期刊
G3-GENES GENOMES GENETICS
卷 6, 期 12, 页码 4097-4103出版社
GENETICS SOCIETY AMERICA
DOI: 10.1534/g3.116.033514
关键词
ovarian cancer; molecular subtypes; unsupervised clustering; reproducibility
资金
- National Cancer Institute at the National Institutes of Health [R01 CA168758, F31 CA186625, R01 CA122443]
- Mayo Clinic Ovarian Cancer Specialized Program of Research Excellence grant [P50 CA136393]
- Mayo Clinic Comprehensive Cancer Center-Gene Analysis Shared Resource [P30 CA15083]
- Gordon and Betty Moore Foundation's Data-Driven Discovery Initiative [GBMF 4552]
- American Cancer Society [IRG 8200327]
- Norris Cotton Cancer Center Developmental Funds
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.
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