Immune Cell Infiltration and Identifying Genes of Prognostic Value in the Papillary Renal Cell Carcinoma Microenvironment by Bioinformatics Analysis.

Papillary renal cell carcinoma (PRCC) is one of the most common histological subtypes of renal cell carcinoma. Type 1 and type 2 PRCC are reported to be clinically and biologically distinct. However, little is known about immune infiltration and the expression patterns of immune-related genes in the...

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Publicado en:BioMed Research International pp. 1 - 13
Autores principales: Liu, Ting, Zhang, Man, Sun, Deming
Formato: pictorial research tables/charts Journal Article
Publicado: Wiley-Blackwell 7/26/2020
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 7/26/2020
      pid: 480
      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2020/5019746
        144773669
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        atl: Immune Cell Infiltration and Identifying Genes of Prognostic Value in the Papillary Renal Cell Carcinoma Microenvironment by Bioinformatics Analysis.
      aug:
        au:
          Liu, Ting
          Zhang, Man
          Sun, Deming
        affil: Department of Nephrology, The People's Hospital of China Three Gorges University
      sug:
        subj:
          Bioinformatics
          Gene Expression Profiling
          Carcinoma, Papillary Immunology
          Carcinoma, Papillary Prognosis
          Carcinoma, Papillary Drug Therapy
          Carcinoma, Renal Cell Immunology
          Carcinoma, Renal Cell Drug Therapy
          Carcinoma, Renal Cell Prognosis
          Human
          RNA, Messenger Analysis
          Microarray Analysis
          Survival Analysis
          Macrophages Analysis
          Treatment Outcomes
          Immunotherapy Methods
      ab: Papillary renal cell carcinoma (PRCC) is one of the most common histological subtypes of renal cell carcinoma. Type 1 and type 2 PRCC are reported to be clinically and biologically distinct. However, little is known about immune infiltration and the expression patterns of immune-related genes in these two histologic subtypes, thereby limiting the development of immunotherapy for PRCC. Thus, we analyzed the expression of 22 immune cells in type 1 and type 2 PRCC tissues by combining The Cancer Genome Atlas (TCGA) database with the ESTIMATE and CIBERSORT algorithms. Subsequently, we extracted a list of differentially expressed genes associated with the immune microenvironment. Multichip mRNA microarray data sets for PRCC were downloaded from the Gene Expression Omnibus (GEO) to further validate our findings. We found that the immune scores and stromal scores were associated with overall survival in patients with type 2 PRCC rather than type 1 PRCC. Tumor-infiltrating M1 and M2 macrophages could predict the clinical outcome by reflecting the host's immune capacity against type 2 PRCC. Furthermore, CCL19/CCR7, CXCL12/CXCR4, and CCL20/CCR6 were shown to be potential new targets for tumor gene therapy in type 2 PRCC. Our findings provide valuable resources for improving immunotherapy for PRCC.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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