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Updated: Oct 18, 2025
The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers
Published on: January 22, 2013
Identification of potential biomarkers associated with immune infiltration in papillary renal cell carcinoma
Ran Deng1,2,3, Jianpeng Li1,2,3, Hong Zhao1,2,3
1Department of Urology, Lanzhou University Second Hospital, Lanzhou, China.
Background:
Immunotherapeutic approaches have recently emerged as effective treatment regimens against various types of cancer. However, the immune-mediated mechanisms surrounding papillary renal cell carcinoma (pRCC) remain unclear. This study aimed to investigate the tumor microenvironment (TME) and identify the potential immune-related biomarkers for pRCC.
Methods:
The CIBERSORT algorithm was used to calculate the abundance ratio of immune cells in each pRCC samples. Univariate Cox analysis was used to select the prognostic-related tumor-infiltrating immune cells (TIICs). Multivariate Cox regression analysis was performed to develop a signature based on the selected prognostic-related TIICs. Then, these pRCC samples were divided into low- and high-risk groups according to the obtained signature. Analyses using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) were performed to investigate the biological function of the DEGs (differentially expressed genes) between the high- and low-risk groups. The hub genes were identified using a weighted gene co-expression network analysis (WGCNA) and a protein-protein interaction (PPI) analysis. The hub genes were subsequently validated by multiple clinical traits and databases.
Results:
According to our analyses, nine immune cells play a vital role in the TME of pRCC. Our analyses also obtained nine potential immune-related biomarkers for pRCC, including TOP2A, BUB1B, BUB1, TPX2, PBK, CEP55, ASPM, RRM2, and CENPF.
Conclusion:
In this study, our data revealed the crucial TIICs and potential immune-related biomarkers for pRCC and provided compelling insights into the pathogenesis and potential therapeutic targets for pRCC.
Insights
This study identifies key immune cells and nine immune-related biomarkers for papillary renal cell carcinoma (pRCC), offering insights into its tumor microenvironment and potential therapeutic targets.
Area of Science:
- Oncology
- Immunology
- Bioinformatics
Background:
- Immunotherapy is a promising cancer treatment, but its mechanisms in papillary renal cell carcinoma (pRCC) are not fully understood.
- Investigating the tumor microenvironment (TME) is crucial for understanding pRCC pathogenesis.
Purpose of the Study:
- To elucidate the immune cell composition within the pRCC tumor microenvironment.
- To identify novel immune-related biomarkers for pRCC prognosis and treatment.
Main Methods:
- CIBERSORT algorithm to quantify immune cell abundance in pRCC samples.
- Univariate and multivariate Cox regression analyses to identify prognostic tumor-infiltrating immune cells (TIICs) and develop a risk signature.
- Gene Ontology, KEGG, GSEA, WGCNA, and PPI analyses to explore biological functions and identify hub genes.
Main Results:
- Nine immune cells were identified as critical players in the pRCC TME.
- Nine potential immune-related biomarkers for pRCC were discovered: TOP2A, BUB1B, BUB1, TPX2, PBK, CEP55, ASPM, RRM2, and CENPF.
Conclusions:
- The study highlights significant TIICs and potential immune biomarkers for pRCC.
- Findings provide valuable insights into pRCC pathogenesis and suggest potential therapeutic strategies.
