ArticleAging2021
Identification and validation of a two-gene metabolic signature for survival prediction in patients with kidney renal clear cell carcinoma.
Article in Aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- An Integrated Immunometabolic Signature Predicts Prognosis and Immunotherapy Response in ccRCC and IdentifiesCancers · 2026Article
- Identifying ADME-related gene signature for immune landscape and prognosis in KIRC by single-cell and spatial transcriptome analysis.Scientific reports · 2025Article
- Adverse event profile of lomustine and temozolomide: a descriptive analysis from WHO-VigiAccess.Frontiers in pharmacology · 2025Article
- Alpha-2-Macroglobulin and Signature Genes: Predictive Biomarkers for Prognosis and Immunotherapy in Clear Cell Renal Cell Carcinoma.Journal of Cancer · 2025Article
- Higher concentration of P7C3 than required for neuroprotection suppresses renal cell carcinoma growth and metastasis.Journal of Cancer · 2024Article
- Functional enrichment analysis of LYSET and identification of related hub gene signatures as novel biomarkers to predict prognosis and immune infiltration status of clear cell renal cell carcinoma.Journal of cancer research and clinical oncology · 2023Article
- A Cluster of Metabolic-Related Genes Serve as Potential Prognostic Biomarkers for Renal Cell Carcinoma.Frontiers in genetics · 2022Article
- Article
- Identification of Prognostic Metabolism-Related Genes in Clear Cell Renal Cell Carcinoma.Journal of oncology · 2021Article
- Identification of Prognostic Gene Signatures for Survival of Patients With Phaeochromocytoma, Paraganglioma, and Other Tumor Types.Cancer diagnosis & prognosisArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metabolic reprogramming contributes to the high mortality of advanced stage kidney renal clear cell carcinoma (KIRC), the most common renal cancer subtype. This study aimed to identify a metabolism-related gene (MRG) signature to improve survival prediction in KIRC patients. We downloaded RNA sequencing data and corresponding clinical information for KIRC and control samples from The Cancer Genome Atlas database and identified, based on an MRG dataset in the Molecular Signatures Database, 123 MRGs with differential expression in KIRC. Following Cox regression analysis and least absolute shrinkage and selection operator selection, RRM2 and ALDH6A1 were identified as prognosis-related genes and used to construct a prognostic signature with independent prognostic significance. After risk score-based patient separation, stratified survival analysis indicated that high-risk patients showed poorer overall survival than low-risk patients. We then constructed a clinical nomogram that showed a concordance index of 0.774 and good performance based upon calibration curves. Gene set enrichment analysis revealed several metabolic pathways significantly enriched in the target genes. The two-gene metabolic signature identified herein may represent a highly valuable tool for KIRC prognosis prediction, and might also help identify new metabolism-related biomarkers and therapeutic targets for KIRC.
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