Multiple studies have identified transcriptome subtypes of high-grade serous ovarian carcinoma (HGSOC), but their interpretation and translation are complicated by tumor evolution and polyclonality accompanied by extensive accumulation of somatic aberrations, varying cell type admixtures, and different tissues of origin. In this study, we examined the chronology of HGSOC subtype evolution in the context of these factors using a novel integrative analysis of absolute copy-number analysis and gene expression in The Cancer Genome Atlas complemented by single-cell analysis of six independent tumors. Tumor purity, ploidy, and subclonality were reliably inferred from different genomic platforms, and these characteristics displayed marked differences between subtypes. Genomic lesions associated with HGSOC subtypes tended to be subclonal, implying subtype divergence at later stages of tumor evolution. Subclonality of recurrent HGSOC alterations was evident for proliferative tumors, characterized by extreme genomic instability, absence of immune infiltration, and greater patient age. In contrast, differentiated tumors were characterized by largely intact genome integrity, high immune infiltration, and younger patient age. Single-cell sequencing of 42,000 tumor cells revealed widespread heterogeneity in tumor cell type composition that drove bulk subtypes but demonstrated a lack of intrinsic subtypes among tumor epithelial cells. Our findings prompt the dismissal of discrete transcriptome subtypes for HGSOC and replacement by a more realistic model of continuous tumor development that includes mixtures of subclones, accumulation of somatic aberrations, infiltration of immune and stromal cells in proportions correlated with tumor stage and tissue of origin, and evolution between properties previously associated with discrete subtypes. SIGNIFICANCE: This study infers whether transcriptome-based groupings of tumors differentiate early in carcinogenesis and are, therefore, appropriate targets for therapy and demonstrates that this is not the case for HGSOC.
Bibliographical noteFunding Information:
L. Geistlinger was supported by a research fellowship from the German Research Foundation (GE3023/1-1 and GE3023/1-2). R.S. LaRue, C.M. Henzler, A.C. Nelson, B.J. Winterhoff, and T.K. Starr were supported by grants from the Jan Chorzempa Cancer Research Endowed Fund (to T.K. Starr), the Masonic Cancer Center's Translational Working Group Grant (to T.K. Starr), University of MN Grand Challenges grant (to B.J. Winterhoff, A.C. Nelson, and T.K. Starr), the American Cancer Society CSDG (#132574-CSDG-18-139-01-CSM to A.C. Nelson), and institutional grants to the University of Minnesota from NIH/NCI P30CA07759821 and CTSI NCATS UL1TR00249402. G. Parmigiani was supported by grant 5P30CA006516-53, and L. Waldron by grants U24CA180996 and 1R03CA191447-01A1 from the NCI of the NIH.
B.J. Winterhoff reports grants from Ovarian Cancer Research Alliance (Liz Tilberis Early Career Award) and University of Minnesota (Grand Challenges Research Program) during the conduct of the study. S.A. Mullany reports grants from OCRA during the conduct of the study. M. Morgan reports grants from US NIH during the conduct of the study. G. Parmigiani reports a patent for WO2014153442A2 Methods and systems for treatment of ovarian cancer issued. L.-X. Qin reports grants from NIH (R21 CA214845) during the conduct of the study. M. Riester is a full-time
© 2020 American Association for Cancer Research.
- Cystadenocarcinoma, Serous/genetics
- Gene Expression Profiling
- Genomic Instability
- Ovarian Neoplasms/genetics
- Single-Cell Analysis
PubMed: MeSH publication types
- Research Support, Non-U.S. Gov't
- Journal Article
- Research Support, N.I.H., Extramural