Protocol for the characterization of the pancreatic tumor microenvironment using organoid-derived mouse models and single-nuclei RNA sequencing.

Single-nuclei RNA sequencing (snRNA-seq) allows for obtaining gene expression profiles from frozen or hard-to-dissociate tissues at the single-nuclei level. Here, we describe a protocol to obtain snRNA-seq data of pancreatic tumors from orthotopically grafted organoid-derived mouse models. We provide details on the establishment of these mouse models, the isolation of single nuclei from pancreatic tumors, and the analysis of the snRNA-seq datasets. For complete details on the use and execution of this protocol, please refer to Mucciolo et al.1.

scAbsolute: measuring single-cell ploidy and replication status.

Cancer cells often exhibit DNA copy number aberrations and can vary widely in their ploidy. Correct estimation of the ploidy of single-cell genomes is paramount for downstream analysis. Based only on single-cell DNA sequencing information, scAbsolute achieves accurate and unbiased measurement of single-cell ploidy and replication status, including whole-genome duplications. We demonstrate scAbsolute's capabilities using experimental cell multiplets, a FUCCI cell cycle expression system, and a benchmark against state-of-the-art methods. scAbsolute provides a robust foundation for single-cell DNA sequencing analysis across different technologies and has the potential to enable improvements in a number of downstream analyses.

EGFR-activated myofibroblasts promote metastasis of pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis. Cancer-associated fibroblasts (CAFs) are recognized potential therapeutic targets, but poor understanding of these heterogeneous cell populations has limited the development of effective treatment strategies. We previously identified transforming growth factor beta (TGF-ß) as a main driver of myofibroblastic CAFs (myCAFs). Here, we show that epidermal growth factor receptor/Erb-B2 receptor (EGFR/ERBB2) signaling is induced by TGF-ß in myCAFs through an autocrine process mediated by amphiregulin. Inhibition of this EGFR/ERBB2-signaling network in PDAC organoid-derived cultures and mouse models differentially impacts distinct CAF subtypes, providing insights into mechanisms underpinning their heterogeneity. Remarkably, EGFR-activated myCAFs promote PDAC metastasis in mice, unmasking functional significance in myCAF heterogeneity. Finally, analyses of other cancer datasets suggest that these processes might operate in other malignancies. These data provide functional relevance to myCAF heterogeneity and identify a candidate target for preventing tumor invasion in PDAC.

Integrated radiogenomics models predict response to neoadjuvant chemotherapy in high grade serous ovarian cancer.

High grade serous ovarian carcinoma (HGSOC) is a highly heterogeneous disease that typically presents at an advanced, metastatic state. The multi-scale complexity of HGSOC is a major obstacle to predicting response to neoadjuvant chemotherapy (NACT) and understanding critical determinants of response. Here we present a framework to predict the response of HGSOC patients to NACT integrating baseline clinical, blood-based, and radiomic biomarkers extracted from all primary and metastatic lesions. We use an ensemble machine learning model trained to predict the change in total disease volume using data obtained at diagnosis (n = 72). The model is validated in an internal hold-out cohort (n = 20) and an independent external patient cohort (n = 42). In the external cohort the integrated radiomics model reduces the prediction error by 8% with respect to the clinical model, achieving an AUC of 0.78 for RECIST 1.1 classification compared to 0.47 for the clinical model. Our results emphasize the value of including radiomics data in integrative models of treatment response and provide methods for developing new biomarker-based clinical trials of NACT in HGSOC.

Molecular landscape and functional characterization of centrosome amplification in ovarian cancer.

High-grade serous ovarian carcinoma (HGSOC) is characterised by poor outcome and extreme chromosome instability (CIN). Therapies targeting centrosome amplification (CA), a key mediator of chromosome missegregation, may have significant clinical utility in HGSOC. However, the prevalence of CA in HGSOC, its relationship to genomic biomarkers of CIN and its potential impact on therapeutic response have not been defined. Using high-throughput multi-regional microscopy on 287 clinical HGSOC tissues and 73 cell lines models, here we show that CA through centriole overduplication is a highly recurrent and heterogeneous feature of HGSOC and strongly associated with CIN and genome subclonality. Cell-based studies showed that high-prevalence CA is phenocopied in ovarian cancer cell lines, and that high CA is associated with increased multi-treatment resistance; most notably to paclitaxel, the commonest treatment used in HGSOC. CA in HGSOC may therefore present a potential driver of tumour evolution and a powerful biomarker for response to standard-of-care treatment.

The copy number and mutational landscape of recurrent ovarian high-grade serous carcinoma.

The drivers of recurrence and resistance in ovarian high grade serous carcinoma remain unclear. We investigate the acquisition of resistance by collecting tumour biopsies from a cohort of 276 women with relapsed ovarian high grade serous carcinoma in the BriTROC-1 study. Panel sequencing shows close concordance between diagnosis and relapse, with only four discordant cases. There is also very strong concordance in copy number between diagnosis and relapse, with no significant difference in purity, ploidy or focal somatic copy number alterations, even when stratified by platinum sensitivity or prior chemotherapy lines. Copy number signatures are strongly correlated with immune cell infiltration, whilst diagnosis samples from patients with primary platinum resistance have increased rates of CCNE1 and KRAS amplification and copy number signature 1 exposure. Our data show that the ovarian high grade serous carcinoma genome is remarkably stable between diagnosis and relapse and acquired chemotherapy resistance does not select for common copy number drivers.

Identification of Tissue-Resident Natural Killer and T Lymphocytes with Anti-Tumor Properties in Ascites of Ovarian Cancer Patients.

Women with ovarian cancer have limited therapy options, with immunotherapy being unsatisfactory for a large group of patients. Tumor cells spread from the ovary or the fallopian tube into the abdominal cavity, which is commonly accompanied with massive ascites production. The ascites represents a unique peritoneal liquid tumor microenvironment with the presence of both tumor and immune cells, including cytotoxic lymphocytes. We characterized lymphocytes in ascites from patients with high-grade serous ovarian cancer. Our data reveal the presence of NK and CD8+ T lymphocytes expressing CD103 and CD49a, which are markers of tissue residency. Moreover, these cells express high levels of the inhibitory NKG2A receptor, with the highest expression level detected on tissue-resident NK cells. Lymphocytes with these features were also present at the primary tumor site. Functional assays showed that tissue-resident NK cells in ascites are highly responsive towards ovarian tumor cells. Similar results were observed in an in vivo mouse model, in which tissue-resident NK and CD8+ T cells were detected in the peritoneal fluid upon tumor growth. Together, our data reveal the presence of highly functional lymphocyte populations that may be targeted to improve immunotherapy for patients with ovarian cancer.

High-grade serous ovarian carcinoma organoids as models of chromosomal instability.

High-grade serous ovarian carcinoma (HGSOC) is the most genomically complex cancer, characterized by ubiquitous TP53 mutation, profound chromosomal instability, and heterogeneity. The mutational processes driving chromosomal instability in HGSOC can be distinguished by specific copy number signatures. To develop clinically relevant models of these mutational processes we derived 15 continuous HGSOC patient-derived organoids (PDOs) and characterized them using bulk transcriptomic, bulk genomic, single-cell genomic, and drug sensitivity assays. We show that HGSOC PDOs comprise communities of different clonal populations and represent models of different causes of chromosomal instability including homologous recombination deficiency, chromothripsis, tandem-duplicator phenotype, and whole genome duplication. We also show that these PDOs can be used as exploratory tools to study transcriptional effects of copy number alterations as well as compound-sensitivity tests. In summary, HGSOC PDO cultures provide validated genomic models for studies of specific mutational processes and precision therapeutics.

Profiling the immune landscape in mucinous ovarian carcinoma.

OBJECTIVE: Mucinous ovarian carcinoma (MOC) is a rare histotype of ovarian cancer, with low response rates to standard chemotherapy, and very poor survival for patients diagnosed at advanced stage. There is a limited understanding of the MOC immune landscape, and consequently whether immune checkpoint inhibitors could be considered for a subset of patients. METHODS: We performed multicolor immunohistochemistry (IHC) and immunofluorescence (IF) on tissue microarrays in a cohort of 126 MOC patients. Cell densities were calculated in the epithelial and stromal components for tumor-associated macrophages (CD68+/PD-L1+, CD68+/PD-L1-), T cells (CD3+/CD8-, CD3+/CD8+), putative T-regulatory cells (Tregs, FOXP3+), B cells (CD20+/CD79A+), plasma cells (CD20-/CD79a+), and PD-L1+ and PD-1+ cells, and compared these values with clinical factors. Univariate and multivariable Cox Proportional Hazards assessed overall survival. Unsupervised k-means clustering identified patient subsets with common patterns of immune cell infiltration. RESULTS: Mean densities of PD1+ cells, PD-L1- macrophages, CD4+ and CD8+ T cells, and FOXP3+ Tregs were higher in the stroma compared to the epithelium. Tumors from advanced (Stage III/IV) MOC had greater epithelial infiltration of PD-L1- macrophages, and fewer PD-L1+ macrophages compared with Stage I/II cancers (p = 0.004 and p = 0.014 respectively). Patients with high epithelial density of FOXP3+ cells, CD8+/FOXP3+ cells, or PD-L1- macrophages, had poorer survival, and high epithelial CD79a + plasma cells conferred better survival, all upon univariate analysis only. Clustering showed that most MOC (86%) had an immune depleted (cold) phenotype, with only a small proportion (11/76,14%) considered immune inflamed (hot) based on T cell and PD-L1 infiltrates. CONCLUSION: In summary, MOCs are mostly immunogenically 'cold', suggesting they may have limited response to current immunotherapies.

The genomic and immune landscape of long-term survivors of high-grade serous ovarian cancer.

Fewer than half of all patients with advanced-stage high-grade serous ovarian cancers (HGSCs) survive more than five years after diagnosis, but those who have an exceptionally long survival could provide insights into tumor biology and therapeutic approaches. We analyzed 60 patients with advanced-stage HGSC who survived more than 10 years after diagnosis using whole-genome sequencing, transcriptome and methylome profiling of their primary tumor samples, comparing this data to 66 short- or moderate-term survivors. Tumors of long-term survivors were more likely to have multiple alterations in genes associated with DNA repair and more frequent somatic variants resulting in an increased predicted neoantigen load. Patients clustered into survival groups based on genomic and immune cell signatures, including three subsets of patients with BRCA1 alterations with distinctly different outcomes. Specific combinations of germline and somatic gene alterations, tumor cell phenotypes and differential immune responses appear to contribute to long-term survival in HGSC.

Clonal somatic copy number altered driver events inform drug sensitivity in high-grade serous ovarian cancer.

Chromosomal instability is a major challenge to patient stratification and targeted drug development for high-grade serous ovarian carcinoma (HGSOC). Here we show that somatic copy number alterations (SCNAs) in frequently amplified HGSOC cancer genes significantly correlate with gene expression and methylation status. We identify five prevalent clonal driver SCNAs (chromosomal amplifications encompassing MYC, PIK3CA, CCNE1, KRAS and TERT) from multi-regional HGSOC data and reason that their strong selection should prioritise them as key biomarkers for targeted therapies. We use primary HGSOC spheroid models to test interactions between in vitro targeted therapy and SCNAs. MYC chromosomal copy number is associated with in-vitro and clinical response to paclitaxel and in-vitro response to mTORC1/2 inhibition. Activation of the mTOR survival pathway in the context of MYC-amplified HGSOC is statistically associated with increased prevalence of SCNAs in genes from the PI3K pathway. Co-occurrence of amplifications in MYC and genes from the PI3K pathway is independently observed in squamous lung cancer and triple negative breast cancer. In this work, we show that identifying co-occurrence of clonal driver SCNA genes could be used to tailor therapeutics for precision medicine.

Molecular Subclasses of Clear Cell Ovarian Carcinoma and Their Impact on Disease Behavior and Outcomes.

PURPOSE: To identify molecular subclasses of clear cell ovarian carcinoma (CCOC) and assess their impact on clinical presentation and outcomes. EXPERIMENTAL DESIGN: We profiled 421 primary CCOCs that passed quality control using a targeted deep sequencing panel of 163 putative CCOC driver genes and whole transcriptome sequencing of 211 of these tumors. Molecularly defined subgroups were identified and tested for association with clinical characteristics and overall survival. RESULTS: We detected a putative somatic driver mutation in at least one candidate gene in 95% (401/421) of CCOC tumors including ARID1A (in 49% of tumors), PIK3CA (49%), TERT (20%), and TP53 (16%). Clustering of cancer driver mutations and RNA expression converged upon two distinct subclasses of CCOC. The first was dominated by ARID1A-mutated tumors with enriched expression of canonical CCOC genes and markers of platinum resistance; the second was largely comprised of tumors with TP53 mutations and enriched for the expression of genes involved in extracellular matrix organization and mesenchymal differentiation. Compared with the ARID1A-mutated group, women with TP53-mutated tumors were more likely to have advanced-stage disease, no antecedent history of endometriosis, and poorer survival, driven by their advanced stage at presentation. In women with ARID1A-mutated tumors, there was a trend toward a lower rate of response to first-line platinum-based therapy. CONCLUSIONS: Our study suggests that CCOC consists of two distinct molecular subclasses with distinct clinical presentation and outcomes, with potential relevance to both traditional and experimental therapy responsiveness. See related commentary by Lheureux, p. 4838.

The Genomic Landscape of Early-Stage Ovarian High-Grade Serous Carcinoma.

PURPOSE: Ovarian high-grade serous carcinoma (HGSC) is usually diagnosed at late stage. We investigated whether late-stage HGSC has unique genomic characteristics consistent with acquisition of evolutionary advantage compared with early-stage tumors. EXPERIMENTAL DESIGN: We performed targeted next-generation sequencing and shallow whole-genome sequencing (sWGS) on pretreatment samples from 43 patients with FIGO stage I-IIA HGSC to investigate somatic mutations and copy-number (CN) alterations (SCNA). We compared results to pretreatment samples from 52 patients with stage IIIC/IV HGSC from the BriTROC-1 study. RESULTS: Age of diagnosis did not differ between early-stage and late-stage patients (median 61.3 years vs. 62.3 years, respectively). TP53 mutations were near-universal in both cohorts (89% early-stage, 100% late-stage), and there were no significant differences in the rates of other somatic mutations, including BRCA1 and BRCA2. We also did not observe cohort-specific focal SCNA that could explain biological behavior. However, ploidy was higher in late-stage (median, 3.0) than early-stage (median, 1.9) samples. CN signature exposures were significantly different between cohorts, with greater relative signature 3 exposure in early-stage and greater signature 4 in late-stage. Unsupervised clustering based on CN signatures identified three clusters that were prognostic. CONCLUSIONS: Early-stage and late-stage HGSCs have highly similar patterns of mutation and focal SCNA. However, CN signature analysis showed that late-stage disease has distinct signature exposures consistent with whole-genome duplication. Further analyses will be required to ascertain whether these differences reflect genuine biological differences between early-stage and late-stage or simply time-related markers of evolutionary fitness. See related commentary by Yang et al., p. 2730.

Immunohistochemistry and Next-generation Sequencing Are Complementary Tests in Identifying PTEN Abnormality in Endometrial Carcinoma Biopsies.

PTEN plays a central role in the pathogenesis of endometrial carcinoma. Previous studies reported a high interobserver reproducibility for the interpretation of PTEN immunohistochemistry (IHC). However, PTEN IHC and its interpretation remain challenging during laboratory practice. The purpose of this study was to reevaluate PTEN IHC pattern in direct comparison to next-generation sequencing in identifying PTEN abnormality. IHC and tagged-amplicon next-generation sequencing PTEN sequencing was performed on 182 endometrial carcinoma biopsy/curetting samples from five centers (Barts, Calgary, Cambridge, Leiden, and Vancouver). Sensitivity, specificity and accuracy of PTEN IHC to predict loss of function PTEN mutations were calculated. Abnormalities of PTEN in association with histotype and molecular subtype were assessed. A total of 5 PTEN IHC patterns were recorded: absent, subclonal loss, equivocal, reduced (relative to internal control) and retained. The absence of PTEN IHC has a sensitivity of 75.4% (95% confidence interval: 62.7-85.5%), a specificity of 84.6% (95% confidence interval: 76.2%-90.9%), and accuracy of 81.2% (95% confidence interval: 74.4%-86.9%) in predicting loss of function PTEN mutation. PTEN abnormality by complementary interpretation of both assays was present in 91.9% of endometrial endometrioid carcinoma, grade 1, and significantly higher in endometrial endometrioid carcinomas of all grades compared with endometrial serous carcinoma (80.0% vs. 19.4%, P<0.0001). PTEN abnormalities are common across all molecular subtypes of endometrioid carcinomas. Our data support the use of ancillary PTEN IHC for diagnostic purposes in endometrial neoplasms. However, for clinical trial design complementary testing of both IHC and sequencing of PTEN should be considered to assess the PTEN status in endometrial carcinomas.

DNA Methylation Profiles of Ovarian Clear Cell Carcinoma.

BACKGROUND: Ovarian clear cell carcinoma (OCCC) is a rare ovarian cancer histotype that tends to be resistant to standard platinum-based chemotherapeutics. We sought to better understand the role of DNA methylation in clinical and biological subclassification of OCCC. METHODS: We interrogated genome-wide methylation using DNA from fresh frozen tumors from 271 cases, applied nonsmooth nonnegative matrix factorization (nsNMF) clustering, and evaluated clinical associations and biological pathways. RESULTS: Two approximately equally sized clusters that associated with several clinical features were identified. Compared with Cluster 2 (N = 137), Cluster 1 cases (N = 134) presented at a more advanced stage, were less likely to be of Asian ancestry, and tended to have poorer outcomes including macroscopic residual disease following primary debulking surgery (P < 0.10). Subset analyses of targeted tumor sequencing and IHC data revealed that Cluster 1 tumors showed TP53 mutation and abnormal p53 expression, and Cluster 2 tumors showed aneuploidy and ARID1A/PIK3CA mutation (P < 0.05). Cluster-defining CpGs included 1,388 CpGs residing within 200 bp of the transcription start sites of 977 genes; 38% of these genes (N = 369 genes) were differentially expressed across cluster in transcriptomic subset analysis (P < 10-4). Differentially expressed genes were enriched for six immune-related pathways, including IFNα and IFNγ responses (P < 10-6). CONCLUSIONS: DNA methylation clusters in OCCC correlate with disease features and gene expression patterns among immune pathways. IMPACT: This work serves as a foundation for integrative analyses that better understand the complex biology of OCCC in an effort to improve potential for development of targeted therapeutics.

FrenchFISH: Poisson Models for Quantifying DNA Copy Number From Fluorescence In Situ Hybridization of Tissue Sections.

PURPOSE: Chromosomal aberration and DNA copy number change are robust hallmarks of cancer. The gold standard for detecting copy number changes in tumor cells is fluorescence in situ hybridization (FISH) using locus-specific probes that are imaged as fluorescent spots. However, spot counting often does not perform well on solid tumor tissue sections due to partially represented or overlapping nuclei. MATERIALS AND METHODS: To overcome these challenges, we have developed a computational approach called FrenchFISH, which comprises a nuclear volume correction method coupled with two types of Poisson models: either a Poisson model for improved manual spot counting without the need for control probes or a homogeneous Poisson point process model for automated spot counting. RESULTS: We benchmarked the performance of FrenchFISH against previous approaches using a controlled simulation scenario and tested it experimentally in 12 ovarian carcinoma FFPE-tissue sections for copy number alterations at three loci (c-Myc, hTERC, and SE7). FrenchFISH outperformed standard spot counting with 74% of the automated counts having < 1 copy number difference from the manual counts and 17% having < 2 copy number differences, while taking less than one third of the time of manual counting. CONCLUSION: FrenchFISH is a general approach that can be used to enhance clinical diagnosis on sections of any tissue by both speeding up and improving the accuracy of spot count estimates.

Population-based targeted sequencing of 54 candidate genes identifies PALB2 as a susceptibility gene for high-grade serous ovarian cancer.

PURPOSE: The known epithelial ovarian cancer (EOC) susceptibility genes account for less than 50% of the heritable risk of ovarian cancer suggesting that other susceptibility genes exist. The aim of this study was to evaluate the contribution to ovarian cancer susceptibility of rare deleterious germline variants in a set of candidate genes. METHODS: We sequenced the coding region of 54 candidate genes in 6385 invasive EOC cases and 6115 controls of broad European ancestry. Genes with an increased frequency of putative deleterious variants in cases versus controls were further examined in an independent set of 14 135 EOC cases and 28 655 controls from the Ovarian Cancer Association Consortium and the UK Biobank. For each gene, we estimated the EOC risks and evaluated associations between germline variant status and clinical characteristics. RESULTS: The ORs associated for high-grade serous ovarian cancer were 3.01 for PALB2 (95% CI 1.59 to 5.68; p=0.00068), 1.99 for POLK (95% CI 1.15 to 3.43; p=0.014) and 4.07 for SLX4 (95% CI 1.34 to 12.4; p=0.013). Deleterious mutations in FBXO10 were associated with a reduced risk of disease (OR 0.27, 95% CI 0.07 to 1.00, p=0.049). However, based on the Bayes false discovery probability, only the association for PALB2 in high-grade serous ovarian cancer is likely to represent a true positive. CONCLUSIONS: We have found strong evidence that carriers of PALB2 deleterious mutations are at increased risk of high-grade serous ovarian cancer. Whether the magnitude of risk is sufficiently high to warrant the inclusion of PALB2 in cancer gene panels for ovarian cancer risk testing is unclear; much larger sample sizes will be needed to provide sufficiently precise estimates for clinical counselling.

Kinome capture sequencing of high-grade serous ovarian carcinoma reveals novel mutations in the JAK3 gene.

High-grade serous ovarian carcinoma (HGSOC) remains the deadliest form of epithelial ovarian cancer and despite major efforts little improvement in overall survival has been achieved. Identification of recurring "driver" genetic lesions has the potential to enable design of novel therapies for cancer. Here, we report on a study to find such new therapeutic targets for HGSOC using exome-capture sequencing approach targeting all kinase genes in 127 patient samples. Consistent with previous reports, the most frequently mutated gene was TP53 (97% mutation frequency) followed by BRCA1 (10% mutation frequency). The average mutation frequency of the kinase genes mutated from our panel was 1.5%. Intriguingly, after BRCA1, JAK3 was the most frequently mutated gene (4% mutation frequency). We tested the transforming properties of JAK3 mutants using the Ba/F3 cell-based in vitro functional assay and identified a novel gain-of-function mutation in the kinase domain of JAK3 (p.T1022I). Importantly, p.T1022I JAK3 mutants displayed higher sensitivity to the JAK3-selective inhibitor Tofacitinib compared to controls. For independent validation, we re-sequenced the entire JAK3 coding sequence using tagged amplicon sequencing (TAm-Seq) in 463 HGSOCs resulting in an overall somatic mutation frequency of 1%. TAm-Seq screening of CDK12 in the same population revealed a 7% mutation frequency. Our data confirms that the frequency of mutations in kinase genes in HGSOC is low and provides accurate estimates for the frequency of JAK3 and CDK12 mutations in a large well characterized cohort. Although p.T1022I JAK3 mutations are rare, our functional validation shows that if detected they should be considered as potentially actionable for therapy. The observation of CDK12 mutations in 7% of HGSOC cases provides a strong rationale for routine somatic testing, although more functional and clinical characterization is required to understand which nonsynonymous mutations alterations are associated with homologous recombination deficiency.

Proteomic analysis of transitional cell carcinoma-like variant of tubo-ovarian high-grade serous carcinoma.

The current World Health Organization classification does not distinguish transitional cell carcinoma of the ovary (TCC) from conventional tubo-ovarian high-grade serous carcinoma (HGSC), despite evidence suggesting improved prognosis for patients with TCC; instead, it is considered a morphologic variant of HGSC. The immunohistochemical (IHC) markers applied to date do not distinguish between TCC and HGSC. Therefore, we sought to compare the proteomic profiles of TCC and conventional HGSC to identify proteins enriched in TCC. Prognostic biomarkers in HGSC have proven to be elusive, and our aim was to identify biomarkers of TCC as a way of reliably and reproducibly identifying patients with a favorable prognosis and better response to chemotherapy compared with those with conventional HGSC. Quantitative global proteome analysis was performed on archival material of 12 cases of TCC and 16 cases of HGSC using SP3 (single-pot, solid phase-enhanced, sample preparation)-Clinical Tissue Proteomics, a recently described protocol for full-proteome analysis from formalin-fixed paraffin-embedded tissues. We identified 430 proteins that were significantly enriched in TCC over HGSC. Unsupervised co-clustering perfectly distinguished TCC from HGSC based on protein expression. Pathway analysis showed that proteins associated with cell death, necrosis, and apoptosis were highly expressed in TCCs, whereas proteins associated with DNA homologous recombination, cell mitosis, proliferation and survival, and cell cycle progression pathways had reduced expression. From the proteomic analysis, three potential biomarkers for TCC were identified, claudin-4 (CLDN4), ubiquitin carboxyl-terminal esterase L1 (UCHL1), and minichromosome maintenance protein 7 (MCM7), and tested by IHC analysis on tissue microarrays. In agreement with the proteomic analysis, IHC expression of those proteins was stronger in TCC than in HGSC (p < 0.0001). Using global proteomic analysis, we are able to distinguish TCC from conventional HGSC. Follow-up studies will be necessary to confirm that these molecular and morphologic differences are clinically significant.