Data Analysis for "Single-Cell Transcriptomic Signatures Enable Stratified Combination Therapy for Platinum-Resistant Ovarian Cancer"

This repository contains the data processing and analysis scripts used in the manuscript “Single-Cell Transcriptomic Signatures Enable Stratified Combination Therapy for Platinum-Resistant Ovarian Cancer”. Abstract In high-grade serous carcinoma (HGSC), extensive intra-tumoral heterogeneity hinders complete cancer 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 patients with HGSC, spanning treatment-naïve, post-neoadjuvant chemotherapy and relapse stages, we established a carboplatin-anchored discovery framework that identifies transcriptional signatures of both intrinsic (pre-existing) and adaptive (therapy-induced) resistance in individual tumors, and prioritizes drugs that mechanistically target these programs to potentiate carboplatin efficacy. Candidate drugs were prioritized through integration of orthogonal resources - viability (GDSC, PRISM) and perturbational transcriptomics (L1000, Perturb-seq) - to reduce context bias and identify mechanism-matched agents. Of 64 drug candidates, three carboplatin adjuvants enhanced long-term efficacy in patient-derived organoids (PDOs), with pevonedistat further significantly reducing tumor burden in orthotopic xenografts. This tiered validation pipeline, spanning 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.