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The impact of stroma on the discovery of molecular subtypes and prognostic gene signatures in serous ovarian cancer

By Matthew Schwede, Levi D Waldron, Samuel C. Mok, Wei Wei, Azfar Basunia, Melissa A. Merritt, Giovanni Parmigiani, David Harrington, John Quackenbush, Michael J. Birrer, Aedin C Culhane

Posted 13 Dec 2018
bioRxiv DOI: 10.1101/496406

Purpose: Recent efforts to improve outcomes for high-grade serous ovarian cancer, a leading cause of cancer death in women, have focused on identifying molecular subtypes and prognostic gene signatures, but existing subtypes have poor cross-study robustness. We tested the contribution of cell admixture in published ovarian cancer molecular subtypes and prognostic gene signatures. Experimental Design: Public gene expression data, two molecular subtype classifications, and 61 published gene signatures of ovarian cancer were examined. Using microdissected data, we developed gene signatures of ovarian tumor and stroma. Computational simulations of increasing stromal cell proportion were performed by mixing gene expression profiles of paired microdissected ovarian tumor and stroma. Results: Established ovarian cancer molecular subtypes are strongly associated with the cell admixture. Tumors were classified as different molecular subtypes in simulations when the percentage of stromal cells increased. Stromal gene expression in bulk tumor was weakly prognostic, and in one dataset, increased stroma was associated with anatomic sampling location. Five published prognostic gene signatures were no longer prognostic in a multivariate model that adjusted for stromal content alone. Conclusions: The discovery that molecular subtypes of high grade serous ovarian cancer are influenced by cell admixture, and stromal cell gene expression is crucial for interpretation and reproduction of ovarian cancer molecular subtypes and gene signatures derived from bulk tissue. Single cell analysis may be required to refine the molecular subtypes of high grade serous ovarian cancer. Because stroma proportion was weakly prognostic, elucidating the role of the tumor microenvironment's components will be important.

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