Abstract B016: Clonal evolution and structural variation drive chemotherapy resistance in ovarian carcinoma

Abstract High-grade serous ovarian carcinoma (HGSC) is a leading cause of gynecologic cancer death, driven by frequent recurrence and resistance to platinum therapies. Uncovering the mechanisms behind this process requires integrating genomic and transcriptional changes in space and time. Here, we present an evolutionary analysis combining multisite phylogenetic trees with transcriptomics, focusing on copy-number (CN) and structural variation (SV) to identify events that shape HGSC progression and treatment resistance. To address the changes during chemotherapy, we first reconstructed tumor phylogenies from 236 whole-genome–sequenced samples derived from 60 patients with relapsed HGSC using PyClone. Patients were stratified according to changes in mutational burden between diagnosis and relapse, as well as by clonal selection patterns, distinguishing cases of monoclonal versus multiclonal relapses. To extend the analysis beyond point mutations, CN and SV profiles were decomposed into clonal profiles within the phylogenetic framework, using a customized implementation of ALPACA. In parallel, matched bulk RNA-seq was integrated to connect relapse-specific genomic alterations with transcriptional changes and pathway deregulation, thereby uncovering pathways and processes underlying chemotherapy resistance. We observed that patients with a single dominant clone at relapse had significantly worse post-relapse survival compared with those exhibiting intra-sample clonal heterogeneity (p = 0.015). Across the cohort, clonal complexity, quantified as the geometric mean of within-sample subclonal heterogeneity per timepoint, showed a marked decline at relapse (p < 0.001). Since this cancer is driven by chromosomal instability, we next characterized CN segmentation and SV breakpoints, which were both significantly increased in relapse samples (p_CN = 0.004, p_SV = 0.006). Together, these results demonstrate structural remodeling rather than mutational burden as a defining feature of treatment resistance that underlies aggressive recurrences. Accordingly, we identified relapse-specific subclonal events as putative drivers of tumor progression during therapy, with impacts on pathways such as MAPK. Integration with matched transcriptomic samples enabled assessment of the functional impact of these events on gene expression and pathway activity. These findings show structural variation as a key driver of HGSC treatment resistance. By linking clonal genomic alterations with transcriptomic consequences, our approach uncovered relapse-specific drivers and opens new avenues for biomarker discovery and therapeutic targeting. Citation Format: Giulia Micoli, Jaana Oikkonen, Kari Lavikka, Déborah Boyenval, Johanna Hynninen, Sampsa Hautaniemi. Clonal evolution and structural variation drive chemotherapy resistance in ovarian carcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Cancer Evolution: The Dynamics of Progression and Persistence; 2025 Dec 4-6; Albuquerque, NM. Philadelphia (PA): AACR; Cancer Res 2025;85(23_Suppl):Abstract nr B016.