A Multi-Omic Analysis of The Heterogeneity of Ovarian Carcinoma

Abstract

As part of the OvCan Initiative by Ovarian Cancer Canada, we generated a resource of multiomic data from 31 human ovarian cancer cell models spanning six histological subtypes (HGSC, CCC, MC, EC, SCCOHT, MMMT). Using RNA sequencing, TMT proteomics, and wholeexome sequencing, we systematically characterized molecular features across models to assess inter-subtype and intra-subtype variability. We demonstrate that these data capture known features of distinct ovarian cancer subtypes, including subtype-specific patterns of gene expression, pathway activation and genomic alterations. We also identify novel molecular patterns, including a partial convergence between EC and SCCOHT models possibly linked to shared SWI/SNF disruption, and concordant RNA-protein signatures highlighting candidate biomarkers and therapeutic targets. Furthermore, we highlight substantial diversity among models within individual subtypes, underscoring the importance of careful model selection in experimental design. Together, this resource will support the ovarian cancer research community by enabling subtype-specific biomarker discovery, therapeutic target identification, and informed model selection, ultimately contributing to the development of new diagnostic and therapeutic approaches.