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Comprehensive cross-population analysis of high-grade serous ovarian cancer supports no more than three subtypes

By Gregory P. Way, James Rudd, Chen Wang, Habib Hamidi, Brooke L. Fridley, Gottfried Konecny, Ellen L Goode, Casey S. Greene, Jennifer A Doherty

Posted 30 Oct 2015
bioRxiv DOI: 10.1101/030239 (published DOI: 10.1534/g3.116.033514)

Four gene expression subtypes of high-grade serous ovarian cancer (HGSC) have been previously described. In these 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 non-negative 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 including serous borderline tumors. In summary, our analysis suggests that either two or three, but not four, gene expression subtypes are most consistent across datasets.

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