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Molecular Analysis of Clinically Defined Subsets of High-Grade Serous Ovarian Cancer.

ABSTRACT: The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC), which is the most lethal gynecologic malignancy, is not well understood. Here, we perform comprehensive multi-platform omics analyses, including integrated analysis, and immune monitoring on primary and metastatic sites from highly clinically annotated HGSC samples based on a laparoscopic triage algorithm from patients who underwent complete gross resection (R0) or received neoadjuvant chemotherapy (NACT) with excellent or poor response. We identify significant distinct molecular abnormalities and cellular changes and immune cell repertoire alterations between the groups, including a higher rate of NF1 copy number loss, and reduced chromothripsis-like patterns, higher levels of strong-binding neoantigens, and a higher number of infiltrated T cells in the R0 versus the NACT groups.

SUBMITTER: Lee S

PROVIDER: S-EPMC7234854 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Molecular Analysis of Clinically Defined Subsets of High-Grade Serous Ovarian Cancer.

Lee Sanghoon S Zhao Li L Rojas Christine C Bateman Nicholas W NW Yao Hui H Lara Olivia D OD Celestino Joseph J Morgan Margaret B MB Nguyen Tri V TV Conrads Kelly A KA Rangel Kelly M KM Dood Robert L RL Hajek Richard A RA Fawcett Gloria L GL Chu Randy A RA Wilson Katlin K Loffredo Jeremy L JL Viollet Coralie C Jazaeri Amir A AA Dalgard Clifton L CL Mao Xizeng X Song Xingzhi X Zhou Ming M Hood Brian L BL Banskota Nirad N Wilkerson Matthew D MD Te Jerez J Soltis Anthony R AR Roman Kristin K Dunn Andrew A Cordover David D Eterovic Agda Karina AK Liu Jinsong J Burks Jared K JK Baggerly Keith A KA Fleming Nicole D ND Lu Karen H KH Westin Shannon N SN Coleman Robert L RL Mills Gordon B GB Casablanca Yovanni Y Zhang Jianhua J Conrads Thomas P TP Maxwell George L GL Futreal P Andrew PA Sood Anil K AK

Cell reports 20200401 2

The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC), which is the most lethal gynecologic malignancy, is not well understood. Here, we perform comprehensive multi-platform omics analyses, including integrated analysis, and immune monitoring on primary and metastatic sites from highly clinically annotated HGSC samples based on a laparoscopic triage algorithm from patients who underwent complete gross resection (R0) or received neoadjuvant chemotherapy (NACT) with excell ...[more]

PMID: 32294438

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Project description:PurposeOvarian cancer is the leading cause of gynecologic cancer-related death worldwide. Early diagnosis of ovarian cancer can significantly improve patient prognosis. Hence, there is an urgent need to identify key diagnostic and prognostic biomarkers specific for ovarian cancer. Because high-grade serous ovarian cancer (HGSOC) is the most common type of ovarian cancer and accounts for the majority of deaths, we identified potential biomarkers for the early diagnosis and prognosis of HGSOC.MethodsSix datasets (GSE14001, GSE18520, GSE26712, GSE27651, GSE40595, and GSE54388) were downloaded from the Gene Expression Omnibus database for analysis. Differentially expressed genes (DEGs) between HGSOC and normal ovarian surface epithelium samples were screened via integrated analysis. Hub genes were identified by analyzing protein-protein interaction (PPI) network data. The online Kaplan-Meier plotter was utilized to evaluate the prognostic roles of these hub genes. The expression of these hub genes was confirmed with Oncomine datasets and validated by quantitative real-time PCR and Western blotting.ResultsA total of 103 DEGs in patients with HGSOC-28 upregulated genes and 75 downregulated genes-were successfully screened. Enrichment analyses revealed that the upregulated genes were enriched in cell division and cell proliferation and that the downregulated genes mainly participated in the Wnt signaling pathway and various metabolic processes. Ten hub genes were associated with HGSOC pathogenesis. Seven overexpressed hub genes were partitioned into module 1 of the PPI network, which was enriched in the cell cycle and DNA replication pathways. Survival analysis revealed that MELK, CEP55 and KDR expression levels were significantly correlated with the overall survival of HGSOC patients (P < 0.05). The RNA and protein expression levels of these hub genes were validated experimentally.ConclusionBased on an integrated analysis, we propose the further investigation of MELK, CEP55 and KDR as promising diagnostic and prognostic biomarkers of HGSOC.

Project description:BackgroundHigh-grade serous ovarian cancer (HGSOC) is a major unmet need in oncology. The remaining uncertainty on its originating tissue has hampered the discovery of molecular oncogenic pathways and the development of effective therapies.MethodsWe used an approach based on the retention in tumors of a DNA methylation trace (OriPrint) that distinguishes the two putative tissues of origin of HGSOC, the fimbrial (FI) and ovarian surface epithelia (OSE), to stratify HGSOC by several clustering methods, both linear and non-linear. The identified tumor subtypes (FI-like and OSE-like HGSOC) were investigated at the RNAseq level to stratify an in-house cohort of macrodissected HGSOC FFPE samples to derive overall and disease-free survival and identify specific transcriptional alterations of the two tumor subtypes, both by classical differential expression and weighted correlation network analysis. We translated our strategy to published datasets and verified the co-occurrence of previously described molecular classification of HGSOC. We performed cytokine analysis coupled to immune phenotyping to verify alterations in the immune compartment associated with HGSOC. We identified genes that are both differentially expressed and methylated in the two tumor subtypes, concentrating on PAX8 as a bona fide marker of FI-like HGSOC.ResultsWe show that: - OriPrint is a robust DNA methylation tracer that exposes the tissue of origin of HGSOC. - The tissue of origin of HGSOC is the main determinant of DNA methylation variance in HGSOC. - The tissue of origin is a prognostic factor for HGSOC patients. - FI-like and OSE-like HGSOC are endowed with specific transcriptional alterations that impact patients' prognosis. - OSE-like tumors present a more invasive and immunomodulatory phenotype, compatible with its worse prognostic impact. - Among genes that are differentially expressed and regulated in FI-like and OSE-like HGSOC, PAX8 is a bona fide marker of FI-like tumors.ConclusionsThrough an integrated approach, our work demonstrates that both FI and OSE are possible origins for human HGSOC, whose derived subtypes are both molecularly and clinically distinct. These results will help define a new roadmap towards rational, subtype-specific therapeutic inroads and improved patients' care.

Dataset Information

Molecular Analysis of Clinically Defined Subsets of High-Grade Serous Ovarian Cancer.

Publications

Molecular Analysis of Clinically Defined Subsets of High-Grade Serous Ovarian Cancer.

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