136: Gene context drift and RECODR: predicting targets to prevent cancer relapse

Jassim A et al., Cancer Cell - This episode summarizes Jassim et al.'s introduction of RECODR, a graph-embedding pipeline that measures gene co-expression context drift from sc/snRNA-seq to reveal drivers of tumorigenesis and treatment resistance and to nominate combination therapies validated in mouse models and predicted for human tumors. Key terms: RECODR, gene context drift, single-cell RNA-seq, treatment resistance, combination therapy. Study Highlights:The authors developed RECODR, which combines co-expression graph networks with Node2Vec/Word2Vec embeddings and alignment to quantify gene context drift between treatment states. In a mouse choroid plexus carcinoma (CPC) model RECODR prioritized ATM as a vulnerability and guided use of an ATM inhibitor; it also identified PARP1 as a target to mitigate monotherapy resistance. For combination AZD1390 and radiation resistance RECODR revealed an expanded immune-like program and nominated dasatinib, which in specific combination schedules produced marked survival benefit in mice. Applied to paired human medulloblastoma and TNBC samples, RECODR detected context-drift signatures and proposed subtype-specific therapies for testing. Conclusion:Measuring changes in gene co-expression context (gene context drift) with RECODR reveals resistance mechanisms invisible to expression-level analyses and can nominate context-specific targets and combination regimens for preclinical and clinical testing. Music:Enjoy the music based on this article at the end of the episode. Article title:Gene context drift identifies drug targets to mitigate cancer treatment resistance First author:Jassim A Journal:Cancer Cell DOI:10.1016/j.ccell.2025.06.005 Reference:Jassim A, Nimmervoll BV, Terranova S, et al. Gene context drift identifies drug targets to mitigate cancer treatment resistance. Cancer Cell. 2025;43:1608–1621. doi:10.1016/j.ccell.2025.06.005 License:This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support:Base by Base is independent and ad-free — no sponsors, no paywall. If an episode was worth your time, chip in and keep the papers audited and the original songs coming:❤️ Support monthly: https://buy.stripe.com/cNifZhclVebvagk2JDgEg01☕ One-time donation: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00 More at basebybase.com On PaperCast Base by Base you'll discover the latest in genomics, functional genomics, structural genomics, and proteomics. Episode link: https://basebybase.com/episodes/gene-context-drift-identifies-drug-targets-to-mitigate-cancer-treatment-resistance QC:This episode was checked against the original article PDF and publication metadata for the episode release published on 2025-09-13. QC Scope:- article metadata and core scientific claims from the narration- excludes analogies, intro/outro, and music- transcript coverage: Audited sections include: gene context drift concept; RECODR pipeline and four context-drift metrics; single-cell RNA-seq co-expression graphs; Node2Vec/Word2Vec embedding and Procrustes alignment; CPC mouse model with AZD1390 and radiation; PARP1 inhibitor AZD9574; dasatinib targeting of an immune-like network; transl- transcript topics: Gene context drift concept; RECODR pipeline and context drift metrics; Single-cell RNA-seq and co-expression graphs; Node2Vec and Word2Vec embedding; Four context-drift metrics: neighbor number, graph reach, neighbor cosine, index gene cosine; CPC mouse model and DNA repair remodeling QC Summary:- factual score: 10/10- metadata score: 10/10- supported core claims: 6- claims flagged for review: 0- metadata checks passed: 4- meta...