Transcriptome-based network analysis related to regulatory T cells infiltration identified RCN1 as a potential biomarker for prognosis in clear cell renal cell carcinoma
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View abstract on PubMed
Summary
This summary is machine-generated.Regulatory T cells (Tregs) are key in kidney cancer. This study identifies RCN1 as a prognostic biomarker for clear cell renal cell carcinoma (ccRCC) by analyzing Treg infiltration and developing a predictive model.
Area Of Science
- Oncology
- Immunology
- Genomics
Background
- Regulatory T cells (Tregs) significantly influence the tumor microenvironment's immunosuppressive nature.
- Understanding Treg roles in clear cell renal cell carcinoma (ccRCC) is vital for discovering prognostic markers and therapeutic strategies.
Purpose Of The Study
- To investigate the prognostic significance of Treg infiltration in ccRCC.
- To identify potential biomarkers for ccRCC prognosis and therapeutic targeting.
Main Methods
- Weighted gene co-expression network analysis (WGCNA) identified Treg-related gene modules in TCGA-KIRC data.
- Consensus clustering defined two ccRCC clusters based on Treg infiltration.
- A 7-gene prognostic model was developed and validated for ccRCC overall survival prediction.
Main Results
- Two distinct ccRCC clusters based on Treg infiltration showed differences in immune microenvironment, pathway activation, prognosis, and drug sensitivity.
- A 7-gene risk score model accurately predicted ccRCC prognosis in training and validation cohorts.
- RCN1 was identified as a reliable prognostic factor, predominantly expressed in tumor cells, and linked to poor prognosis across multiple cancers.
Conclusions
- A prognostic model linked to Treg infiltration aids in ccRCC clinical stratification.
- RCN1 demonstrates significant potential as a valuable biomarker for ccRCC.
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