Cavallaro, U. | Search bioRxiv

bioRxiv2018

A cell-of-origin epigenetic tracer reveals clinically distinct subtypes of high grade serous ovarian cancer

High grade serous ovarian cancer (HGSOC) is a major unmet need in oncology. The persistent uncertainty on its originating tissue has contributed to hamper the discovery of oncogenic pathways and effective therapies. Here we define the DNA methylation print that distinguishes the human fimbrial (FI) and ovarian surface epithelia (OSE) and develop a robust epigenetic cell-of-origin tracer that stratifies HGSOC in FI-and OSE-originated tumors across all available cohorts. We translate this origin-based stratification into a clinically actionable transcriptomic signature, demonstrating its prognostic impact on patients survival and identifying novel network level dysregulations specific for the two disease subtypes.

cancer biology↗

bioRxiv2018

Single cell derived organoids capture the self-renewing subpopulations of metastatic ovarian cancer

High Grade Serous Ovarian cancer (HGSOC) is a major unmet need in oncology, due to its precocious dissemination and the lack of meaningful human models for the investigation of disease pathogenesis in a patient-specific manner. To overcome this roadblock, we present a new method to isolate and grow single cells directly from patients ascites, establishing the conditions for propagating them as single-cell derived ovarian cancer organoids (scOCOs). By single cell RNA sequencing (scRNAseq) we define the cellular composition of metastatic ascites and trace its propagation in 2D and 3D culture paradigms, finding that scOCOs retain and amplify key subpopulations from the original patients samples and recapitulate features of the original metastasis that do not emerge from classical 2D culture, including retention of individual patients specificities. By enabling the enrichment of uniquely informative cell subpopulations from HGSOC metastasis and the clonal interrogation of their diversity at the functional and molecular level, this method transforms the prospects of precision oncology for ovarian cancer.

cancer biology↗