Genome-wide association analyses of ovarian cancer patients undergoing primary debulking surgery identify candidate genes for residual disease

Survival from ovarian cancer depends on the resection status after primary surgery. We performed genome-wide association analyses for resection status of 7705 ovarian cancer patients, including 4954 with high-grade serous carcinoma (HGSOC), to identify variants associated with residual disease. The most significant association with resection status was observed for rs72845444, upstream of MGMT, in HGSOC (p = 3.9 × 10-8). In gene-based analyses, PPP2R5C was the most strongly associated gene in HGSOC after stage adjustment. In an independent set of 378 ovarian tumours from the AGO-OVAR 11 study, variants near MGMT and PPP2R5C correlated with methylation and transcript levels, and PPP2R5C mRNA levels predicted progression-free survival in patients with residual disease. MGMT encodes a DNA repair enzyme, and PPP2R5C encodes the B56γ subunit of the PP2A tumour suppressor. Our results link heritable variation at these two loci with resection status in HGSOC.

Implementation of endometrial cancer molecular subtyping into a hybrid community-academic practice

OBJECTIVES

We sought to confirm utility of our institution's modified Proactive Molecular Risk Classifier for Endometrial Cancer protocol in our daily practice, which includes mismatch repair (MMR), p53, and L1 cell adhesion molecule (L1CAM) immunohistochemistry with in-house next-generation sequencing for POLE, TP53, and CTNNB1.

METHODS

We conducted a retrospective review of all patients in our institution who underwent primary endometrial carcinoma resection from the year prior to protocol implementation (PRE; October 1, 2020, to September 30, 2021) through first year of implementation (POST; October 1, 2021, to September 30, 2022) to compare the distribution of molecular and traditional staging factors using GOG-249 criteria to assign clinical risk.

RESULTS

In total, 136 of 260 PRE patients were classified as clinically low risk (LR), of whom 31 were MMR deficient. Of the 157 LR POST patients with endometrioid-type carcinoma, 45 were MMR deficient, 5 were POLE mutant, 5 were TP53 mutant, 56 were of no specific molecular profile (NSMP), and 46 did not receive full protocol testing. Of all 79 POST NSMP endometrioid-type cases, 18 were CTNNB1 mutated and 8 showed L1CAM expression.

CONCLUSIONS

Our protocol identified 22 (14%) of 157 LR tumors that harbored incipient intermediate- to high-risk molecular aberrations in TP53, CTNNB1, or L1CAM. Moving forward, results of ongoing trials assessing adjuvant therapy decisions based on molecular classification are necessary to confirm protocol utility and identify appropriate modifications.

The transcription factor PAX8 promotes angiogenesis in ovarian cancer through interaction with SOX17

PAX8 is a master transcription factor that is essential during embryogenesis and promotes neoplastic growth. It is expressed by the secretory cells lining the female reproductive tract, and its deletion during development results in atresia of reproductive tract organs. Nearly all ovarian carcinomas express PAX8, and its knockdown results in apoptosis of ovarian cancer cells. To explore the role of PAX8 in these tissues, we purified the PAX8 protein complex from nonmalignant fallopian tube cells and high-grade serous ovarian carcinoma cell lines. We found that PAX8 was a member of a large chromatin remodeling complex and preferentially interacted with SOX17, another developmental transcription factor. Depleting either PAX8 or SOX17 from cancer cells altered the expression of factors involved in angiogenesis and functionally disrupted tubule and capillary formation in cell culture and mouse models. PAX8 and SOX17 in ovarian cancer cells promoted the secretion of angiogenic factors by suppressing the expression of SERPINE1, which encodes a proteinase inhibitor with antiangiogenic effects. The findings reveal a non-cell-autonomous function of these transcription factors in regulating angiogenesis in ovarian cancer.

Single-Cell RNA Sequencing of Ovarian Cancer: Promises and Challenges

Ovarian cancer remains the leading cause of death from gynecologic malignancy in the Western world. Tumors are comprised of heterogeneous populations of various cancer, immune, and stromal cells; it is hypothesized that rare cancer stem cells within these subpopulations lead to disease recurrence and treatment resistance. Technological advances now allow for the analysis of tumor genomes and transcriptomes at the single-cell level, which provides the resolution to potentially identify these rare cancer stem cells within the larger tumor.In this chapter, we review the evolution of next-generation RNA sequencing techniques, the methodology of single-cell isolation and sequencing, sequencing data analysis, and the potential applications in ovarian cancer. We also summarize the current published work using single-cell sequencing in ovarian cancer.By utilizing this novel technique to characterize the gene expression of rare subpopulations, new targets and treatment pathways may be identified in ovarian cancer to change treatment paradigms.

Molecular characterization of endometrial cancer and therapeutic implications

PURPOSE OF REVIEW

The present article reviews molecular subtyping and genomic characterization of endometrial carcinoma, and the associated therapeutic and prognostic implications.

RECENT FINDINGS

Endometrial cancer has historically been classified through histology into endometrioid and nonendometrioid subtypes with poor prognostic predictability. Molecular classification through genomic analysis now allows for a major advance in characterization. Four distinct subgroups have been identified: polymerase (POLE) ultramutated, microsatellite unstable, copy number-low--microsatellite stable, and copy number-high-'serous-like'. These subtypes have prognostic implications and may aid in the identification of early-stage patients who are at high risk for recurrence. Through analysis of surrogate markers (POLE, MSI, and p53) and other validated molecular alterations (L1CAM), it is possible to obtain an integrated molecular risk profile that relates to prognosis. Studies utilizing this risk profile in order to identify patients who may benefit from adjuvant treatment for early-stage disease are on-going.

SUMMARY

Molecular characterization of endometrial cancer into subgroups has enhanced prognostic and therapeutic implications, contrary to traditional risk stratification. Further development of an integrated molecular risk profile may identify patients who could most benefit from adjuvant treatment following surgery and tailor treatment decisions in the recurrent setting.

Development and Validation of the Gene Expression Predictor of High-grade Serous Ovarian Carcinoma Molecular SubTYPE (PrOTYPE)

PURPOSE

Gene expression-based molecular subtypes of high-grade serous tubo-ovarian cancer (HGSOC), demonstrated across multiple studies, may provide improved stratification for molecularly targeted trials. However, evaluation of clinical utility has been hindered by nonstandardized methods, which are not applicable in a clinical setting. We sought to generate a clinical grade minimal gene set assay for classification of individual tumor specimens into HGSOC subtypes and confirm previously reported subtype-associated features.

EXPERIMENTAL DESIGN

Adopting two independent approaches, we derived and internally validated algorithms for subtype prediction using published gene expression data from 1,650 tumors. We applied resulting models to NanoString data on 3,829 HGSOCs from the Ovarian Tumor Tissue Analysis consortium. We further developed, confirmed, and validated a reduced, minimal gene set predictor, with methods suitable for a single-patient setting.

RESULTS

Gene expression data were used to derive the predictor of high-grade serous ovarian carcinoma molecular subtype (PrOTYPE) assay. We established a de facto standard as a consensus of two parallel approaches. PrOTYPE subtypes are significantly associated with age, stage, residual disease, tumor-infiltrating lymphocytes, and outcome. The locked-down clinical grade PrOTYPE test includes a model with 55 genes that predicted gene expression subtype with >95% accuracy that was maintained in all analytic and biological validations.

CONCLUSIONS

We validated the PrOTYPE assay following the Institute of Medicine guidelines for the development of omics-based tests. This fully defined and locked-down clinical grade assay will enable trial design with molecular subtype stratification and allow for objective assessment of the predictive value of HGSOC molecular subtypes in precision medicine applications.See related commentary by McMullen et al., p. 5271.

Prognostic gene expression signature for high-grade serous ovarian cancer

BACKGROUND

Median overall survival (OS) for women with high-grade serous ovarian cancer (HGSOC) is ∼4 years, yet survival varies widely between patients. There are no well-established, gene expression signatures associated with prognosis. The aim of this study was to develop a robust prognostic signature for OS in patients with HGSOC.

PATIENTS AND METHODS

Expression of 513 genes, selected from a meta-analysis of 1455 tumours and other candidates, was measured using NanoString technology from formalin-fixed paraffin-embedded tumour tissue collected from 3769 women with HGSOC from multiple studies. Elastic net regularization for survival analysis was applied to develop a prognostic model for 5-year OS, trained on 2702 tumours from 15 studies and evaluated on an independent set of 1067 tumours from six studies.

RESULTS

Expression levels of 276 genes were associated with OS (false discovery rate < 0.05) in covariate-adjusted single-gene analyses. The top five genes were TAP1, ZFHX4, CXCL9, FBN1 and PTGER3 (P < 0.001). The best performing prognostic signature included 101 genes enriched in pathways with treatment implications. Each gain of one standard deviation in the gene expression score conferred a greater than twofold increase in risk of death [hazard ratio (HR) 2.35, 95% confidence interval (CI) 2.02-2.71; P < 0.001]. Median survival [HR (95% CI)] by gene expression score quintile was 9.5 (8.3 to -), 5.4 (4.6-7.0), 3.8 (3.3-4.6), 3.2 (2.9-3.7) and 2.3 (2.1-2.6) years.

CONCLUSION

The OTTA-SPOT (Ovarian Tumor Tissue Analysis consortium - Stratified Prognosis of Ovarian Tumours) gene expression signature may improve risk stratification in clinical trials by identifying patients who are least likely to achieve 5-year survival. The identified novel genes associated with the outcome may also yield opportunities for the development of targeted therapeutic approaches.

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.

UNC-45A is preferentially expressed in epithelial cells and binds to and co-localizes with interphase MTs

UNC-45A is an ubiquitously expressed protein highly conserved throughout evolution. Most of what we currently know about UNC-45A pertains to its role as a regulator of the actomyosin system. However, emerging studies from both our and other laboratories support a role of UNC-45A outside of actomyosin regulation. This includes studies showing that UNC-45A: regulates gene transcription, co-localizes and biochemically co-fractionates with gamma tubulin and regulates centrosomal positioning, is found in the same subcellular fractions where MT-associated proteins are, and is a mitotic spindle-associated protein with MT-destabilizing activity in absence of the actomyosin system.

Here, we extended our previous findings and show that UNC45A is variably expressed across a spectrum of cell lines with the highest level being found in HeLa cells and in ovarian cancer cells inherently paclitaxel-resistant. Furthermore, we show that UNC-45A is preferentially expressed in epithelial cells, localizes to mitotic spindles in clinical tumor specimens of cancer and co-localizes and co-fractionates with MTs in interphase cells independent of actin or myosin.

In sum, we report alteration of UNC45A localization in the setting of chemotherapeutic treatment of cells with paclitaxel, and localization of UNC45A to MTs both in vitro and in vivo. These findings will be important to ongoing and future studies in the field that further identify the important role of UNC45A in cancer and other cellular processes.

A patient-centered mobile health application to motivate use of genetic counseling among women with ovarian cancer: A pilot randomized controlled trial

OBJECTIVE

Despite current guidelines recommending women with ovarian cancer receive genetic risk evaluation by a genetic counselor, utilization has historically been low. We sought to assess the feasibility and effectiveness of a week-long mobile Application for Genetic Information on Cancer (mAGIC) intervention aimed to persuade women with ovarian cancer to pursue genetic counseling.

METHODS

The mobile application intervention was based on the Fogg Behavior Model, and consisted of three parts: (1) identifying barriers, (2) developing motivators, and (3) providing triggers to action. The Health Belief Model was used to guide content development. We conducted a prospective, randomized, controlled pilot trial among 104 untested women with a history of epithelial ovarian, primary peritoneal or fallopian tube cancer with the primary objective of increasing uptake of cancer genetic counseling services.

RESULTS

Utilization of cancer genetic counseling services improved in both study arms over historical controls, however there was no statistically significant difference between them (intervention: 54.5% versus control: 38.6%; p = 0.14). However, compared to controls, women randomized to the mAGIC intervention demonstrated greater knowledge of hereditary cancer (0-10 scale; 9.4 ± 1.0 vs. 7.1 ± 1.5; p < 0.0001), which persisted for at least three months. Additionally, 96% of women in the intervention group reported they had talked with their family about genetic counseling compared to 77% in the control group (p = 0.01).

CONCLUSIONS

The mAGIC intervention did not result in increased uptake of genetic counseling, however it provided significant secondary benefits, including increased participants' knowledge about hereditary ovarian cancer, self-efficacy, and their reported communication with family members. ClinicalTrials.gov Identifier: NCT02877862.

Developing a Clinico-Molecular Test for Individualized Treatment of Ovarian Cancer: The interplay of Precision Medicine Informatics with Clinical and Health Economics Dimensions

We report recent progress in the development of a precision test for individualized use of the VEGF-A targeting drug bevacizumab for treating ovarian cancer. We discuss the discovery model stage (i.e., past feasibility modeling and before conversion to the production test). Main results: (a) Informatics modeling plays a critical role in supporting driving clinical and health economic requirements. (b) The novel computational models support the creation of a precision test with sufficient predictivity to reduce healthcare system costs up to $30 billion over 10 years, and make the use of bevacizumab affordable without loss of length or quality of life.

Bevacizumab May Differentially Improve Ovarian Cancer Outcome in Patients with Proliferative and Mesenchymal Molecular Subtypes

Purpose: Recent progress in understanding the molecular biology of epithelial ovarian cancer has not yet translated into individualized treatment for these women or improvements in their disease outcome. Gene expression has been utilized to identify distinct molecular subtypes, but there have been no reports investigating whether or not molecular subtyping is predictive of response to bevacizumab in ovarian cancer.Experimental Design: DASL gene expression arrays were performed on FFPE tissue from patients enrolled on the ICON7 trial. Patients were stratified into four TCGA molecular subtypes. Associations between molecular subtype and the efficacy of randomly assigned therapy with bevacizumab were assessed.Results: Molecular subtypes were assigned as follows: 122 immunoreactive (34%), 96 proliferative (27%), 73 differentiated (20%), and 68 mesenchymal (19%). In univariate analysis patients with tumors of proliferative subtype obtained the greatest benefit from bevacizumab with a median PFS improvement of 10.1 months [HR, 0.55 (95% CI, 0.34-0.90), P = 0.016]. For the mesenchymal subtype, bevacizumab conferred a nonsignificant improvement in PFS of 8.2 months [HR 0.78 (95% CI, 0.44-1.40), P = 0.41]. Bevacizumab conferred modest improvements in PFS for patients with immunoreactive subtype (3.8 months; P = 0.08) or differentiated subtype (3.7 months; P = 0.61). Multivariate analysis demonstrated significant PFS improvement in proliferative subtype patients only [HR, 0.45 (95% CI, 0.27-0.74), P = 0.0015].Conclusions: Ovarian carcinoma molecular subtypes with the poorest survival (proliferative and mesenchymal) derive a comparably greater benefit from treatment that includes bevacizumab. Validation of our findings in an independent cohort could enable the use of bevacizumab for those patients most likely to benefit, thereby reducing side effects and healthcare cost. Clin Cancer Res; 23(14); 3794-801. ©2017 AACR.

Abstract 5402: Single cell sequencing of high grade serous ovarian cancer

We performed RNA sequencing of single cells derived from a high grade serous ovarian cancer (HGSOC) specimen to determine the extent of heterogeneity and to determine if it was feasible to identify cancer stem cells or gene expression signatures of chemo resistance. To perform RNA sequencing we enzymatically digested a fresh specimen from an HGSOC derived from the ovary. Immune cells were depleted by flow cytometry and single cell sequencing was performed using the Fluidigm C1 chip in tandem with Illumina HiSeq 2500 sequencing. Multiple bioinformatics tools were used to identify subgroups and activated pathways. Immunohistochemistry was performed on an adjacent tumor section to analyze markers of epithelium, stroma and stem cells. We found that gene expression patterns in single cells could be used to separate cells into stroma-like and epithelial-like groups. Gene set enrichment analysis identified proliferative genesets (oxidative phosphorylation and MYC targets) associated with the epithelial-like cells while epithelial-to-mesenchymal-transition (EMT) genes associated with the stroma-like cells. Neither group was significantly associated with genesets derived from chemo-resistant cells. Using known marker analysis, we could identify a small percentage of cells that expressed ovarian cancer stem cell markers and we could group cells into functional categories. Using four molecular subtypes established from large-scale bulk sequencing studies we show that single cells from a single patient are heterogeneous and each molecular subtype is represented. In conclusion, we show the feasibility of performing single cell sequencing on an epithelial ovarian cancer and reveal a heterogeneous population of cells. Expanding these findings to a larger cohort of patients could allow for identification of targetable sub-populations of cells that were previously undetectable in studies that use bulk samples to interrogate the transcriptome and genome of ovarian cancer patients.

Citation Format: Timothy K. Starr, Boris Winterhoff, Makayla Maile, Kenneth Beckman, Jerry Daniel, Melissa Geller, Martina Bazzaro, Molly Klein, Raffaele Hellweg, Juan Abrahante, Amit K. Mitra, Atilla Sebe, Sally A. Mullany. Single cell sequencing of high grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5402. doi:10.1158/1538-7445.AM2017-5402

Assessment of the Intraoperative Consultation Service Rendered by General Pathologists in a Scenario Where a Well-Defined Decision Algorithm Is Followed

OBJECTIVES

Intraoperative consultation (IOC) remains an area of general practice even within subspecialized pathology departments. This study assesses the IOCs rendered in a general pathology setting where surgeons integrate these results in a well-defined algorithm, developed with the input of specialized pathologists.

METHODS

The surgical decisions to perform lymphadenectomy in patients with endometrial adenocarcinoma operated on at our institution between January 2003 and June 2015 as a result of the IOC assessment of tumor size, histologic grade, and depth of invasion in the hysterectomy specimen were analyzed.

RESULTS

Frozen section (FS) was examined in 801 cases. In comparison to permanent section analysis, FS International Federation of Gynecology and Obstetrics (FIGO) grade had an overall accuracy of 0.95 (95% confidence interval [CI], 0.93-0.98). The FS depth of invasion had an overall accuracy of 0.92 (95% CI, 0.89-0.94). FIGO grade was not documented in 47.8%, the depth of myometrial invasion in 45.2%, and tumor size in 41.8% of the pathology reports.

CONCLUSIONS

The high omission rate of the needed parameters by the general pathologists would question their overall understanding of the paradigm shift intended by this algorithm. Possible explanations of this phenomenon and potential solutions are discussed.

Bevacizumab May Differentially Improve Ovarian Cancer Outcome in Patients with Proliferative and Mesenchymal Molecular Subtypes

Purpose: Recent progress in understanding the molecular biology of epithelial ovarian cancer has not yet translated into individualized treatment for these women or improvements in their disease outcome. Gene expression has been utilized to identify distinct molecular subtypes, but there have been no reports investigating whether or not molecular subtyping is predictive of response to bevacizumab in ovarian cancer.Experimental Design: DASL gene expression arrays were performed on FFPE tissue from patients enrolled on the ICON7 trial. Patients were stratified into four TCGA molecular subtypes. Associations between molecular subtype and the efficacy of randomly assigned therapy with bevacizumab were assessed.Results: Molecular subtypes were assigned as follows: 122 immunoreactive (34%), 96 proliferative (27%), 73 differentiated (20%), and 68 mesenchymal (19%). In univariate analysis patients with tumors of proliferative subtype obtained the greatest benefit from bevacizumab with a median PFS improvement of 10.1 months [HR, 0.55 (95% CI, 0.34-0.90), P = 0.016]. For the mesenchymal subtype, bevacizumab conferred a nonsignificant improvement in PFS of 8.2 months [HR 0.78 (95% CI, 0.44-1.40), P = 0.41]. Bevacizumab conferred modest improvements in PFS for patients with immunoreactive subtype (3.8 months; P = 0.08) or differentiated subtype (3.7 months; P = 0.61). Multivariate analysis demonstrated significant PFS improvement in proliferative subtype patients only [HR, 0.45 (95% CI, 0.27-0.74), P = 0.0015].Conclusions: Ovarian carcinoma molecular subtypes with the poorest survival (proliferative and mesenchymal) derive a comparably greater benefit from treatment that includes bevacizumab. Validation of our findings in an independent cohort could enable the use of bevacizumab for those patients most likely to benefit, thereby reducing side effects and healthcare cost. Clin Cancer Res; 23(14); 3794-801. ©2017 AACR.

Molecular classification of high grade endometrioid and clear cell ovarian cancer using TCGA gene expression signatures

BACKGROUND

It is unclear whether the transcriptional subtypes of high grade serous ovarian cancer (HGSOC) apply to high grade clear cell (HGCCOC) or high grade endometrioid ovarian cancer (HGEOC). We aim to delineate transcriptional profiles of HGCCOCs and HGEOCs.

METHODS

We used Agilent microarrays to determine gene expression profiles of 276 well annotated ovarian cancers (OCs) including 37 HGCCOCs and 66 HGEOCs. We excluded low grade OCs as these are known to be distinct molecular entities. We applied the prespecified TCGA and CLOVAR gene signatures using consensus non-negative matrix factorization (NMF).

RESULTS

We confirm the presence of four TCGA transcriptional subtypes and their significant prognostic relevance (p<0.001) across all three histological subtypes (HGSOC, HGCCOC and HGEOCs). However, we also demonstrate that 22/37 (59%) HGCCOCs and 30/67 (45%) HGEOCs form 2 additional separate clusters with distinct gene signatures. Importantly, of the HGCCOC and HGEOCs that clustered separately 62% and 65% were early stage (FIGO I/II), respectively. These finding were confirmed using the reduced CLOVAR gene set for classification where most early stage HGCCOCs and HGEOCs formed a distinct cluster of their own. When restricting the analysis to the four TCGA signatures (ssGSEA or NMF with CLOVAR genes) most early stage HGCCOCs and HGEOC were assigned to the differentiated subtype.

CONCLUSIONS

Using transcriptional profiling the current study suggests that HGCCOCs and HGEOCs of advanced stage group together with HGSOCs. However, HGCCOCs and HGEOCs of early disease stages may have distinct transcriptional signatures similar to those seen in their low grade counterparts.

Gene-expression signatures in ovarian cancer: Promise and challenges for patient stratification

Microarray-based gene expression studies demonstrate that ovarian cancer is both a clinically diverse and molecularly heterogeneous disease compromising subtypes with distinct gene expression patterns that are each associated with statistically significant different clinical outcomes. The information provided by gene expression based assays is promising and deserves incorporation into clinical decision-making. Further studies are needed to determine which subtype signatures are most appropriate to select patients for a given therapy. This process will require the development of standardized molecular diagnostic assays that can be used for retrospective correlative studies and prospective validations of their clinical utility. Recent advances in assay development for FFPE tissues will facilitate accurate and cost-effective classification of ovarian cancer and help move the evolving molecular classification to clinic. The current review will summarize the development of gene expression based assays in ovarian cancer and will describe how the results of studies to date have expanded our appreciation of the heterogeneity of ovarian cancer. We discuss difficulties in the development and validation of molecular classifications in ovarian cancer and we provide future directions how we may be able to soon classify the disease in a manner that might have greater clinical utility.

Elevated CDCP1 predicts poor patient outcome and mediates ovarian clear cell carcinoma by promoting tumor spheroid formation, cell migration and chemoresistance

Hematogenous metastases are rarely present at diagnosis of ovarian clear cell carcinoma (OCC). Instead dissemination of these tumors is characteristically via direct extension of the primary tumor into nearby organs and the spread of exfoliated tumor cells throughout the peritoneum, initially via the peritoneal fluid, and later via ascites that accumulates as a result of disruption of the lymphatic system. The molecular mechanisms orchestrating these processes are uncertain. In particular, the signaling pathways used by malignant cells to survive the stresses of anchorage-free growth in peritoneal fluid and ascites, and to colonize remote sites, are poorly defined. We demonstrate that the transmembrane glycoprotein CUB-domain-containing protein 1 (CDCP1) has important and inhibitable roles in these processes. In vitro assays indicate that CDCP1 mediates formation and survival of OCC spheroids, as well as cell migration and chemoresistance. Disruption of CDCP1 via silencing and antibody-mediated inhibition markedly reduce the ability of TOV21G OCC cells to form intraperitoneal tumors and induce accumulation of ascites in mice. Mechanistically our data suggest that CDCP1 effects are mediated via a novel mechanism of protein kinase B (Akt) activation. Immunohistochemical analysis also suggested that CDCP1 is functionally important in OCC, with its expression elevated in 90% of 198 OCC tumors and increased CDCP1 expression correlating with poor patient disease-free and overall survival. This analysis also showed that CDCP1 is largely restricted to the surface of malignant cells where it is accessible to therapeutic antibodies. Importantly, antibody-mediated blockade of CDCP1 in vivo significantly increased the anti-tumor efficacy of carboplatin, the chemotherapy most commonly used to treat OCC. In summary, our data indicate that CDCP1 is important in the progression of OCC and that targeting pathways mediated by this protein may be useful for the management of OCC, potentially in combination with chemotherapies and agents targeting the Akt pathway.

PG545 enhances anti-cancer activity of chemotherapy in ovarian models and increases surrogate biomarkers such as VEGF in preclinical and clinical plasma samples

BACKGROUND

Despite the utility of antiangiogenic drugs in ovarian cancer, efficacy remains limited due to resistance linked to alternate angiogenic pathways and metastasis. Therefore, we investigated PG545, an anti-angiogenic and anti-metastatic agent which is currently in Phase I clinical trials, using preclinical models of ovarian cancer.

METHODS

PG545's anti-cancer activity was investigated in vitro and in vivo as a single agent, and in combination with paclitaxel, cisplatin or carboplatin using various ovarian cancer cell lines and tumour models.

RESULTS

PG545, alone, or in combination with chemotherapeutics, inhibited proliferation of ovarian cancer cells, demonstrating synergy with paclitaxel in A2780 cells. PG545 inhibited growth factor-mediated cell migration and reduced HB-EGF-induced phosphorylation of ERK, AKT and EGFR in vitro and significantly reduced tumour burden which was enhanced when combined with paclitaxel in an A2780 model or carboplatin in a SKOV-3 model. Moreover, in the immunocompetent ID8 model, PG545 also significantly reduced ascites in vivo. In the A2780 maintenance model, PG545 initiated with, and following paclitaxel and cisplatin treatment, significantly improved overall survival. PG545 increased plasma VEGF levels (and other targets) in preclinical models and in a small cohort of advanced cancer patients which might represent a potential biomarker of response.

CONCLUSION

Our results support clinical testing of PG545, particularly in combination with paclitaxel, as a novel therapeutic strategy for ovarian cancer.

Fine-mapping of the HNF1B multicancer locus identifies candidate variants that mediate endometrial cancer risk

Common variants in the hepatocyte nuclear factor 1 homeobox B (HNF1B) gene are associated with the risk of Type II diabetes and multiple cancers. Evidence to date indicates that cancer risk may be mediated via genetic or epigenetic effects on HNF1B gene expression. We previously found single-nucleotide polymorphisms (SNPs) at the HNF1B locus to be associated with endometrial cancer, and now report extensive fine-mapping and in silico and laboratory analyses of this locus. Analysis of 1184 genotyped and imputed SNPs in 6608 Caucasian cases and 37 925 controls, and 895 Asian cases and 1968 controls, revealed the best signal of association for SNP rs11263763 (P = 8.4 × 10(-14), odds ratio = 0.86, 95% confidence interval = 0.82-0.89), located within HNF1B intron 1. Haplotype analysis and conditional analyses provide no evidence of further independent endometrial cancer risk variants at this locus. SNP rs11263763 genotype was associated with HNF1B mRNA expression but not with HNF1B methylation in endometrial tumor samples from The Cancer Genome Atlas. Genetic analyses prioritized rs11263763 and four other SNPs in high-to-moderate linkage disequilibrium as the most likely causal SNPs. Three of these SNPs map to the extended HNF1B promoter based on chromatin marks extending from the minimal promoter region. Reporter assays demonstrated that this extended region reduces activity in combination with the minimal HNF1B promoter, and that the minor alleles of rs11263763 or rs8064454 are associated with decreased HNF1B promoter activity. Our findings provide evidence for a single signal associated with endometrial cancer risk at the HNF1B locus, and that risk is likely mediated via altered HNF1B gene expression.

Candidate locus analysis of the TERT-CLPTM1L cancer risk region on chromosome 5p15 identifies multiple independent variants associated with endometrial cancer risk

Several studies have reported associations between multiple cancer types and single-nucleotide polymorphisms (SNPs) on chromosome 5p15, which harbours TERT and CLPTM1L, but no such association has been reported with endometrial cancer. To evaluate the role of genetic variants at the TERT-CLPTM1L region in endometrial cancer risk, we carried out comprehensive fine-mapping analyses of genotyped and imputed SNPs using a custom Illumina iSelect array which includes dense SNP coverage of this region. We examined 396 SNPs (113 genotyped, 283 imputed) in 4,401 endometrial cancer cases and 28,758 controls. Single-SNP and forward/backward logistic regression models suggested evidence for three variants independently associated with endometrial cancer risk (P = 4.9 × 10(-6) to P = 7.7 × 10(-5)). Only one falls into a haplotype previously associated with other cancer types (rs7705526, in TERT intron 1), and this SNP has been shown to alter TERT promoter activity. One of the novel associations (rs13174814) maps to a second region in the TERT promoter and the other (rs62329728) is in the promoter region of CLPTM1L; neither are correlated with previously reported cancer-associated SNPs. Using TCGA RNASeq data, we found significantly increased expression of both TERT and CLPTM1L in endometrial cancer tissue compared with normal tissue (TERT P = 1.5 × 10(-18), CLPTM1L P = 1.5 × 10(-19)). Our study thus reports a novel endometrial cancer risk locus and expands the spectrum of cancer types associated with genetic variation at 5p15, further highlighting the importance of this region for cancer susceptibility.

Prognostic and therapeutic relevance of molecular subtypes in high-grade serous ovarian cancer

Molecular classification of high-grade serous ovarian cancer (HGSOC) using transcriptional profiling has proven to be complex and difficult to validate across studies. We determined gene expression profiles of 174 well-annotated HGSOCs and demonstrate prognostic significance of the prespecified TCGA Network gene signatures. Furthermore, we confirm the presence of four HGSOC transcriptional subtypes using a de novo classification. Survival differed statistically significantly between de novo subtypes (log rank, P = .006) and was the best for the immunoreactive-like subtype, but statistically significantly worse for the proliferative- or mesenchymal-like subtypes (adjusted hazard ratio = 1.89, 95% confidence interval = 1.18 to 3.02, P = .008, and adjusted hazard ratio = 2.45, 95% confidence interval = 1.43 to 4.18, P = .001, respectively). More prognostic information was provided by the de novo than the TCGA classification (Likelihood Ratio tests, P = .003 and P = .04, respectively). All statistical tests were two-sided. These findings were replicated in an external data set of 185 HGSOCs and confirm the presence of four prognostically relevant molecular subtypes that have the potential to guide therapy decisions.

Prognostic and therapeutic relevance of molecular subtypes in high-grade serous ovarian cancer

Molecular classification of high-grade serous ovarian cancer (HGSOC) using transcriptional profiling has proven to be complex and difficult to validate across studies. We determined gene expression profiles of 174 well-annotated HGSOCs and demonstrate prognostic significance of the prespecified TCGA Network gene signatures. Furthermore, we confirm the presence of four HGSOC transcriptional subtypes using a de novo classification. Survival differed statistically significantly between de novo subtypes (log rank, P = .006) and was the best for the immunoreactive-like subtype, but statistically significantly worse for the proliferative- or mesenchymal-like subtypes (adjusted hazard ratio = 1.89, 95% confidence interval = 1.18 to 3.02, P = .008, and adjusted hazard ratio = 2.45, 95% confidence interval = 1.43 to 4.18, P = .001, respectively). More prognostic information was provided by the de novo than the TCGA classification (Likelihood Ratio tests, P = .003 and P = .04, respectively). All statistical tests were two-sided. These findings were replicated in an external data set of 185 HGSOCs and confirm the presence of four prognostically relevant molecular subtypes that have the potential to guide therapy decisions.

Prognostic and therapeutic relevance of molecular subtypes in high-grade serous ovarian cancer

Molecular classification of high-grade serous ovarian cancer (HGSOC) using transcriptional profiling has proven to be complex and difficult to validate across studies. We determined gene expression profiles of 174 well-annotated HGSOCs and demonstrate prognostic significance of the prespecified TCGA Network gene signatures. Furthermore, we confirm the presence of four HGSOC transcriptional subtypes using a de novo classification. Survival differed statistically significantly between de novo subtypes (log rank, P = .006) and was the best for the immunoreactive-like subtype, but statistically significantly worse for the proliferative- or mesenchymal-like subtypes (adjusted hazard ratio = 1.89, 95% confidence interval = 1.18 to 3.02, P = .008, and adjusted hazard ratio = 2.45, 95% confidence interval = 1.43 to 4.18, P = .001, respectively). More prognostic information was provided by the de novo than the TCGA classification (Likelihood Ratio tests, P = .003 and P = .04, respectively). All statistical tests were two-sided. These findings were replicated in an external data set of 185 HGSOCs and confirm the presence of four prognostically relevant molecular subtypes that have the potential to guide therapy decisions.