Single-Cell Transcriptomic Signatures Enable Stratified Combination Therapy for Platinum-Resistant Ovarian Cancer
Year: 2026
Type: preprint
Abstract: In high-grade serous carcinoma (HGSC), extensive intra-tumoral heterogeneity hinders complete eradication and remains a major obstacle to developing combination therapies capable of eliminating subpopulations resistant to standard-of-care treatment. Using single-cell RNA sequencing of 72 samples from 54 HGSC patients spanning treatment-naïve, post-neoadjuvant chemotherapy and relapse stages, we established a carboplatin-anchored framework that identifies transcriptional signatures of intrinsic (pre-existing) and adaptive (therapy-induced) resistance in individual tumors and prioritizes mechanistically matched drugs to potentiate carboplatin efficacy. Candidate compounds were ranked by integrating orthogonal resources—viability (GDSC, PRISM) and perturbational transcriptomics (L1000, Perturb-seq)—to reduce context bias. Among 64 candidates, three carboplatin adjuvants enhanced long-term efficacy in patient-derived organoids (PDOs), and pevonedistat further significantly reduced tumor burden in orthotopic xenografts. This tiered validation pipeline—from short-term and long-term PDOs and in vivo orthoptic xenografts—establishes a translational framework linking single cell resistance programs to actionable, tumor-specific, carboplatin-anchored combinations for HGSC.
Institutions: University of Copenhagen, Haukeland University Hospital, University of Bergen, University of Helsinki, Institut Pasteur, Université Paris Cité, Centre National de la Recherche Scientifique, Sorbonne Université, LIP6, University of Turku, Turku University Hospital, Finnish Cancer Institute
Language: English
Subfield: Reproductive Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: green
Awards: Comprehensive characterization and effective combinatorial targeting of high-grade serous ovarian cancer via single-cell analysis, G7622348745, Improved clinical decisions via integrating multiple data levels to overcome chemotherapy resistance in high-grade serous ovarian cancer, G965336219
OpenAlex ID: W7134110987
