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TNBC organoid sc-multiome seq data treated with epigenetic drugs

GSE288798 Homo sapiens Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing 6 samples Submitted 2025/02/06 Platform GPL18573
Summary
Identifying biologically relevant signals from single-cell omics data to ultimately promote precision medicine is one current grant challenge. To address this challenge, we focused on triple-negative breast cancer (TNBC), integrated bulk and single-cell RNA-seq data from a large global population, and identified subpopulation identities that were able to provide responsive trajectories upon treatment. As a proof of principle, we applied our computational frame work on a TNBC organoid treated with two epigenetic drugs, JQ1 and MS177. We used this model to highlight how different components within the tumor responded molecularly differently to drug treatment.
Published in
Decoding drug-responsive cell subpopulations in triple-negative breast cancer using single-cell multiomics
Wang Y, Haase S, Whitman A et al. · iScience 2026 · PMID 42088352 · doi:10.1016/j.isci.2026.115445
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Also filed as BioProject PRJNA1219492 and SRA study SRP561704. Searching any of these in the dataset finder brings you back here.

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