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Comparative single-cell transcriptomic profiling of patient-derived renal carcinoma cells in cellular and animal models of kidney cancer

GSE272610 Homo sapiens Expression profiling by high throughput sequencing 5 samples Submitted 2025/04/22 Platform GPL24676
Summary
Clear-cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer, which is often resistant to conventional cancer therapies including chemotherapy and radiation therapy. Targeted treatments including immunotherapies and small molecule inhibitors have been recently developed with positive outcomes. However, variations in the patient response and resistance to therapies suggest that models that better recapitulate the pathogenesis and metastatic mechanisms of ccRCC are required to improve our understanding and subsequent management of ccRCC. Here, we examined the transcriptional landscapes of in vitro as well as orthotopic and metastatic NOD/SCID-γ mouse models of ccRCC using the RCC243 cell line established from the primary tumour of a patient that was diagnosed with metastatic ccRCC. Notably, RCC243 cells developed metastatic tumours using assays in mouse models, and they retained their clear-cell morphology irrespective of model type but exhibited differential gene expression profiles between models of RCC243, highlighting the impact of the cellular environment and the stage of disease progression. Furthermore, we identified prognostic markers that were conserved between RCC243 models and patient ccRCC tumour datasets and showed that genes that were upregulated in the metastatic RCC243 model were associated with worse prognosis in patients. Overall, this study presents a novel metastatic model of ccRCC, highlights the role of the cellular environment on the transcriptome, and demonstrates the importance of the choice of an experimental model.
Published in
Comparative single-cell transcriptomic profiling of patient-derived renal carcinoma cells in cellular and animal models of kidney cancer
Huang R, Kee L, Gont A et al. · FEBS open bio 2025 · PMID 40241258 · doi:10.1002/2211-5463.70022
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Direct links to NCBI, no account and no request form: the whole study as GSE272610_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 PRJNA1137423 and SRA study SRP520881. Searching any of these in the dataset finder brings you back here.

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