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Transcriptomic analysis of tumor self-seeded cells, primary tumor cells, and circulating tumor cells in liver cancer

GSE232386 Homo sapiens Expression profiling by high throughput sequencing 8 samples Submitted 2024/06/24 Platform GPL24676
Summary
Recent studies have indicated a multi-directional seeding of circulating tumor cells (CTCs). Apart from seeding to distant tissues (cancer metastases), CTCs can also reinfiltrate and colonize already established tumors. This process of “tumor self-seeding” provides new insights into the dynamics of tumor progression, and has been indicated to promote tumor growth, angiogenesis, and invasion. Thus, therapeutic targeting of tumor self-seeded cells (TSCs) may provide effective strategies for preventing tumor progression. However, TSCs have not been well identified and characterized due to unsuitable animal models. Therefore, this study aims to develop a novel animal model to recapitulate the process of tumor self-seeding and characterize the transcriptional and functional profiles of TSCs in liver cancer. Using our tumor self-seeding model, TSCs, primary tumor cells (PCs), and CTCs were identified and isolated by fluorescence-activated cell sorting (FACS). RNA sequencing of the purified cells identified TSCs as a subpopulation of PCs. Further analyses showed that TSCs were enriched with gene sets of cancer metastasis and invasiveness, suggesting TSCs may provide novel cell targets with diagnostic, prognostic, or therapeutic potential.
Published in
Identification and characterization of TM4SF1(+) tumor self-seeded cells
Yang H, Wang H, He Y et al. · Cell reports 2024 · PMID 39003738 · doi:10.1016/j.celrep.2024.114512
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Direct links to NCBI, no account and no request form: the whole study as GSE232386_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 8 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA971901 and SRA study SRP437371. Searching any of these in the dataset finder brings you back here.

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