ArticleFrontiers in oncology2024
Development of prognostic signatures and risk index related to lipid metabolism in ccRCC.
Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- A multi-omics prognostic model and functional validation ofTranslational andrology and urology · 2026Article
- Neutrophil extracellular traps and metabolic reprogramming in renal cell carcinoma: implications for tumor progression and immune-based therapeutics.Cancer biology & medicine · 2025Review
- ECHS1: pathogenic mechanisms, experimental models, and emerging therapeutic strategies.Orphanet journal of rare diseases · 2025Review
- New insights into the mechanisms of the immune microenvironment and immunotherapy in osteosarcoma.Frontiers in immunology · 2024Review
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8 authors.
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Abstract
Background: Clear cell renal cell carcinoma (ccRCC) is a metabolic disorder characterized by abnormal lipid accumulation in the cytoplasm. Lipid metabolism-related genes may have important clinical significance for prognosis prediction and individualized treatment. Methods: We collected bulk and single-cell transcriptomic data of ccRCC and normal samples to identify key lipid metabolism-related prognostic signatures. qPCR was used to confirm the expression of signatures in cancer cell lines. Based on the identified signatures, we developed a lipid metabolism risk score (LMRS) as a risk index. We explored the potential application value of prognostic signatures and LMRS in precise treatment from multiple perspectives. Results: Through comprehensive analysis, we identified five lipid metabolism-related prognostic signatures (ACADM, ACAT1, ECHS1, HPGD, DGKZ). We developed a risk index LMRS, which was significantly associated with poor prognosis in patients. There was a significant correlation between LMRS and the infiltration levels of multiple immune cells. Patients with high LMRS may be more likely to respond to immunotherapy. The different LMRS groups were suitable for different anticancer drug treatment regimens. Conclusion: Prognostic signatures and LMRS we developed may be applied to the risk assessment of ccRCC patients, which may have potential guiding significance in the diagnosis and precise treatment of ccRCC patients.
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