ArticleScientific reports2023
Better prediction of clinical outcome in clear cell renal cell carcinoma based on a 6 metabolism-related gene signature.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 5 citations in OpenAlex.
- ITPKA promotes invasive phenotypes in clear cell renal cell carcinoma through functional modulation of PPAR signaling.American journal of cancer research · 2026Article
- The key enzyme PYCR1 in proline metabolism: a dual driver of cancer progression and fibrotic remodeling.Journal of enzyme inhibition and medicinal chemistry · 2025Review
- Bioinformatics and machine learning reveal novel prognostic biomarkers in head and neck squamous cell carcinoma.Journal of applied genetics · 2025Article
- An immunometabolism-related signature for renal clear cell carcinoma diagnosis and therapeutic target.Journal of cell communication and signaling · 2025Article
- Integrative Analysis of Immune- and Metabolism-Related Genes Identifies Robust Prognostic Signature and PYCR1 as a Carcinogenic Regulator in Clear Cell Renal Cell Carcinoma.International journal of molecular sciences · 2025Article
- Prediction of prognosis and immunotherapy response of tryptophan metabolism genes in acute myeloid leukemia.Frontiers in pharmacology · 2025Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It has been reported that metabolic disorders participate in the formation and progression of clear cell renal cell carcinoma (ccRCC). However, the predictive value of metabolism-related genes (MRGs) in clinical outcome of ccRCC is still largely unknown. Herein, a novel metabolism-related signature was generated to assess the effect of MRGs on the prognosis of ccRCC patients. Important module MRGs were selected by differentially expressed analysis and WGCNA. Subsequently, the hub MRGs were screened via univariate cox regression as well as LASSO regression. A new metabolism-related signature of 6 hub MRGs (PAFAH2, ACADSB, ACADM, HADH, PYCR1 and ITPKA) was constructed, with a good prognostic prediction ability in the TCGA cohort. The prediction accuracy of this signature was further confirmed in both GSE22541 and FAHWMU cohort. Interestingly, this MRG risk signature was highly correlated with tumor mutation burden and immune infiltration in ccRCC. Notably, lower PAFAH2, a member of 6 MRGs, was found in ccRCC. Knockdown of PAFAH2 contributed to renal cancer cell proliferation and migration. Collectively, a 6-MRG prognostic risk signature is generated to estimate the prognostic status of ccRCC patients, providing a novel insight in the prognosis prediction and treatment of ccRCC.
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