Construction and Validation of a Mutation-Related Model in Papillary Renal Cell Carcinoma and Associated Immune Infiltration
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Summary
This summary is machine-generated.A new three-gene model predicts survival in papillary renal cell carcinoma (PRCC) patients. This model, using NEK2, CENPA, and GINS2, shows high expression in PRCC and aids clinical prognosis evaluation.
Area Of Science
- Oncology
- Genomics
- Biomarker Discovery
Background
- Papillary renal cell carcinoma (PRCC) prognosis evaluation needs improvement.
- Gene mutations play a role in PRCC patient survival.
Purpose Of The Study
- To develop and validate a gene-based model for predicting PRCC patient survival.
- To identify key genes and pathways associated with PRCC prognosis.
Main Methods
- Utilized TCGA RNA sequencing data for PRCC patients.
- Constructed a protein-protein interaction network and applied LASSO and Cox regression.
- Validated the model using external datasets and performed immunohistochemistry.
Main Results
- A three-gene model (NEK2, CENPA, GINS2) was developed and validated.
- Enrichment analysis indicated involvement in muscle system processes.
- CENPA expression correlated with PD-1 and CTLA4; all three genes were highly expressed in PRCC.
Conclusions
- A robust three-gene model accurately predicts PRCC patient survival.
- The model offers a valuable tool for clinical prognosis assessment.
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