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Better prediction of clinical outcome in clear cell renal cell carcinoma based on a 6 metabolism-related gene signature

Authors :
Zhixian Yu
Yating Zhan
Yong Guo
Dalin He
Source :
Scientific Reports, Vol 13, Iss 1, Pp 1-14 (2023)
Publication Year :
2023
Publisher :
Nature Portfolio, 2023.

Abstract

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.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
20452322
Volume :
13
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Scientific Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.4287019331b042aca9062c4e0a05f9d5
Document Type :
article
Full Text :
https://doi.org/10.1038/s41598-023-38380-7