The DNA damage response in advanced ovarian cancer: functional analysis combined with machine learning identifies signatures that correlate with chemotherapy sensitivity and patient outcome

Abstract

Background: Ovarian cancers are hallmarked by chromosomal instability. New therapies deliver improved patient outcomes in relevant phenotypes, however therapy resistance and poor long-term survival signal requirements for better patient preselection. An impaired DNA damage response (DDR) is a major chemosensitivity determinant. Comprising five pathways, DDR redundancy is complex and rarely studied alongside chemoresistance influence from mitochondrial dysfunction. We developed functional assays to monitor DDR and mitochondrial states and trialled this suite on patient explants. Methods: We profiled DDR and mitochondrial signatures in cultures from 16 primary-setting ovarian cancer patients receiving platinum chemotherapy. Explant signature relationships to patient progression-free (PFS) and overall survival (OS) were assessed by multiple statistical and machine-learning methods. Results: DR dysregulation was wide-ranging. Defective HR (HRD) and NHEJ were near-mutually exclusive. HRD patients (44%) had increased SSB abrogation. HR competence was associated with perturbed mitochondria (78% vs 57% HRD) while every relapse patient harboured dysfunctional mitochondria. DDR signatures classified explant platinum cytotoxicity and mitochondrial dysregulation. Importantly, explant signatures classified patient PFS and OS. Conclusions: Whilst individual pathway scores are mechanistically insufficient to describe resistance, holistic DDR and mitochondrial states accurately predict patient survival. Our assay suite demonstrates promise for translational chemosensitivity prediction.