ArticleBMC cancer2025
Mechanisms of HRAS regulation of liver hepatocellular carcinoma for prognosis prediction.
Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Prognostic evaluation of glycolysis markers in hepatocellular carcinoma: insights from meta-analysis and multi-omics approaches.BMC medical genomics · 2025Pooled it
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9 authors.
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Abstract
backgroundLiver hepatocellular carcinoma (LIHC) often has a poor prognosis. Since the relationship between HRas proto-oncogene, GTPase (HRAS) and LIHC has not been elucidated, the aim of this study was to explore the mechanisms by which HRAS is involved in regulating the prognosis of LIHC.
methodsWe usedThe Cancer Genome Atlas (TCGA) database to characterize differences in HRAS gene expression between LIHC patients and healthy individuals. In addition, we analysed the relationships between HRAS gene expression levels and the clinicopathological characteristics of LIHC patients. Next, we used univariate and multivariate Cox regression analyses to identify prognostic factors. Differentially expressed genes were identified between the low- and high-expression groups, and KEGG and GO analyses and GSEA were performed to study the underlying mechanisms. The effects of high and low HRAS expression on the prognosis of LIHC patients was determined according to CIBERSORT. We subsequently assayed HRAS gene expression at the cellular level, and these data were validated in a tumour xenograft model.
resultsWe established and validated the HRAS gene as a prognostic signature and analysed the relationships between HRAS expression levels and clinicopathological features. Patients were categorized into high and low HRAS gene expression groups. We determined that high HRAS expression is associated with carbon metabolism, the PPAR signalling pathway, and small molecule catabolism in cancer. Furthermore, we conclude that the poor prognosis that results from elevated HRAS expression is associated with immune cell infiltration. We used LASSO + KNN to build an AI classification model that shows good performance in distinguishing liver cancer tissues form normal tissues. Finally, we verified that HRAS is highly expressed in hepatocellular carcinoma cells and promotes tumour growth.
conclusionWe identified and validated the role of HRAS in hepatocellular carcinoma to assess hepatocellular carcinoma prognosis. The results of this study can be applied to predict survival, for personalized liver cancer treatment strategies, and provide information for the development of potential targeted therapies and new ideas for liver cancer patient treatment.
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