{"doi":"10.1158/1055-9965.epi-24-0113","title":"Molecular Subtypes of High-Grade Serous Ovarian Cancer across Racial Groups and Gene Expression Platforms","abstract":"<h4>Background</h4>High-grade serous carcinoma (HGSC) gene expression subtypes are associated with differential survival. We characterized HGSC gene expression in Black individuals and considered whether gene expression differences by self-identified race may contribute to poorer HGSC survival among Black versus White individuals.<h4>Methods</h4>We included newly generated RNA sequencing data from Black and White individuals and array-based genotyping data from four existing studies of White and Japanese individuals. We used K-means clustering, a method with no predefined number of clusters or dataset-specific features, to assign subtypes. Cluster- and dataset-specific gene expression patterns were summarized by moderated t-scores. We compared cluster-specific gene expression patterns across datasets by calculating the correlation between the summarized vectors of moderated t-scores. After mapping to The Cancer Genome Atlas-derived HGSC subtypes, we used Cox proportional hazards models to estimate subtype-specific survival by dataset.<h4>Results</h4>Cluster-specific gene expression was similar across gene expression platforms and racial groups. Comparing the Black population with the White and Japanese populations, the immunoreactive subtype was more common (39% vs. 23%-28%) and the differentiated subtype was less common (7% vs. 22%-31%). Patterns of subtype-specific survival were similar between the Black and White populations with RNA sequencing data; compared with mesenchymal cases, the risk of death was similar for proliferative and differentiated cases and suggestively lower for immunoreactive cases [Black population HR = 0.79 (0.55, 1.13); White population HR = 0.86 (0.62, 1.19)].<h4>Conclusions</h4>Although the prevalence of HGSC subtypes varied by race, subtype-specific survival was similar.<h4>Impact</h4>HGSC subtypes can be consistently assigned across platforms and self-identified racial groups.","journal":"Cancer Epidemiology, Biomarkers &amp; Prevention","year":2024,"id":9901,"datarank":0.38781239593256933,"base_score":2.302585092994046,"endowment":2.302585092994046,"self_citation_contribution":0.3453877639491069,"citation_network_contribution":0.042424631983462434,"self_endowment_contribution":0.3453877639491069,"citer_contribution":0.042424631983462434,"corpus_percentile":49.47111472742067,"corpus_rank":622,"citation_count":11,"citer_count":7,"citers_with_citation_signal":2,"citers_with_endowment":2,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.7036,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-05-23","fair_score":31.3333,"fair_percentile":13.390501319261213,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":297,"name":"Mollie  E. 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