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Transcriptomic Landscape of Hras12V Oncogene-Induced Hepatocarcinogenesis with Gender Disparity

GSE232694 Mus musculus Expression profiling by high throughput sequencing 6 samples Submitted 2024/05/18 Platform GPL17021
Summary
The genesis of hepatocellular carcinoma (HCC) is closely related to hyper-activated Ras signals and male factors. This study aimed to characterize the underlying mechanisms by examining the transcriptome of Hras12V transgenic mice (Ras-Tg, HCC model). A transcriptomic database was established via RNA-Seq of HCC (T) and the adjacent precancerous liver tissue (P) of Ras-Tg and the normal liver tissue of wild-type mice (W) of both sexes. Bioinformatics analysis as well as metabolite and gene expression assays were performed. Totally, 2708 differentially expressed genes (DEGs) were screened out (FC ≥ 2 and q < 0.05). Longitudinal comparative analysis within W, P, and T and correlation expression pattern analysis revealed common/unique cluster-enriched items towards HCC between the sexes. Specifically, the numbers of DEGs were much higher in females than in males, and tumor suppressor genes, such as p21Waf1/Cip1 and C6, were significantly higher in the female P. This finding denotes the higher sensitivity of female hepatocytes to the Ras oncogene and, therefore, the difficulty in developing HCC. Moreover, convergence in HCC between the sexes suggests the underlying mechanisms for ineffectiveness of sex hormone therapies. Additionally, expression pattern analysis revealed that the DEGs and their relevant pathways were either positively or negatively associated with the HCC/Ras oncogene. Among them, the vital role of glutathione metabolism in HCC was established. The systemic transcriptomic database of the Ras oncogene-induced HCC with sex disparities provides valuable clues for elucidating the underlying mechanisms, selecting the diagnostic biomarker, and planning the clinical therapy in HCC.
Published in
Transcriptomic landscape of Hras12V oncogene-induced hepatocarcinogenesis with gender disparity
Di H, Rong Z, Mao N et al. · BMC cancer 2025 · PMID 39819515 · doi:10.1186/s12885-025-13476-7
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Direct links to NCBI, no account and no request form: the whole study as GSE232694_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 PRJNA973591 and SRA study SRP438375. Searching any of these in the dataset finder brings you back here.

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