Abstract 6363: Predicting resistance to cytotoxic chemotherapy
Authors: Joe S. Thompson, Laura Madrid, Barbara Hernando, Carolin M. Sauer, Maria Vias, Maria Escobar-Rey, Wing-Kit Leung, Diego Garcia-Lopez, Jamie Huckstep, Magdalena Sekowska, Karen Hosking, Mercedes Jimenez-Linan, Marika A. Reinius, Abhipsa Roy, Omar Abdulle, Justina Pangonyte, Harry Dobson, Amy Cullen, Dilrini De Silva, David Gómez-Sánchez, Marina Torres, Ángel Fernández-Sanromán, Deborah Sanders, Filipe Correia Martins, Ionut-Gabriel Funingana, Giovanni Codacci-Pisanelli, Miguel Quintela-Fandino, Florian Markowetz, Jason Yip, James D. Brenton, Anna M. Piskorz, Geoff Macintyre
Journal: Cancer Research (2025)

Abstract Cytotoxic chemotherapies are typically administered without the use of precision biomarkers. As such, many patients can experience severe toxic side effects without any benefit. Here, we present a set of chromosomal instability (CIN) signature biomarkers that can identify patients resistant to platinum-, taxane-, and anthracycline-based treatment using a single genomic test. We leveraged real-world cohorts to retrospectively emulate a series of biomarker clinical trials across a total of 740 patients. In emulations where patients were pseudo-randomized to a single chemotherapy treatment arm or alternative standard-of-care arm, predicted resistant patients had increased risk of treatment failure for taxane in ovarian (HR=8.751, 95% CI=3.072-24.924), taxane in metastatic breast (HR=5.24, 95% CI=1.41-19.43), taxane in metastatic prostate (HR=4.01, 95% CI=1.73-9.27), anthracycline in ovarian (HR=2.34, 95% CI=1.25-4.59), and anthracycline in metastatic breast (HR=3.53, 95% CI=1.85-6.75). Non-randomized emulations showed predictive capacity for platinum resistance in ovarian (HR=1.65, 95% CI=1.27-2.14) and anthracycline in sarcoma (HR=3.59, 95% CI=1.19-10.81). We also demonstrate that implementation using gene capture panel sequencing of tissue or shallow whole genome sequencing of cell free DNA from liquid biopsies may be feasible. Our findings highlight the clinical value of CIN signatures in predicting resistance to various chemotherapies across multiple different types of cancer. Ultimately, this has the potential to transform the current one-size-fits-all chemotherapy approach into a more precise and tailored treatment. Citation Format: Joe S. Thompson, Laura Madrid, Barbara Hernando, Carolin M. Sauer, Maria Vias, Maria Escobar-Rey, Wing-Kit Leung, Diego Garcia-Lopez, Jamie Huckstep, Magdalena Sekowska, Karen Hosking, Mercedes Jimenez-Linan, Marika A. Reinius, Abhipsa Roy, Omar Abdulle, Justina Pangonyte, Harry Dobson, Amy Cullen, Dilrini De Silva, David Gómez-Sánchez, Marina Torres, Ángel Fernández-Sanromán, Deborah Sanders, Filipe Correia Martins, Ionut-Gabriel Funingana, Giovanni Codacci-Pisanelli, Miguel Quintela-Fandino, Florian Markowetz, Jason Yip, James D. Brenton, Anna M. Piskorz, Geoff Macintyre. Predicting resistance to cytotoxic chemotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 6363.