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Molecular and functional landscape of malignant serous effusions for precision oncology [MSE_baseline]

GSE240952 Homo sapiens Expression profiling by high throughput sequencing 6 samples Submitted 2024/08/26 Platform GPL30173Platform GPL22790
Summary
Personalized treatment for patients with advanced solid tumors critically depends on the deep characterization of tumor cells. These patients frequently develop malignant serous effusions (MSE). The value of MSE-based tumor cell characterization for guiding precision oncology is, however, currently unclear. Here, we present a comprehensive characterization of a pan-cancer cohort of 150 MSE samples at the cellular, molecular, and functional level. Our integrative analysis reveals dynamic cellular heterogeneity in MSE, and uncovers links between tumor driver mutations and ex vivo growth patterns. Strong concordance between genomic and transcriptional profiles of MSE and their corresponding solid tumors validates their use as a model system for solid tumor biology. We link baseline gene expression patterns to global ex vivo drug sensitivity, and demonstrate that drug-induced transcriptional changes in MSE are highly indicative of compound mode of action. Two case studies exemplify the utility of our approach in investigating acquired resistance to targeted therapy and identifying treatment options for relapsed solid tumors. In summary, our study provides a functional multi-omics view on a pan-cancer MSE cohort and underlines the utility of MSE-based precision oncology.
Published in
Molecular and functional landscape of malignant serous effusions for precision oncology
Wegmann R, Bankel L, Festl Y et al. · Nature communications 2024 · PMID 39358333 · doi:10.1038/s41467-024-52694-8
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Direct links to NCBI, no account and no request form: the whole study as GSE240952_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 6 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1005931 and SRA study SRP455349. Searching any of these in the dataset finder brings you back here.

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