Identification of potential biomarkers associated with immune infiltration in papillary renal cell carcinoma

Autor: Ran Deng, Jiangwei Man, Jinlong Cao, Li Yang, Jianpeng Li, Hong Zhao, Zhirui Zou
Rok vydání: 2021
Předmět:
Zdroj: Journal of Clinical Laboratory Analysis
ISSN: 1098-2825
0887-8013
DOI: 10.1002/jcla.24022
Popis: 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.
The infiltration levels of 22 immune cells in the 291 pRCC samples obtained from patients are shown in Figures A and B. Additionally, we screened the nine immune cells associated with OS via univariate Cox analysis, and the results were shown in Figure D. The immune cells associated with OS were follicular helper T cells, Macrophages M1, activated dendritic cells activated, regulatory T cells (Tregs), B‐cell memory, CD8 T cells8, macrophages M2, naïve B cells, and CD4 memory‐activated T cells. The 291patients were divided into low‐ and high‐risk groups based on the selected prognostic‐related immune cells via Multivariate Cox regression analysis.
Databáze: OpenAIRE
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