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Association of CXCL13 and Immune Cell Infiltration Signature in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is one of the most commonly diagnosed kidney tumors and is often accompanied by immune cell infiltration. In this study, we attempted to identify microenvironment-associated genes and explore the correlation between CXCL13 and tumor-infiltrating immune cells (...

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Autores principales: Jiao, Fangdong, Sun, Hao, Yang, Qingya, Sun, Hui, Wang, Zehua, Liu, Ming, Chen, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7359384/
https://www.ncbi.nlm.nih.gov/pubmed/32669964
http://dx.doi.org/10.7150/ijms.46874
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author Jiao, Fangdong
Sun, Hao
Yang, Qingya
Sun, Hui
Wang, Zehua
Liu, Ming
Chen, Jun
author_facet Jiao, Fangdong
Sun, Hao
Yang, Qingya
Sun, Hui
Wang, Zehua
Liu, Ming
Chen, Jun
author_sort Jiao, Fangdong
collection PubMed
description Clear cell renal cell carcinoma (ccRCC) is one of the most commonly diagnosed kidney tumors and is often accompanied by immune cell infiltration. In this study, we attempted to identify microenvironment-associated genes and explore the correlation between CXCL13 and tumor-infiltrating immune cells (TIICs). Gene expression profiles and their corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. The ESTIMATE (Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data) algorithm was used to calculate immune cell and stromal cell scores, according to which patients were divided into high- and low-score groups, allowing differentially expressed genes (DEGs) to be identified. Functional enrichment and PPI network analysis were used to identify the functions of the DEGs. CIBERSORT algorithm and TIMER analysis were used to evaluate the immune score. Oncomine and TCGA database were used to explore CXCL13 mRNA expression level in ccRCC. High ESTIMATE score was significantly associated with prognosis. Functional enrichment analysis clarified that DEGs were associated with T cell activation, immune response-regulating cell surface receptor signaling pathway, and positive regulation of cytokine production. PPI network was used to identify CXCL13 as a hub gene. And CIBERSORT algorithm and TIMER analysis showed that strong correlation between CXCL13 expression level and TIICs. Oncomine database was used to validate high CXCL13 expression level in ccRCC tissue, compared to normal tissues. In conclusion, we obtained a list of tumor microenvironment-related genes and identified CXCL13 as an immune response biomarker in patients with ccRCC, GSEA analysis, wound healing and transwell assays showed CXCL13 played a role in tumor migration.
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spelling pubmed-73593842020-07-14 Association of CXCL13 and Immune Cell Infiltration Signature in Clear Cell Renal Cell Carcinoma Jiao, Fangdong Sun, Hao Yang, Qingya Sun, Hui Wang, Zehua Liu, Ming Chen, Jun Int J Med Sci Research Paper Clear cell renal cell carcinoma (ccRCC) is one of the most commonly diagnosed kidney tumors and is often accompanied by immune cell infiltration. In this study, we attempted to identify microenvironment-associated genes and explore the correlation between CXCL13 and tumor-infiltrating immune cells (TIICs). Gene expression profiles and their corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. The ESTIMATE (Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data) algorithm was used to calculate immune cell and stromal cell scores, according to which patients were divided into high- and low-score groups, allowing differentially expressed genes (DEGs) to be identified. Functional enrichment and PPI network analysis were used to identify the functions of the DEGs. CIBERSORT algorithm and TIMER analysis were used to evaluate the immune score. Oncomine and TCGA database were used to explore CXCL13 mRNA expression level in ccRCC. High ESTIMATE score was significantly associated with prognosis. Functional enrichment analysis clarified that DEGs were associated with T cell activation, immune response-regulating cell surface receptor signaling pathway, and positive regulation of cytokine production. PPI network was used to identify CXCL13 as a hub gene. And CIBERSORT algorithm and TIMER analysis showed that strong correlation between CXCL13 expression level and TIICs. Oncomine database was used to validate high CXCL13 expression level in ccRCC tissue, compared to normal tissues. In conclusion, we obtained a list of tumor microenvironment-related genes and identified CXCL13 as an immune response biomarker in patients with ccRCC, GSEA analysis, wound healing and transwell assays showed CXCL13 played a role in tumor migration. Ivyspring International Publisher 2020-06-27 /pmc/articles/PMC7359384/ /pubmed/32669964 http://dx.doi.org/10.7150/ijms.46874 Text en © The author(s) This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
spellingShingle Research Paper
Jiao, Fangdong
Sun, Hao
Yang, Qingya
Sun, Hui
Wang, Zehua
Liu, Ming
Chen, Jun
Association of CXCL13 and Immune Cell Infiltration Signature in Clear Cell Renal Cell Carcinoma
title Association of CXCL13 and Immune Cell Infiltration Signature in Clear Cell Renal Cell Carcinoma
title_full Association of CXCL13 and Immune Cell Infiltration Signature in Clear Cell Renal Cell Carcinoma
title_fullStr Association of CXCL13 and Immune Cell Infiltration Signature in Clear Cell Renal Cell Carcinoma
title_full_unstemmed Association of CXCL13 and Immune Cell Infiltration Signature in Clear Cell Renal Cell Carcinoma
title_short Association of CXCL13 and Immune Cell Infiltration Signature in Clear Cell Renal Cell Carcinoma
title_sort association of cxcl13 and immune cell infiltration signature in clear cell renal cell carcinoma
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7359384/
https://www.ncbi.nlm.nih.gov/pubmed/32669964
http://dx.doi.org/10.7150/ijms.46874
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