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Refined cellular activity expression signatures provide a targeted framework to quantify phenotypic intra-tumour heterogeneity in single-cell data II

GSE310220 Homo sapiens Expression profiling by high throughput sequencing 6 samples Submitted 2025/11/20 Platform GPL24676
Summary
Single cell RNA-seq (scRNA-seq) nowadays allows deeper insight into cellular biology at both the individual and population level. Measuring cell-to-cell variations in the population can furthermore help quantify phenotypic heterogeneity in populations in which cell states and identities deviate from healthy expectations. Cellular activities quantifiable using gene set enrichment analyses can provide useful grounds to quantify phenotypic heterogeneity, but the specificity and adequacy of existing molecular signatures scRNA-seq data is still insufficient. Here we induced 6 activities in vitro, for which we refined existing expression signatures to enhance specificity and detection: epithelial-mesenchymal transition (EMT), DNA repair, responses to interferons α and γ (IFNα and IFNγ, respectively), glycolysis, oxidative phosphorylation (OxPhos).
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Direct links to NCBI, no account and no request form: the whole study as GSE310220_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 PRJNA1365313 and SRA study SRP645543. Searching any of these in the dataset finder brings you back here.

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