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Heritable states influence stem cell fates upon acquisition of cancer mutations [Second]

GSE282755 Mus musculus Expression profiling by high throughput sequencing 5 samples Submitted 2025/04/30 Platform GPL24247
Summary
Tumors with the same driver mutations can display a striking variation in their progression and treatment response, but the origins of this variation are still unclear. In this study, we use state-fate analysis to unveil that heritable stem cell states can influence how individual cells respond to the acquisition of the same cancer mutation. We develop a new methodological pipeline, single-cell Tracking of Recombinase Activation And Clonal Kinetics, and apply it to hematopoietic stem cells carrying Cre/Flp-conditional leukemia alleles. Tracking the gene expression changes and expansion kinetics of a common set of stem cell clones, with and without the same myeloid leukemia mutations, we unveil a striking heterogeneity in the malignant fates of diverse stem cells. First, we define that heritable clonal states persist in expansion cultures and cause the selection of a small group of clones with a specific fitness signature. Then, using mouse models of the most frequent initiating mutations, we define that these pre-existent stem cell states influence the mutation-induced changes in expansion, fate, and malignant gene expression programs. Initiating driver mutations increase the survival probability of clones with low fitness through enhancing their stemness programs. Surprisingly, the fate of high-fitness stem-cell clones is sometimes reversed, producing more mature leukemias, yet still carrying markers of their cell of origin. We further validate these HSC-of-origin signatures in bulk and single-cell RNAseq datasets from cancer patients. Our findings suggest that aggressive premalignant clonal expansions arise from low-fitness stem cells more frequently than previously expected.
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Direct links to NCBI, no account and no request form: the whole study as GSE282755_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 5 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1190370 and SRA study SRP547388. Searching any of these in the dataset finder brings you back here.

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