC. Phylogenetic analyses supported STIC as precursor lesions in half of our
patient cohort, but also identified STIC as metastases in two patients. Ex vivo assays revealed that
HGSOC spheroids can implant in the fallopian tube epithelium and mimic STIC lesions. That STIC
may represent metastases calls into question the assumption that STIC are always indicative of
primary fallopian tube cancers.
Statement of Significance
We find that that the putative precursor lesions for high grade serous ovarian cancers, serous tubal
intraepithelial carcinomas, possess most of the genomic aberrations present in advanced cancers. In
addition, a proportion of STIC represent intraepithelial metastases to the fallopian tube rather than the
origin of HGSOC.
Introduction
High-grade serous cancer (HGSOC) encompasses several pathological tumor entities, including
ovarian, fallopian tube, and peritoneal cancer. The cell of origin of these cancers is currently
unresolved, but their pattern of dissemination, clinical behavior, and chemosensitivity is very similar
(1-3). For almost a century it was believed that the surface epithelium of the ovary gives rise to
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 3
Page 3 of 24
HGSOC. However, in 2001, a Dutch research group described preneoplastic lesions in the fallopian
tubes of patients at high familial risk of HGSOC (4). Careful sectioning of the fallopian tubes in
patients with HGSOC has revealed serous tubal intraepithelial carcinomas (STIC) with atypical
histologic changes that resemble the invasive serous component found in 50% of all patients with
HGSOC. Further molecular analysis of STIC found identical TP53 mutations in the STIC and
corresponding HGSOC, as well as a similar upregulation of cell cycle and DNA repair proteins (5, 6).
Because TP53 gene mutations represent one of the earliest genetic changes in HGSOC, and
because they are detected in all STIC, it was then considered evident that STIC may be the precursor
lesions of HGSOC. This hypothesis received additional support with the recent development of a
genetic mouse model designed to determine if the fallopian tube can give rise to HGSOC. In this
model, the PAX8 promoter, specific to secretory fallopian tube epithelial cells (FTECs), was used to
inactivate BRCA1 (Breast Cancer 1; germline mutations in BRCA1/2 occur in about 13% of HGSOCs)
and PTEN and drive expression of mutant TP53. These mice develop tumors mimicking human STIC
lesions in the fallopian tube and have molecular alterations that recapitulate human HGSOC (7). If
one assumes that HGSOC advances along a linear progression series from in situ tumors to invasive
tumors to metastasis, as is believed of colon cancer (8), these findings support the hypothesis that
HGSOC originates in the fallopian tube.
Fully understanding the relationship of STIC and HGSOC requires a comprehensive
understanding of the genomic alterations underlying both STIC and HGSOC. Using next generation
sequencing technologies, the TCGA and an Australian consortium has provided a snapshot of the
genomic changes and signaling pathways characterizing invasive HGSOC at the ovary (2, 9).
Compared to other carcinomas, HGSOC is uniquely characterized by recurrent copy number variants,
with TP53 the most commonly mutated gene (10). In pancreatic and prostate cancer, among others,
multi-site sequencing of primary tumors and metastases have revealed evidence of multi-step
dissemination and unraveled the complex genomic trajectories of metastasis (3, 11). Although several
groups have performed sequencing of HGSOC and begun to understand its metastatic trajectory
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 4
Page 4 of 24
throughout the peritoneal cavity (12-14), without integrative whole exome sequencing of STIC and
metastatic lesions, the reconstruction of a complete metastatic trajectory for HGSOC is not possible.
We set out to characterize the dynamics of mutations and copy number variations during HGSOC
dissemination, using a systematic genomic characterization of a uniform group of sporadic advanced
HGSOC patients with STIC and without BRCA1/2 germline mutational changes. We hypothesized
that sequencing both putative precursor lesions and metastatic HGSOC will elucidate early core
events in HGSOC and the genomic characters necessary to reconstruct its step-wise progression.
Results
To begin to systematically understand the spatiotemporal genomics of ovarian cancer
progression, we identified a cohort of eight patients who presented for primary tumor debulking
surgery with advanced, metastatic HGSOC. Germline DNA was available for all patients, and the final
pathology for these patients showed STIC, invasive FT, ovarian, and omental metastases (Fig. 1A).
These four anatomic sites encompass the hypothetical progression series; from in situ STIC
precursors to locally invasive fallopian tube lesions, then to primary ovarian metastases, and finally,
to distant peritoneal omental metastases. All were chemotherapy naïve, with no germline BRCA1/2
mutations and no significant family history of ovarian or breast cancer (clinic-pathologic features
Table S1). For each anatomic site, the tumor compartments were collected using laser-capture
microdissection (LCM) (Fig. 1B). Microdissection was utilized to both eliminate stromal contamination
and to facilitate highly-specific sequencing of small in situ STIC lesions. Ovarian tumors were
microdissected from the ovary associated with the STIC lesion in cases of bilateral ovarian
involvement. Because, by definition, there is limited material in microdissected STIC (Fig. 1A), the
DNA isolation method was optimized to include longer digestion times and reduction of elution
volumes. Whole exome sequencing (WES) and data processing were performed to assess the
spatiotemporal pattern of genomic alterations during HGSOC progression (Fig. 1C, Fig. S1A).
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 5
Page 5 of 24
Despite low input amounts for some samples (50 ng), depth of coverage and on-target reads were
similar across all anatomic sites surveyed (Fig. S1B-D, Table S2).
An average of 1.0 SNVs per megabase (Mb) were identified, corresponding to approximately 50
de novo somatic mutations per sample, which is comparable to rates identified in the TCGA analysis
of HGSOC (9, 15) (Table S3). The analysis of germline DNA did not detect BRCA1/2 mutations in the
patient cohort. The majority of mutated genes in our analysis had been identified in the TCGA
analysis, confirming that the patient cohort was representative of HGSOC. Mutational burden was
similar across all anatomic sites. The only exception was patient 539, who had a significantly higher
mutational burden in the ovarian and omental metastasis (Fig. 1D). Overall, the pattern of mutations
was enriched for C>T substitutions, a signature associated with aging, mediated by spontaneous
deamination of 5-methylcytosine (10). In contrast, C>A mutational rate, associated with environmental
carcinogenesis (15) was low (Fig. 1E). The mutational signature was correlated with age at time of
diagnosis and was patient-specific (Fig. S1E/F). No significant differences were observed by
anatomic site (Fig. S1G). Mutational signatures, including rates of indel detection, were similar to
those observed in the TCGA analysis of HGSOC (Fig. S1G). Patients with missense mutations in
TP53 had evidence of nuclear p53 stabilization as indicated by high protein expression in the tumor.
One patient (505) had a null splice site mutation and did not express p53 protein (Fig. S1H).
TP53 was the only gene mutated in every patient and anatomic site (Fig. 2A, Fig. S2A) and the
only gene identified as significantly mutated across more than one patient by MutSig, an algorithm
that corrects for high mutational rates in late replicating and poorly transcribed genes (16). Common
mutations in CSMD3 and other genes were not significant. Each patient had the same TP53 mutation
in all anatomic sites (Table S4) while other mutations were limited to a subset of the patients or
anatomic sites (Fig. S2A). Mutant allele frequencies (MAF) for TP53 were high at all sites (0.7188-
1.000), suggesting early loss-of-heterozygosity at the TP53 locus, highlighting the advantages of
microdissection for obtaining high tumor purity (Table S4). In general, an increase in MAF across the
progression from STIC to omental metastases was observed (Fig. S2B).
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 6
Page 6 of 24
To identify candidate driver molecular changes, mutations were assigned to three classes: 1)
core mutations, present in all four anatomic sites; 2) shared mutations, present in two or three
anatomic sites; and 3) private mutations unique to a single anatomic site. In all patients, a minority of
SNVs were “core” mutations, likely to participate in the early transformation of normal cells (Fig. 2B).
Core and private mutations had identical mutational signatures (Fig. S2C). A clear pattern emerged
when we examined mutational class by anatomic site: the STIC and FT sites had a significantly
higher proportion of “private” mutations. Gene ontology (GO) analysis of putative core mutations
across all patients (Fig. 2C) revealed enrichment of three separate pathways involved in cell adhesion
(Fig. S2D), suggesting that mutation of genes involved in mediating contact with extracellular
matrices (ECMs) or other cells may be an early event in HGSOC progression.
HGSOC has a disproportionately high number of copy number variants (CNVs) compared to
other cancers (10). The genomic location of CNVs in our data set were highly concordant with the
TCGA analysis of HGSOC (9), including frequent amplification of chromosome 1q, 3q, and 8q and
deletion of 4p, 4q, and 8p (Fig. 3A, Table S5). Across all anatomic sites, patient-specific copy-number
profiles were apparent, including amplification of cytoband 8q24 in patient 754 (Fig. 3B), but every
patient had distinct amplifications and deletions. Because the deletion of DNA damage repair genes
plays a role in the etiology of HGSOC (9, 17), we specifically investigated copy number profiles for
DNA damage repair and response genes. Indeed, frequent deletion of genes implicated in
homologous recombination (BRCA2, FANCB), base excision repair (APEX2, NEIL3), non-
homologous end-joining (WRN), and DNA damage signaling (RAD23A) was observed (Fig. 3C, Fig.
S3A). Although the extent and frequency of amplifications and deletions varied significantly across
patients (Fig. 3D), we observed no significant differences between anatomic sites (Fig. 3E). We did
not detect any metastasis specific genes. Interestingly, the genomic instability evident in omental and
ovarian sites was already present in the fallopian tube and STIC (Fig. 3E).
Next, we utilized GISTIC, an algorithm to identify significant, recurrent amplifications and
deletions (18), to detect core CNVs collaborating with TP53 to drive HGSOC (Fig. S3B/C). The Euler
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 7
Page 7 of 24
plot in Fig. 3F integrates significantly amplified or deleted genes at each anatomic site, identifying
several genomic events known to be involved in HGSOC tumorigenesis, including CCNE1
amplification, NF1 deletion, and other genes with previously uncharacterized roles in HGSOC biology.
These core genomic events consisted of 93 amplified and 69 deleted genes, which represented less
than 5% of all significantly amplified and deleted genes. Significantly amplified processes included
genes involved in the regulation of transcription and RNA metabolism, as well as several microRNAs
(Fig. S3D, Table S6).
To elucidate the metastatic trajectories of HGSOC in each patient, a phylogenetic clustering
approach was used (11). This analysis revealed three distinct classes of dissemination: I) “Basal
STIC,” in which STIC represented the basal branch (most similar to germline DNA of the patient) of a
hierarchical, step-wise dissemination process. II) “Parallel” dissemination in which no clear hierarchal
dissemination pattern was evident and all branches developed simultaneously from one precursor. III)
“STIC Metastases,” in which other anatomic sites were hierarchically more basal than the STIC
lesions, implying that in these patients, STIC represented metastases to the fallopian tube (Fig. 4A,
Fig. S4, Table S7). Histologically, the STIC from these cases was indistinguishable from the other
basal STIC, although one of these cases presented with intraluminal HGSOC spheroids in the
fallopian tube (Fig. 4B). Intraluminal HGSOC spheroids were present in three of the eight patients in
our cohort, including one patient in whom spheroids adhered to the apical surface of the fallopian
tube epithelium (Fig. 4C).
While intraepithelial metastases of HGSOC to the fallopian tube have not been described, they
have been observed in other tumor types, including endometrial and colon cancer (12, 19, 20).
Intraluminal HGSOC spheroids found within the FT are common findings in HGSOC patients (21).
Because metastasis to the fallopian tube was an unexpected finding, we sought to determine if
HGSOC cells are able to implant into the fallopian tube epithelium. A model of intraepithelial
metastasis was developed, in which full thickness primary human fallopian tubes were co-cultured
with ovarian cancer spheroids (Fig. 4D, Fig. S5A). In this ex vivo model, the normal fallopian tube
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 8
Page 8 of 24
epithelial morphology was preserved, including high expression of PAX8 and junctional expression of
β-catenin and E-cadherin (22) (Fig. S5B). Histological examination of the fallopian tube-cancer cell
explants revealed the presence of implanted tumor cells that histologically resembled STIC and
expressed the established molecular markers of STIC, including p53, Ki-67, and stathmin (Fig. 4E,
S5C) (5, 6, 12, 23). HT-29 colon adenocarcinoma cells were also capable of implanting in the
fallopian tube epithelium and could be distinguished by a lack of PAX8 immunoreactivity (Fig. S5D).
In addition, using a similar approach, we found that HGSOC spheroids were also capable of adhering
to ex vivo omental explants (Fig. S5E), but did not adhere to endometrial explants after extended
culture (data not shown).
To mechanistically understand the interactions between fallopian tube epithelial cells (FTEC) and
HGSOC cells, we established in vitro models of FTEC-cancer cell adhesion and epithelial clearance.
Human FTECs (22) expressing PAX8 and preserving tight junctions (β-catenin expression, Fig.
S6A/B) were co-cultured with HGSOC spheroids and adhesion measured. The cancer cells adhered
to a monolayer of primary fallopian tube epithelium within 15 minutes in a β1-integrin-dependent
manner (Fig. 4F/G, Fig. S6C) and cleared the FTEC and fully integrated in the monolayer within 12
hours (Fig. 4H). Combined, these in vitro and ex vivo experiments suggest that ovarian cancer cells
are capable of adhering to and integrating with fallopian tube epithelium, suggesting that a portion of
putative precursor STIC are, instead, metastatic mimics.
Discussion
We set out to study the dynamics of genomic alterations with the goal of understanding the
relationships of STIC to the metastatic trajectory of HGSOC. Although we were initially challenged by
the intrinsically low sample amounts of STIC, we show here that WES of low-input, in situ specimens
is feasible and can be integrated into established workflows. That this study was performed with
archival paraffin blocks indicates that the sources of samples used for analysis of core genomic
events or phylogenetic reconstruction can be expanded to paraffin blocks which are widely available.
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 9
Page 9 of 24
The laser-capture microdissection of the tumor compartment allowed the collection of pure tumor
samples, allowing us to make firm conclusions about genetic changes without the stromal
contamination observed in other studies (3, 9).
We find that multi-site sequencing is useful for identifying candidate driver genomic events, with
putative core mutations representing a minority of mutational events at any one site. In our study the
mutation rate and mutation signature, as well as the CNV rates of STIC and HGSOC were consistent
and unique to each patient. All samples had mutations at the TP53 locus, including all STIC lesions,
demonstrating that the patients examined here are representative of HGSOC (5, 24). Every patient
had very different genomic changes, consistent with the perception of HGSOC as a very
heterogeneous disease that is not easily defined by a specific mutational change. There were no
significant alterations between anatomic sites within a single patient, suggesting that the biologic
processes underlying genomic instability, both CNVs and SNVs, are established early during disease
progression. The extent and nature of mutations and CNVs is such that even “basal STIC” possess
the same genomic instability and all the features of invasive HGSOC. During the progression to a
disseminated HGSOC, the STIC have co-evolved with the tumor, thus increasing the extent of CNVs
and SNVs. Common core events include mutation of TP53, frequent amplification of CCNE1, and
deletion of DNA damage repair and signaling genes. In addition, we found a previously unappreciated
widespread (70-100%) and early loss of heterozygosity (LOH) at the TP53 locus. This is in stark
contrast to TP53 LOH rates in other cancers (15), indicating an exceptionally strong selective
advantage for loss of the wild-type TP53 allele in HGSOC.
Notably, we found evidence that a portion of STIC represent metastases to the fallopian tube
epithelium, rather than the origin of the tumor. Another study had considered the possibility of
metastasis to the fallopian tube from HGSOC and uterine cancers (12). Targeted sequencing of
multiple, anatomically distinct STIC in ovarian cancer patients has identified identical TP53 mutations
in these synchronous in situ lesions, suggesting that they may represent clonal metastases within the
fallopian tube (5). In the absence of germline TP53 mutation, the acquisition of identical TP53
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 10
Page 10 of 24
mutations in two synchronous STIC is highly unlikely. Intraepithelial metastasis is thought to also
occur in lung cancer, where cells metastasize to the bronchial epithelium (25). Although we found that
non-gynecologic cancers may metastasize to the fallopian tube, these implants do not gain
expression of FTEC markers and can be immunohistochemically differentiated from HGSOC. There
is also evidence that the fallopian tube epithelium is a receptive site for metastasis of non-gynecologic
cancers (19, 20).
The peritoneal cavity, including the fallopian tubes and ovaries, is a continuous system bathed in
peritoneal fluid, which may facilitate complex patterns of dissemination. In both cases of “STIC
metastasis” the omentum represented the most basal tumor site. The clinical presentation of primary
peritoneal carcinoma, in which HGSOC is detected primarily in non-ovarian anatomical sites (26),
suggests that the omentum and peritoneal mesothelium represents a microenvironment that fosters
the establishment and growth of early metastases (27, 28). Based on expression of molecular
markers and the lack of putative precursor lesions (26), it would be surprising for the peritoneal
mesothelium of the omentum to represent the precursor of HGSOC. Endosalpingiosis to the
omentum occurs frequently (15%) of women in an unselected cohort (29, 30). Normal oviductal tissue
displaced to the omentum or peritoneum (endosalpingiosis) could undergo transformation thus
mimicking an omental primary tumor or a primary peritoneal cancer with serous histology (30, 31).
Alternatively, it is possible that the STIC metastases either originated from a precursor lesion within
the fallopian tube or that a STIC precursor lesion colonized the peritoneum and later back-
metastasized to the tube (11).
The data presented herein may lead us to develop our perception of STIC further: STIC in
HGSOC could be primary or metastatic. Previous studies observed precursor lesions exclusively in
the fallopian tube of BRCA mutation carriers undergoing prophylactic salpingo-oophorectomy (32),
while our study focused on sporadic HGSOC. As clinical studies have begun to investigate the utility
and safety of salpingectomy in high-risk patients (33-35), it will be imperative to understand if
metastasis to the fallopian tube occurs in the context of germline BRCA mutations. Lastly, the
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 11
Page 11 of 24
frequent observation of STIC detected after neo-adjuvant treatment (occurring in 50% of all cases)
could represent a late metastasis to a chemoresistant niche (36). Therefore a better understanding of
the cross-talk between cell types unique to intraepithelial fallopian tube metastases could be both
relevant clinically and important biologically.
Materials and Methods
Surgical treatment
All patients had newly diagnosed advanced, metastatic high-grade serous ovarian carcinoma
(HGSOC) and were undergoing primary debulking surgery by a gynecologic oncologist (SDY, EL) at
the University of Chicago (Table S1). All tissues were collected with informed consent under
approved, University of Chicago IRB protocols and in accordance with the Declaration of Helsinki.
LCM and DNA extraction
10 µm sections of each tissue were cut onto PEN-MembraneSlides (Leica), deparaffinized with
xylenes, rehydrated through graded alcohols, and stained with hematoxylin. Tumor components from
each tissue were microdissected with a Leica LMD 6500 (up to 5 serial sections per sample). In
cases of bilateral ovarian involvement, tumor was microdissected from the ovary of the same laterality
as the STIC lesion. DNA was extracted with a QIAamp DNA FFPE Tissue Kit (Qiagen), with
proteinase K digestion extended to 12 hours and sequential elution of DNA in 20 µl volumes following
5 minute incubations.
Sequencing and alignment
Libraries were prepared per standard protocols (Agilent SureSelect Human All Exon v5) and
sequenced on an Illumina HiSeq 2500 ultra high-throughput sequencing system (100 bp, paired-end).
Sequence quality was assessed using FastQC v0.11.2. Adapters were then removed and overlapping
mates were merged using SeqPrep. Processed reads were then aligned to the human genome
(hg19) using Novoalign v3.02.07 and filtered to remove low quality alignments and PCR duplicates
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 12
Page 12 of 24
with sambamba v0.5.4 (37). Alignment metrics were gathered using the CalculateHsMetrics tool from
Picard v1.129 and the Agilent SureSelect target files. Filtered alignments were then refined as
suggested by the Broad Institute’s “Best Practices” (38) using GATK v3.4 (39).
SNV/Indel Analysis
Refined alignments were then used to detect somatic mutations across the various
combinations of normal (gDNA) and tumor samples within a patient. To reduce the number of false
positives, three somatic mutation detection (SMD) tools were used: MuTect v1.1.4 (40), VarScan2
v2.3.9 (41), and Virmid v1.2.0 (42). Important differences between these tools include 1) Virmid and
VarScan2 can detect loss of heterozygosity (LOH); 2) Virmid and VarScan2 can detect germline
mutations; and 3) only VarScan2 attempts to call indels.
All detected somatic variants (including indels) were filtered to remove low quality, low
coverage, and ambiguous genotype calls using in-house scripts (43). Filtered variants were then
annotated using Annovar (44) and further filtered to remove variants located in intergenic,
upstream/downstream, intronic, UTR5/3, or non-coding regions. Next, results across the 3 SMD tools
were combined and merged at loci where the alleles were concordant or the mutation was observed
in more than one anatomic site of the same patient. For one patient, manual review of TP53
sequencing alignments with the Integrated Genome Viewer was used to confirm mutation of TP53 at
all anatomic sites. To calculate mutational rates, per-locus coverage was estimated using GATK’s
DepthOfCoverage tool. Then, per-sample estimates of total target size were estimated by counting
the number of loci with both normal and tumor sample coverage ≥8×. Next, using exonic and splicing
somatic mutations, mutation rates were estimated for each tumor-normal combination.
To detect significant mutations, somatic variants detected by at least 2 SMDs or by MuTect, as
well as high-quality indels, were annotated by Oncotator (45) and converted to a single MAF file. The
MAF file was then processed by MutSigCV v1.4 (16) using the default settings and databases.
Mutations detected as significant in only a single patient were excluded. Mutational signatures were
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 13
Page 13 of 24
assessed by assigning each SNV to one of seven classes as follows: T>C (A>G and T>C); C>T (G>A
and C>T); C>G (G>C and C>G); T>G (A>C and T>G); T>A (A>T and T>A); C>A (G>T and C>A); and
indels (insertions and deletions) (10). Mutational classes, based on their distribution between
anatomic sites, were defined as follows: core mutations were shared by all four anatomic sites within
a patient; shared mutations were present in two or three anatomic sites within a patient; and private
mutations were detected in only a single anatomic site for a patient.
To assess germline mutation status of BRCA1/2 and other ovarian cancer susceptibility genes,
Virmid and VarScan2 calls were utilized. Germline variants were filtered to remove potential false
positives following the suggestions presented by the VarScan2 developers (41).
CNV Analysis
Refined alignments were scanned for copy number variations (CNVs) using VarScan2 (41) and
custom scripts based on a previously published method (46). Due to the high overlap in segments
between methods and less variability in the in-house method, we utilized the method introduced by
Lonigro et al (46), which we term the “MI Method”. First, per-target (exon) coverage was estimated
using GATK’s DepthOfCoverage tool (v3.4.0). Then, normalization was performed for each tumor-
normal pair. Briefly, targets with coverage less than 10 in the matched normal sample were excluded.
Then, per-target coverage in the tumor sample was divided by the per-target coverage in the matched
normal sample resulting in coverage ratios for each target. Coverage ratios are then globally
normalized by dividing each of them by the ratio of human mappings between the two samples
(tumor/normal) and log2 transforming. Finally, the overall median value is subtracted, resulting in a set
of log2-transformed coverage ratios with median zero for each tumor/normal matched pair. The
normalized values were then segmented using the R/bioconductoR package ”copynumber” v1.6.0
(47). Segmented CNV calls were used to extract regions with log2R greater than 0.2 or less than 0.2,
as performed with TCGA data, to extract the percentage of the genome that was amplified or deleted
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 14
Page 14 of 24
by anatomic site or patient. Copynumber segments were grouped by tissue (e.g., all STIC samples
were run together) and used as inputs for GISTIC v2.0.22 (18).
Tumor Phylogenetics
Somatic mutations (both synonymous and non-synonymous) were combined with high-
confidence LOH loci calls (>20× coverage, VarScan2) to generate a binary presence-absence matrix
of genomic characters for each anatomic site within each patient. Inclusion of both LOH and SNV
data lowers the likelihood of mutation reversion confounding phylogenetic analyses. Distance
matrices were calculated using Jaccard-Tanimoto similarity coefficients with 100 bootstrap replicates
and clustered using the unweighted pair group method with arithmetic mean (UPGMA) method to
generate maximum likelihood dendrograms using DendroUPGMA (48). Cophenetic correlation
coefficients were greater than 0.98 for all trees (49). Resulting dendrograms were plotted with the
Interactive Tree of Life interface (50).
Immunohistochemistry
5 µm formalin-fixed, paraffin-embedded tissue sections were deparaffinized with xylene and
rehydrated with a graded series of ethanol. Antigen retrieval was performed in 10 mM sodium citrate
buffer (pH 6) with 0.05% Tween 20 at 100oC. Samples were then incubated with 0.3% hydrogen
peroxide for 20 mins at RT and blocked with 2.5% normal horse serum (Vector Laboratories) for 1 hr
at RT. Primary antibodies (Stathmin, 1:200, Cell Signaling Technologies; Ki-67, 1:200, Thermo
Scientific; PAX8, 1:200, Cell Signaling Technologies; β-catenin, 1:200, BD Biosciences; E-cadherin,
1:200, BD Biosciences; pan-p53, 1:200, Calbiochem) in 1.25% normal horse serum/PBS were
incubated overnight at 4oC and visualized using the R.T.U VectaStain Kit and DAB (Vector
Laboratories) and counterstained with hematoxylin.
Immunofluorescence
Cells were fixed in 4% paraformaldehyde, permeabilized with 0.5% TritonX-100, and blocked
with 10% goat serum. Primary antibodies (PAX8, 1:200, Cell Signaling Technologies; β-catenin,
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 15
Page 15 of 24
1:200, BD Biosciences) were incubated overnight in 10% goat serum. Samples were probed with
fluorescent secondary antibodies (Thermo Scientific) and Hoechst (Invitrogen) for one hour before
washing and mounting with ProLong Gold. Images were collected on a Zeiss LSM 510 Meta Confocal
microscope and images processed with ImageJ.
Cell culture
HeyA8 (Gordon Mills, MD Anderson, Houston, TX; received June 2006), TYK-nu (Gottfried
Koneczny, University of California, Los Angeles; November 2014), and HT-29 (Marcus Peter,
Northwestern University, Chicago, IL; May 2009) cells were grown under recommended culture
conditions and genotyped to confirm their authenticity (IDEXX Bioresearch short tandem repeat
marker profiling every three months; all cell lines last validated January-July 2016). All cell lines were
mycoplasma-negative. Immortalized FT33-TAg FTEC cells were a gift from Dr. Ronnie Drapkin
(University of Pennsylvania; December 2014) and were cultured in 2% Ultroser G (Crescent
Chemical) in DMEM/F12 50/50 (Corning) (22).
Ex vivo metastasis assays
Normal fallopian tube, endometrial, and omental tissues were collected from patients with
benign gynecological conditions at the time of surgery. Fimbriae or 0.5 cm3 endometrial or omental
tissues were dissected and transferred into 500 µl of FTEC media, known to support the proliferation
and survival of primary fallopian tube epithelial cells (22). To each well, 5×104 HGSOC cells (TYK-nu
or HeyA8) were added. For some experiments, spheroids were labeled with CellTracker Green
(Thermo Scientific, 1:1000 dilution). Following 72 hrs of co-culture, fimbriae were fixed in 4%
formaldehyde, dehydrated through graded alcohols and xylenes, and embedded in paraffin blocks. 5
µm sections were cut for each tissue and processed for IHC and immunohistochemistry (p53, Ki-67,
and stathmin).
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 16
Page 16 of 24
Isolation of primary HGSOC spheroids.
Ascites fluid from HGSOC patients was passed through a 40 µm nylon mesh and washed with
PBS to remove single cells. Isolated spheroids were maintained in non-adherent plates (Corning).
Isolation of primary fallopian tube epithelial cells.
Fallopian tubes were collected from patients with benign gynecological conditions. Primary
fallopian tube secretory epithelial cells (FTECs) were extracted and cultured as previously described
(22).
In vitro fallopian tube adhesion assay
96-well plates were coated with fibronectin (0.1 µg/ml). Immortalized FTECs (FT33-TAg cells)
were plated at 1×104 cells per well and grown to confluency (48 hrs). Ovarian cancer cells were
labeled with CellTracker Green (1:1000) and added to wells of plate (5×104 cells per well) and
incubated for 15 mins (37oC, 5% CO2). For β1-inhibitor experiments, cells were treated in suspension
with AIIB2 blocking antibody or antibody control (5 µg/ml) for 30 mins. Alternatively, 5×104 HGSOC
cells (TYK-nu or HeyA8) were plated in a 96 well plate and allowed to form spheroids for 24 hrs
before being labeled with CellTracker Green (1:1000) and transferred to FTEC plates as for single
cell suspensions. Plates were washed once with PBS, fixed in 4% paraformaldehyde, and imaged
with a Zeiss Axio Observer.A1 with AxioVision software (Rel 4.8). Cells were counted (single-cells) or
total area covered by cells quantified (spheroids) to quantify adhesion with ImageJ.
In vitro fallopian tube epithelial clearance assay
The method was adapted from Iwancki et al (51). Glass bottom 8-chamber slides were coated
with 0.1 µg/ml fibronectin. Primary FTECs were directly plated into each well (2×104 cells/well) at
passage zero and grown to 100% confluency (72 hrs) before labeling with CellTracker Green
(1:1000). In parallel, 5×103 TYK-nu cells were plated in a non-adherent 96-well plate (Corning) to
form spheroids for 72 hrs. Spheroids were directly transferred from 96-well plate to the FTEC
monolayer and incubated for 12 hrs before fixation and staining for actin (AlexaFluor 647 phalloidin,
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 17
Page 17 of 24
Thermo Scientific). Images were collected on a Zeiss LSM 510 Meta Confocal microscope and
images processed with ImageJ.
Authors’ Contributions
Conception and design: M.A. Eckert, E. Lengyel
Development of methodology: M.A. Eckert, K.M. Hernandez, J. Andrade, S.L. Volchenboum, P.
Faber
Acquisition of data: M.A. Eckert, S. Pan, P. Faber, A. Montag, R. Lastra
Bioinformatics: K.M. Hernandez, S.L. Volchenboum, J. Andrade
Sample acquisition, pathology review: S.D. Yamada, E. Lengyel, R. Lastra, A. Montag
Writing of manuscript: M.A. Eckert, K.M. Hernandez, M.E. Peter, E. Lengyel
Editing of the manuscript: M.A. Eckert, S.L. Volchenboum, SD Yamada, E. Lengyel
Study supervision: M.A. Eckert, E. Lengyel
Acknowledgements
We thank the Harris Family Foundation for their generous support. We thank Drs. H.A. Kenny,
M. Curtis, K. Watters, and A. Mukherjee from the University of Chicago ovarian cancer laboratory for
helpful discussions. We are very thankful to Gail Isenberg, University of Chicago, for carefully editing
the manuscript.
References
1. Lengyel E. Ovarian cancer development and metastasis. Am J Pathol. 2010;177(3):1053-64.
2. Norquist BM, Harrell MI, Brady MF, Walsh T, Lee MK, Gulsuner S, et al. Inherited Mutations in
Women With Ovarian Carcinoma. JAMA oncology. 2015:1-9.
3. Patch AM, Christie EL, Etemadmoghadam D, Garsed DW, George J, Fereday S, et al. Whole-
genome characterization of chemoresistant ovarian cancer. Nature. 2015;521(7553):489-94.
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 18
Page 18 of 24
4. Piek JM, van Diest PJ, Zweemer RP, Jansen JW, Poort-Keesom RJ, Menko FH, et al.
Dysplastic changes in prophylactically removed fallopian tubes of women predisposed to developing
ovarian cancer. Journal of Pathology. 2001;195(4):451-6.
5. Kuhn E, Kurman RJ, Vang R, Sehdev AS, Han G, Soslow R, et al. TP53 mutations in serous
tubal intraepithelial carcinoma and concurrent pelvic high-grade serous carcinoma-evidence
supporting the clonal relationship of the two lesions. Journal of Pathology. 2012;226:421-6.
6. Lee Y, Miron A, Drapkin R, Nucci MR, Medeiros F, Saleemuddin A, et al. A candidate
precursor to serous carcinoma that originates in the distal fallopian tube. Journal of Pathology.
2007;211:26-35.
7. Perets R, Wyant GA, Muto KW, Bijron JG, Poole BB, Chin KT, et al. Transformation of the
fallopian tube secretory epithelium leads to high-grade serous ovarian cancer in Brca; Tp53; Pten
models. Cancer Cell. 2013;24:751-65.
8. Fearon ER, Vogelstein B. A genetic model for colorectal tumorigenesis. Cell. 1990;61(5):759-
67.
9. The Cancer Genome Atlas N. Integrated genomic analyses of ovarian carcinoma. Nature.
2011;474:609-15.
10. Ciriello G, Miller ML, Aksoy BA, Senbabaoglu Y, Schultz N, Sander C. Emerging landscape of
oncogenic signatures across human cancers. Nat Genet. 2013;45(10):1127-33.
11. Yachida S, Jones S, Bozic I, Antal T, Leary R, Fu B, et al. Distant metastasis occurs late
during the genetic evolution of pancreatic cancer. Nature. 2010;467(7319):1114-7.
12. McDaniel AS, Stall JN, Hovelson DH, Cani AK, Liu CJ, Tomlins SA, et al. Next-Generation
Sequencing of Tubal Intraepithelial Carcinomas. JAMA oncology. 2015;1(8):1128-32.
13. Schwarz RF, Ng CK, Cooke SL, Newman S, Temple J, Piskorz AM, et al. Spatial and temporal
heterogeneity in high-grade serous ovarian cancer: a phylogenetic analysis. PLoS Med.
2015;12(2):e1001789.
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 19
Page 19 of 24
14. McPherson A, Roth A, Laks E, Masud T, Bashashati A, Zhang AW, et al. Divergent modes of
clonal spread and intraperitoneal mixing in high-grade serous ovarian cancer. Nat Genet.
2016;48(7):758-67.
15. Kandoth C, McLellan MD, Vandin F, Ye K, Niu B, Lu C, et al. Mutational landscape and
significance across 12 major cancer types. Nature. 2013;502(7471):333-9.
16. Lawrence MS, Stojanov P, Polak P, Kryukov GV, Cibulskis K, Sivachenko A, et al. Mutational
heterogeneity in cancer and the search for new cancer-associated genes. Nature.
2013;499(7457):214-8.
17. George J, Alsop K, Etemadmoghadam D, Hondow H, Mikeska T, Dobrovic A, et al.
Nonequivalent gene expression and copy number alterations in high-grade serous ovarian cancers
with BRCA1 and BRCA2 mutations. Clin Cancer Res. 2013;19(13):3474-84.
18. Mermel CH, Schumacher SE, Hill B, Meyerson ML, Beroukhim R, Getz G. GISTIC2.0
facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in
human cancers. Genome Biol. 2011;12(4):R41.
19. Stewart CJ, Leung YC, Whitehouse A. Fallopian tube metastases of non-gynaecological origin:
a series of 20 cases emphasizing patterns of involvement including intra-epithelial spread.
Histopathology. 2012;60(6B):E106-14.
20. Rabban JT, Vohra P, Zaloudek CJ. Nongynecologic metastases to fallopian tube mucosa: a
potential mimic of tubal high-grade serous carcinoma and benign tubal mucinous metaplasia or
nonmucinous hyperplasia. Am J Surg Pathol. 2015;39(1):35-51.
21. Bijron JG, Seldenrijk CA, Zweemer RP, Lange JG, Verheijen RH, van Diest PJ. Fallopian tube
intraluminal tumor spread from noninvasive precursor lesions: a novel metastatic route in early pelvic
carcinogenesis. Am J Surg Pathol. 2013;37(8):1123-30.
22. Karst AM, Drapkin R. Primary culture and immortalization of human fallopian tube secretory
epithelial cells. Nat Protoc. 2012;7:1755-64.
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 20
Page 20 of 24
23. Karst AM, Levanon K, Duraisamy S, Liu JF, Hirsch MS, Hecht JL, et al. Stathmin 1, a marker
of PI3K pathway activation and regulator of microtubule dynamics, is expressed in early pelvic serous
carcinomas. Gynecol Oncol. 2011;123(1):5-12.
24. Ahmet AA, Etemadmoghadam D, Temple J, Lynch AG, Riad M, Sharma R, et al. Driver
mutations in TP53 are ubiquitous in high grade serous carcinoma of the ovary. Journal of Pathology.
2010;221(1):49-56.
25. Kiryu T, Hoshi H, Matsui E, Iwata H, Kokubo M, Shimokawa K, et al.
Endotracheal/endobronchial metastases : clinicopathologic study with special reference to
developmental modes. Chest. 2001;119(3):768-75.
26. Nik NN, Vang R, Shih Ie M, Kurman RJ. Origin and pathogenesis of pelvic (ovarian, tubal, and
primary peritoneal) serous carcinoma. Annu Rev Pathol. 2014;9:27-45.
27. Kenny HA, Kaur S, Coussens LM, Lengyel E. The initial steps of ovarian cancer cell
metastasis are mediated by MMP-2 cleavage of vitronectin and fibronectin. J Clin Invest.
2008;118(4):1367-79.
28. Nieman KM, Kenny HA, Penicka CV, Ladanyi A, Buell-Gutbrod R, Zillhardt M, et al. Adipocytes
promote ovarian cancer metastasis and provide energy for rapid tumor growth. Nat Med.
2011;17(11):1498-503.
29. Zinsser KR, Wheeler JE. Endosalpingiosis in the omentum: a study of autopsy and surgical
material. Am J Surg Pathol. 1982;6(2):109-17.
30. Prentice L, Stewart A, Mohiuddin S, Johnson NP. What is endosalpingiosis? Fertil Steril.
2012;98(4):942-7.
31. McCoubrey A, Houghton O, McCallion K, McCluggage WG. Serous adenocarcinoma of the
sigmoid mesentery arising in cystic endosalpingiosis. J Clin Pathol. 2005;58(11):1221-3.
32. Perets R, Drapkin R. It's Totally Tubular....Riding The New Wave of Ovarian Cancer Research.
Cancer Res. 2016;76(1):10-7.
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 21
Page 21 of 24
33. Falconer H, Yin L, Gronberg H, Altman D. Ovarian cancer risk after salpingectomy: a
nationwide population-based study. J Natl Cancer Inst. 2015;107(2).
34. Daly MB, Dresher CW, Yates MS, Jeter JM, Karlan BY, Alberts DS, et al. Salpingectomy as a
means to reduce ovarian cancer risk. Cancer Prev Res (Phila). 2015;8(5):342-8.
35. Przybycin CG, Kurman RJ, Ronnett BM, Shih Ie M, Vang R. Are all pelvic (nonuterine) serous
carcinomas of tubal origin? Am J Surg Pathol. 2010;34(10):1407-16.
36. Colon E, Carlson JW. Evaluation of the fallopian tubes after neoadjuvant chemotherapy:
Persistence of serous tubal intraepithelial carcinoma. Int J Gynecol Pathol. 2014;00:DOI
10.1097/PGP.0b013e3182a142c2.
37. Tarasov A, Vilella AJ, Cuppen E, Nijman IJ, Prins P. Sambamba: fast processing of NGS
alignment formats. Bioinformatics. 2015;31(12):2032-4.
38. Van der Auwera GA, Carneiro MO, Hartl C, Poplin R, Del Angel G, Levy-Moonshine A, et al.
From FastQ data to high confidence variant calls: the Genome Analysis Toolkit best practices
pipeline. Curr Protoc Bioinformatics. 2013;43:11 0 1-33.
39. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The Genome
Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.
Genome Res. 2010;20(9):1297-303.
40. Cibulskis K, Lawrence MS, Carter SL, Sivachenko A, Jaffe D, Sougnez C, et al. Sensitive
detection of somatic point mutations in impure and heterogeneous cancer samples. Nat Biotechnol.
2013;31(3):213-9.
41. Koboldt DC, Zhang Q, Larson DE, Shen D, McLellan MD, Lin L, et al. VarScan 2: somatic
mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res.
2012;22(3):568-76.
42. Kim S, Jeong K, Bhutani K, Lee J, Patel A, Scott E, et al. Virmid: accurate detection of somatic
mutations with sample impurity inference. Genome Biol. 2013;14(8):R90.
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 22
Page 22 of 24
43. Bao R, Hernandez K, Huang L, Kang W, Bartom E, Onel K, et al. ExScalibur: A High-
Performance Cloud-Enabled Suite for Whole Exome Germline and Somatic Mutation Identification.
PLoS One. 2015;10(8):e0135800.
44. Wang K, Li M, Hakonarson H. ANNOVAR: functional annotation of genetic variants from high-
throughput sequencing data. Nucleic Acids Res. 2010;38(16):e164.
45. Ramos AH, Lichtenstein L, Gupta M, Lawrence MS, Pugh TJ, Saksena G, et al. Oncotator:
cancer variant annotation tool. Hum Mutat. 2015;36(4):E2423-9.
46. Lonigro RJ, Grasso CS, Robinson DR, Jing X, Wu YM, Cao X, et al. Detection of somatic copy
number alterations in cancer using targeted exome capture sequencing. Neoplasia.
2011;13(11):1019-25.
47. Nilsen G, Liestol K, Van Loo P, Moen Vollan HK, Eide MB, Rueda OM, et al. Copynumber:
Efficient algorithms for single- and multi-track copy number segmentation. BMC Genomics.
2012;13:591.
48. Garcia-Vallve S, Palau J, Romeu A. Horizontal gene transfer in glycosyl hydrolases inferred
from codon usage in Escherichia coli and Bacillus subtilis. Mol Biol Evol. 1999;16(9):1125-34.
49. Sokal RR, Rohlf FJ. The Comparison of Dendrograms by Objective Methods. Taxon.
1962;11(2):33-40.
50. Letunic I, Bork P. Interactive Tree Of Life (iTOL): an online tool for phylogenetic tree display
and annotation. Bioinformatics. 2007;23(1):127-8.
51. Iwanicki M, Davidowitz RA, Ng MR, Besser A, Muranen T, Merritt M, et al. Ovarian cancer
spheroids use myosin-generated force to clear the mesothelium. Cancer Discov. 2011;1(7):144-57.
Figure Legends
Figure 1. High grade serous ovarian cancer (HGSOC) mutational processes are established
early and are patient specific. A) Representative p53 IHC and H&E images of the hypothetical
progression series of HGSOC in a patient with STIC, and invasive lesions in the fallopian tube, ovary,
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 23
Page 23 of 24
and abdominal omentum. B) Laser capture microdissection of the tumor compartment from omentum.
C) Workflow to elucidate the spatiotemporal pattern of genomic alterations in HGSOC to capture
tumor phylogenies and core events. D) Frequency of SNV by anatomic site and patient reveal that
mutational burden is patient-specific rather than determined by anatomic tumor location. Average
mutational burden across the patient cohort is approximately 1 somatic mutation per megabase (50
mutations total per tumor sample). E) Identification of an age-related mutational signature class
characterized by high rates of C>T substitutions in all samples of the patient cohort, reveals a
comparable mutational process underlying disease progression in all patients examined. STIC =
serous tubal intraepithelial carcinoma; FT = invasive fallopian tube tumor; OV = invasive ovarian
tumor; OM = omental metastasis.; SNV = single nucleotide variants.
Figure 2. Core, recurrent SNVs in HGSOC are restricted to TP53 mutations. A) Oncoprint of all
non-synonymous mutations in patient 539 reveals mutation of TP53 and distribution of mutations into
core, shared, and private classes. B) A minority of SNVs and insertions/deletions (indels) are present
in all samples (“core”). The majority of mutations are shared between 2-3 anatomic sites (“shared”),
or present in only one site (“private”) C) Euler diagram of all non-synonymous SNVs and indels. Core
SNVs/indels present in all anatomic sites are highlighted in red.
Figure 3. Genomic instability is a core feature of ovarian cancer that frequently involves DNA-
damage repair genes. A) Frequency plot of copy number variations (CNVs) across all patients and
all four anatomic sites. Annotated arm level events were also identified as significant in the TCGA
analysis of HGSOC. For all plots in Figure 3, amplifications are red and deletions are blue. B)
Genomic aberration plot of CNVs across all anatomic sites and patients imply high degree of genomic
instability in all anatomic sites. Chromosome numbers are indicated on margin. Amplifications are
red; deletions are blue. C) CNV status of significantly altered DNA repair pathway genes (from
REPAIRtoire) reveals common deletion of DNA damage response and repair genes known to be
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 24
Page 24 of 24
involved in HGSOC. Amplifications are red; deletions are blue. D/E) Extent of genomic instability is
patient-specific (D) and does not vary by anatomic site (E). F) GISTIC identification and analysis of
significantly altered genes identifies conserved core amplifications and deletions. Number of
amplifications in red and deletions in blue.
Figure 4. Phylogenetic analyses of ovarian cancer progression reveal diverse metastatic
processes and evidence of intraepithelial metastasis. A) Phylogenetic trees of each patient with
key genomic events (SNVs, Indels, CNVs) that characterize each branching event annotated (C
(“core”), 1, or 2). Deletions are in blue. B) Representative p53 staining of a “STIC Metastasis” in
patient #563 (left), as well as intraluminal HGSOC spheroids within the same fallopian tube (right). C)
P53 staining of intraluminal HGSOC spheroids adhering to the epithelium of the fallopian tube (patient
530) D) Human fallopian tube fimbriae and spheroids that were co-cultured. E) Co-culture of human
fallopian tube explants with TYK-nu ovarian cancer spheroids mimic STICs with clearance of normal
epithelium and implantation of tumor cells expressing Ki-67 and nuclear p53. F/G) Adhesion of
fluorescently-labeled HGSOC cells (green) to primary FTEC monolayer (brightfield) after 15 minutes.
Pretreatment with β1-integrin blocking antibody (AIIB2) attenuated adhesion of HeyA8 and TYK-nu
cells to FTEC monolayer. H) TYK-nu ovarian cancer spheroids (phalloidin only) clear a primary
human fallopian tube epithelial monolayer (phalloidin and CellTracker Green) after 12 hours.
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 25
Eckert et al. Figure 1.
A B STIC p53
FT Ov Om Before LCM After LCM Captured Tumor
D SNVs by Anatomic Site SNVs by Patient
E
C
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 26
Eckert et al. Figure 2
B C
A
Identification of Core SNVs
Oncoprint of Non-Synonymous Mutations
TP53
Core Shared Private
539
Missense Indel Nonsense
Mutational Class Distribution
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 27
Eckert et al. Figure 3. A B
C
D E F CNVs by Anatomic Site CNVs by Patient Identification of Core CNVs
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 28
Eckert et al. Figure 4.
B
563 STIC
E
TYK
-nu
OvC
a
H&E Ki-67 p53
A
C
1o human FT
H FTECs Phalloidin Merge
Ctr
l Ig
G
β1 I
nhib
itor
I
II
Inset
F G HeyA8 + FTECs
III
D
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607
Page 29
Published OnlineFirst October 7, 2016.Cancer Discov Mark A. Eckert, Shawn Pan, Kyle M. Hernandez, et al. the Fallopian TubeMetastatic Trajectories Including Intraepithelial Metastasis to Genomics of Ovarian Cancer Progression Reveals Diverse
Updated version
10.1158/2159-8290.CD-16-0607doi:
Access the most recent version of this article at:
Material
Supplementary
http://cancerdiscovery.aacrjournals.org/content/suppl/2016/10/07/2159-8290.CD-16-0607.DC1
Access the most recent supplemental material at:
Manuscript
Authoredited. Author manuscripts have been peer reviewed and accepted for publication but have not yet been
E-mail alerts related to this article or journal.Sign up to receive free email-alerts
Subscriptions
Reprints and
[email protected] at
To order reprints of this article or to subscribe to the journal, contact the AACR Publications
Permissions
Rightslink site. Click on "Request Permissions" which will take you to the Copyright Clearance Center's (CCC)
.http://cancerdiscovery.aacrjournals.org/content/early/2016/10/07/2159-8290.CD-16-0607To request permission to re-use all or part of this article, use this link
Research. on August 25, 2020. © 2016 American Association for Cancercancerdiscovery.aacrjournals.org Downloaded from
Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Author Manuscript Published OnlineFirst on October 7, 2016; DOI: 10.1158/2159-8290.CD-16-0607