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Single cell RNA-seq of oxaliplatin resistant HCT116 cells

GSE299427 Homo sapiens Expression profiling by high throughput sequencing 4 samples Submitted 2025/07/23 Platform GPL15433
Summary
Drug resistance and distant metastases are leading causes of mortality in colorectal cancer (CRC), yet the molecular mechanisms linking these processes remain elusive. In this study, we demonstrate that acquired resistance to oxaliplatin, a first-line chemotherapeutic in CRC, enhances metastatic potential through transcriptional reprogramming. Using a clinically relevant dosing regimen, we generated oxaliplatin-resistant CRC cells that displayed increased metastatic potential. Integrated transcriptomic and phenotypic analyses revealed that dysregulated cholesterol biogenesis amplifies TGF-beta signaling, which in turn drives expression of SERPINE1, that serves as a key effector of both oxaliplatin resistance and metastasis. Furthermore, we uncovered a SERPINE1-associated nine-gene expression signature, RESIST-M, that robustly predicts overall and relapse-free survival across distinct patient cohorts. Notably, RESIST-M stratifies a high-risk subtype of CMS4/iCMS3-fibrotic patients that display the poorest prognosis, underscoring its clinical relevance. Targeting of SERPINE1 or cholesterol biosynthesis re-sensitized resistant, pro-metastatic cells to oxaliplatin in mouse xenograft models. Altogether, this study uncovers a mechanistic link between metabolic rewiring and transcriptional plasticity underlying therapy-induced metastasis in primary CRC. Additionally, it also reveals actionable vulnerabilities that offer both prognostic value and therapeutic potential.
Published in
Modeling oxaliplatin resistance in colorectal cancer reveals a SERPINE1-based gene signature (RESIST-M) and therapeutic strategies for pro-metastatic CMS4 subtype
Wong SQR, Das M, Tenzin K et al. · Cell death & disease 2025 · PMID 40664638 · doi:10.1038/s41419-025-07855-y
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Direct links to NCBI, no account and no request form: the whole study as GSE299427_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 4 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1274413 and SRA study SRP591032. Searching any of these in the dataset finder brings you back here.

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