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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

http://cancerdiscovery.aacrjournals.org/

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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




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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




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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).




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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).




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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




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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




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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.




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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




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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




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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




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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




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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




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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,




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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).




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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,




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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.

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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,




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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




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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.




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




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




Eckert et al. Figure 3. A B

C

D E F CNVs by Anatomic Site CNVs by Patient Identification of Core CNVs




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




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

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