Abstract 1024: CIN signatures as biomarkers of drug sensitivity: Real-world evidence from DNA targeted sequencing data

Abstract Chromosomal instability (CIN) signatures are DNA copy number-based genomic biomarkers with emerging evidence for predicting treatment sensitivity across multiple drugs and cancer types. Modern computational approaches enable the quantification of CIN signatures from clinically validated targeted DNA sequencing panels such as MSK-IMPACT. In this study, we derived copy number profiles from 63,630 tumor-normal MSK-IMPACT pairs using FACETS and computed pan-cancer CIN signatures across 73 cancer types. Analyses were restricted to pre-treatment samples, and CIN signature exposures were used to build three therapy-specific biomarkers: (i) a new biomarker of sensitivity for PARP inhibitors (PARPi) trained on progression-free survival (PFS) data from BRCA wild-type (BRCAwt) high-grade serous ovarian cancer (HGSOC) (ii) a new biomarker of sensitivity to platinum-based chemotherapies trained on disease-free survival (DFS) data from locally advanced rectal cancer (LARC) and (iii) an existing biomarker for resistance to anthracycline-based chemotherapies, now derived from targeted sequencing data for the first time. Each biomarker was validated in at least one independent MSK-IMPACT cohort of a different cancer type, using PFS calculated from treatment initiation and assessed at 12 months. The PARPi biomarker performed similarly to the Myriad MyChoice Genomic Instability Score (GIS) in identifying BRCAwt HGSOC patients with longer PFS after treatment (CIN signatures: n=84, HR=0.38, p=0.005; GIS: n=84, HR=0.41, p=0.004) and fully identified responders in an independent BRCAwt prostate adenocarcinoma (PRAD) cohort (Sensitivity 100%, Specificity 60%, AUC=0.73). The platinum biomarker predicted longer PFS in primary head and neck squamous cell carcinoma (HNSCC) (n=82, HR=0.43, p=0.007). The anthracycline biomarker predicted shorter PFS in hormone-receptor positive HER2 negative (HR+/HER2-) breast cancer - both primary (n=191, HR=1.72, p=0.015) and metastatic (n=216, HR=1.72, p=0.003) - and in primary soft-tissue sarcoma (n=251, HR = 1.81, p=0.006). These results highlight the feasibility and clinical potential of CIN signatures at a pan-cancer level, illustrating how the frequently overlooked complexity of genome-wide copy number alterations contained in routine targeted panels can be transformed into interpretable biomarkers to guide therapy selection. This proof-of-concept establishes that CIN signatures can be extracted from regulatory-approved assays such as MSK-IMPACT, although further validation is needed to facilitate clinical adoption. Citation Format: David Gómez-Sánchez, Adam Price, Max Schmidt, Sharafudeen Abubakar, Farheen Shah, Christina Lee, Chin-Tung Chen, Barbara Hernando, Daniel Muldoon, Areej Alsaafin, Evan Seffar, George Li, Subhiksha Nandakumar, Wassim Abida, Stephen Graves, Mackenzie Sullivan, Rachel N. Grisham, Britta Weigelt, Luc GT Morris, Nadeem Riaz, Pedram Razavi, Allison L. Richards, Mark Donoghue, Walid Khaled Chatila, Chaitanya Bandlamudi, Nikolaus Schultz, Michael F. Berger, Sohrab Shah, Geoff Macintyre, Julio Garcia-Aguilar, Francisco Sanchez-Vega. CIN signatures as biomarkers of drug sensitivity: Real-world evidence from DNA targeted sequencing data abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1024.