Gene context drift identifies drug targets to mitigate cancer treatment resistance

Amir Jassim; Birgit V Nimmervoll; Sabrina Terranova; Erica Nathan; Linda Hu; Jessica T Taylor; Katherine E Masih; Lisa Ruff; Matilde Duarte; Elizabeth Cooper; Gunjan Katyal; Melika Akhbari; Reuben J Gilbertson; Jennifer C Coleman; Joseph S Toker; Colton Terhune; Gabriel Balmus; Stephen P Jackson; Hailong Liu; Tao Jiang; Michael D Taylor; Kui Hua; Jean E Abraham; Mariella G Filbin; Anthony Hill; Anarita Patrizi; Neil Dani; Aviv Regev; Maria K Lehtinen; Richard J Gilbertson

doi:10.1016/j.ccell.2025.06.005

Gene context drift identifies drug targets to mitigate cancer treatment resistance

Cancer Cell. 2025 Jun 20:S1535-6108(25)00255-7. doi: 10.1016/j.ccell.2025.06.005. Online ahead of print.

Authors

Amir Jassim¹, Birgit V Nimmervoll², Sabrina Terranova², Erica Nathan², Linda Hu², Jessica T Taylor², Katherine E Masih³, Lisa Ruff², Matilde Duarte², Elizabeth Cooper², Gunjan Katyal², Melika Akhbari², Reuben J Gilbertson², Jennifer C Coleman², Joseph S Toker², Colton Terhune², Gabriel Balmus⁴, Stephen P Jackson², Hailong Liu⁵, Tao Jiang⁶, Michael D Taylor⁷, Kui Hua², Jean E Abraham⁸, Mariella G Filbin⁹, Anthony Hill¹⁰, Anarita Patrizi¹⁰, Neil Dani¹¹, Aviv Regev¹², Maria K Lehtinen⁹, Richard J Gilbertson¹³

Affiliations

¹ Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK. Electronic address: amir.jassim@cruk.cam.ac.uk.
² Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK.
³ Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK; Genetics Branch, Center for Cancer Research, National Cancer Institute, NIH, Bethseda, MD 20892, USA.
⁴ UK Dementia Research Institute at the University of Cambridge and Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0AH, UK; Department of Molecular Neuroscience, Transylvanian Institute of Neuroscience, 400191 Cluj-Napoca, Romania.
⁵ Department of Radiotherapy, Beijing Tiantan Hospital Capital Medical University, Beijing 100070, China.
⁶ Department of Pediatric Neurosurgery, Beijing Tiantan Hospital Capital Medical University, Beijing 100070, China.
⁷ Texas Children's Cancer and Hematology Center, Houston, TX 77030, USA; Department of Pediatrics, Hematology/Oncology, Baylor College of Medicine, Houston, TX 77030, USA; Department of Neurosurgery, Baylor College of Medicine, Houston, TX 77030, USA; Department of Neurosurgery, Texas Children's Hospital, Houston, TX 77030, USA; Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA.
⁸ Department of Oncology, University of Cambridge, Box 197 Cambridge Biomedical Campus, Cambridge CB2 0XZ, UK; Precision Breast Cancer Institute, Box 197 Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK.
⁹ Boston Children's Hospital, 300 Longwood Avenue, Boston, MA 02115, USA.
¹⁰ Schaller Research Group, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany.
¹¹ Department of Cell and Developmental Biology, Vanderbilt School of Medicine, Nashville, TN 37232, USA.
¹² Broad Institute of MIT and Harvard, Cambridge, MA, USA.
¹³ Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK; Department of Oncology, University of Cambridge, Box 197 Cambridge Biomedical Campus, Cambridge CB2 0XZ, UK. Electronic address: richard.gilbertson@cruk.cam.ac.uk.

PMID: 40578362
DOI: 10.1016/j.ccell.2025.06.005

Abstract

Cancer treatment often fails because combinations of different therapies evoke complex resistance mechanisms that are hard to predict. We introduce REsistance through COntext DRift (RECODR): a computational pipeline that combines co-expression graph networks of single-cell RNA sequencing profiles with a graph-embedding approach to measure changes in gene co-expression context during cancer treatment. RECODR is based on the idea that gene co-expression context, rather than expression level alone, reveals important information about treatment resistance. Analysis of tumors treated in preclinical and clinical trials using RECODR unmasked resistance mechanisms -invisible to existing computational approaches- enabling the design of highly effective combination treatments for mice with choroid plexus carcinoma, and the prediction of potential new treatments for patients with medulloblastoma and triple-negative breast cancer. Thus, RECODR may unravel the complexity of cancer treatment resistance by detecting context-specific changes in gene interactions that determine the resistant phenotype.

Keywords: DNA repair; cancer; choroid plexus; choroid plexus carcinoma; combination therapy; graph networks; machine learning; radiation; treatment resistance; triple-negative breast cancer.