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The Use of Reverse Phase Protein Arrays RPPA to Explore Protein Expression Variation within Individual Renal Cell Cancers
Published on: January 22, 2013
Bioinformatics analysis of immune-related prognostic genes and immunotherapy in renal clear cell carcinoma
Ziwen Pan1, Sheng Chang1, Song Chen1
1Institute of Organ Transplantation, Tongji Hospital, Key Laboratory of Organ Transplantation, Ministry of Education, NHC Key Laboratory of Organ Transplantation, Key Laboratory of Organ Transplantation, Chinese Academy of Medical Sciences, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Abstract:
Clear cell renal cell carcinoma (ccRCC) is an immunogenic tumor, and investigating the immunorelated genes is essential. To investigate the immunoprognostic genes of ccRCC, we analyzed the data assimilated from a public database (The Cancer Genome Atlas (TCGA) database and the gene expression omnibus (GEO) database) using bioinformatics. Then, an immunoprognosis model was constructed to identify four hub genes with moderate predictive values for the prognosis of ccRCC patients. These four genes were associated with the prognosis of ccRCC patients based on Oncomine and Gena Expression Profiling Interactive Analysis (GEPIA) databases. The correlation analysis between the immune infiltrate, immune checkpoints, and immunotherapy and this immunoprognosis model showed that immune infiltration could predict the immunotherapy effects. We also conducted a quantitative real-time polymerase chain reaction analysis and found that the expressions of three hub genes were associated with tumor progression (P<0.1). In conclusion, four genes that may serve as potential biomarkers in ccRCC were identified with respect to prognosis.
Insights
Researchers identified four key genes as potential biomarkers for clear cell renal cell carcinoma (ccRCC) prognosis. These immunorelated genes may help predict patient outcomes and immunotherapy response in ccRCC.
Area of Science:
- Oncology
- Immunology
- Bioinformatics
Background:
- Clear cell renal cell carcinoma (ccRCC) is an immunogenic tumor.
- Investigating immunorelated genes is crucial for understanding ccRCC.
- Identifying prognostic biomarkers can improve patient management.
Purpose of the Study:
- To identify immunoprognostic genes for clear cell renal cell carcinoma (ccRCC).
- To construct a predictive model for ccRCC patient prognosis.
- To explore the relationship between immune infiltration and immunotherapy response.
Main Methods:
- Bioinformatic analysis of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases.
- Construction of an immunoprognosis model to identify hub genes.
- Correlation analysis of immune infiltrate, immune checkpoints, and immunotherapy.
- Quantitative real-time polymerase chain reaction (qRT-PCR) for gene expression validation.
Main Results:
- Four hub genes with moderate predictive values for ccRCC prognosis were identified.
- These hub genes were validated using Oncomine and GEPIA databases.
- Immune infiltration was found to predict immunotherapy effects.
- Expression of three hub genes correlated with tumor progression (P<0.1).
Conclusions:
- Four potential prognostic biomarkers for clear cell renal cell carcinoma (ccRCC) were identified.
- The identified genes may aid in predicting ccRCC patient outcomes.
- The study highlights the role of immune infiltration in predicting immunotherapy efficacy.
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