Comprehensive Cross-Population Analysis of High-Grade Serous Ovarian Cancer Supports No More Than Three Subtypes. Issue 12 (1st December 2016)

• Record Type: Journal Article
• Authors: Way, Gregory P; Rudd, James; Wang, Chen; Hamidi, Habib; Fridley, Brooke L; Konecny, Gottfried E; Goode, Ellen L; Greene, Casey S; Doherty, Jennifer A
• Is Part Of: G3. Volume 6:Issue 12(2016)
• Page Start: 4097
• Page End: 4103
• Publication Date: 2016-12-01
• Subjects: ovarian cancer -- molecular subtypes -- unsupervised clustering -- reproducibility; Genetics -- Research -- Periodicals; Genomics -- Periodicals; Genetics; Genomics; Genes; Genetics -- Research; Genomics; Electronic journals; Periodical; Periodicals; Fulltext; Internet Resources; Periodicals; 572.8
• DOI: 10.1534/g3.116.033514
• Languages: English
• ISSNs: 2160-1836

Abstract

Abstract: Four gene expression subtypes of high-grade serous ovarian cancer (HGSC) have been previously described. In these early studies, a fraction of samples that did not fit well into the four subtype classifications were excluded. Therefore, we sought to systematically determine the concordance of transcriptomic HGSC subtypes across populations without removing any samples. We created a bioinformatics pipeline to independently cluster the five largest mRNA expression datasets using k -means and nonnegative matrix factorization (NMF). We summarized differential expression patterns to compare clusters across studies. While previous studies reported four subtypes, our cross-population comparison does not support four. Because these results contrast with previous reports, we attempted to reproduce analyses performed in those studies. Our results suggest that early results favoring four subtypes may have been driven by the inclusion of serous borderline tumors. In summary, our analysis suggests that either two or three, but not four, gene expression subtypes are most consistent across datasets.