ArticleAmerican journal of cancer research2024
A novel brown adipocytes-related gene signature predicts and validates prognosis and immune infiltration of clear cell renal cell carcinoma.
Article in American journal of cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Identification and validation of brown adipocyte-related key genes in ST-segment elevated myocardial infarction.Journal of cardiothoracic surgery · 2026Article
- Integrative immunogenomic profiling identifies CALU as a brown adipocyte-linked modulator of progression and treatment response in pancreatic cancer.Discover oncology · 2026Article
- Article
- Prognostic value of brown adipocyte-related genes in colorectal cancer: a multi-omics and Mendelian randomization study.Discover oncology · 2025Article
- Causal impact of genetically determined metabolites on kidney cancer and its subtypes: an integrated mendelian randomization and metabolomic study.American journal of cancer research · 2025Article
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3 authors.
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Abstract
backgroundClear cell renal cell carcinoma (ccRCC) is the most common kidney cancer. The crosstalk between tumor tissue and adjacent adipose tissue has been appreciated recently. This study examines the predictive usefulness of brown adipocyte-related genes (BARGs) in ccRCC.
methodsThe transcriptome and clinical data of ccRCC patients were obtained from TCGA-KIRC and USA-ccRCC cohorts (848 tumor samples; 72 normal samples). Lasso-Cox methods were used to construct the risk prognostic signature model. We used Kaplan-Meier survival analysis to evaluate the prognostic significance of the risk model with ROC curves ascertaining prediction accuracy. The differences in immune cell infiltrates and signature risk scores between different risk categories were analyzed. Finally, biological experiments were performed to explore the functions of candidate genes.
resultsTCGA-KIRC patients were classified into two clusters that differed significantly regarding overall survival (OS) and tumor microenvironment. After screening BARGs candidates, a signature consisting of PPP1R1A, DPYSL3, and PTPRM was created to calculate risk score. Patients were assigned to the high or low-risk group, and the high-risk group had a significantly worse prognosis. Consistent trend was validated in external USA-ccRCC cohort. Meanwhile, the signature risk score affected immune cell infiltrates within the ccRCC microenvironment, positively correlated with the infiltration of CD4
conclusionWe developed a predictive BARGs-related risk signature for early diagnosis and classifying ccRCC patients, which offers potential targets for individualized treatment of ccRCC.
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