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Deciphering Immune-Associated Genes to Predict Survival in Clear Cell Renal Cell Cancer

BACKGROUND: To elucidate the correlations between tumor microenvironment and clinical characteristics as well as prognosis in clear cell renal cell cancer (ccRCC) and investigate the immune-associated genes by a comprehensive analysis of The Cancer Genome Atlas (TCGA) database. METHODS: We collected...

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Autores principales: Hu, Daixing, Zhou, Mi, Zhu, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6925759/
https://www.ncbi.nlm.nih.gov/pubmed/31886185
http://dx.doi.org/10.1155/2019/2506843
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author Hu, Daixing
Zhou, Mi
Zhu, Xin
author_facet Hu, Daixing
Zhou, Mi
Zhu, Xin
author_sort Hu, Daixing
collection PubMed
description BACKGROUND: To elucidate the correlations between tumor microenvironment and clinical characteristics as well as prognosis in clear cell renal cell cancer (ccRCC) and investigate the immune-associated genes by a comprehensive analysis of The Cancer Genome Atlas (TCGA) database. METHODS: We collected mRNA expression profiles of 537 ccRCC samples from the TCGA database. Immune scores and stromal scores were calculated by applying the ESTIMATE algorithm. We evaluated the correlation between immune/stromal scores and clinical characteristics as well as prognosis. The differentially expressed genes (DEGs) were screened between high immune/stromal score and low immune/stromal score groups by the cutoff of |log (fold change)| > 1, P value <0.05 by using package “limma” in R. Functional enrichment analysis was performed by DAVID, and the protein-protein interaction network of intersected DEGs between stromal score and immune score groups was conducted using the STRING database. The Kaplan–Meier method was used to explore DEGs with predictive values in overall survival, and the prognostic DEGs were further validated in a Gene Expression Omnibus (GEO) dataset GSE29609. RESULTS: A higher immune score was associated with T3/4 (vs. T1/2, P < 0.001), N1 (vs. N0, P=0.05), M1 (vs. M0, P=0.004), G3/4 (vs. G1/2, P < 0.001), advanced AJCC stage (P < 0.001), and shorter overall survival (P=0.04). Intersected DEGs between immune and stromal score groups were 48 upregulated and 47 downregulated genes, with 43 DEGs associated with overall survival in ccRCC. After validation by a cohort of 39 ccRCC cases with detailed follow-up information from GSE29609, six immune-associated DEGs including CASP5, HSD11B1, VSIG4, HMGCS2, HSD11B2, and OGDHL were demonstrated to be predictive of prognosis in ccRCC. CONCLUSIONS: Our study elucidated tight associations between immune score and clinical characteristics as well as prognosis in ccRCC. Moreover, six DEGs were explored and validated to exert predictive values in overall survival of ccRCC.
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spelling pubmed-69257592019-12-29 Deciphering Immune-Associated Genes to Predict Survival in Clear Cell Renal Cell Cancer Hu, Daixing Zhou, Mi Zhu, Xin Biomed Res Int Research Article BACKGROUND: To elucidate the correlations between tumor microenvironment and clinical characteristics as well as prognosis in clear cell renal cell cancer (ccRCC) and investigate the immune-associated genes by a comprehensive analysis of The Cancer Genome Atlas (TCGA) database. METHODS: We collected mRNA expression profiles of 537 ccRCC samples from the TCGA database. Immune scores and stromal scores were calculated by applying the ESTIMATE algorithm. We evaluated the correlation between immune/stromal scores and clinical characteristics as well as prognosis. The differentially expressed genes (DEGs) were screened between high immune/stromal score and low immune/stromal score groups by the cutoff of |log (fold change)| > 1, P value <0.05 by using package “limma” in R. Functional enrichment analysis was performed by DAVID, and the protein-protein interaction network of intersected DEGs between stromal score and immune score groups was conducted using the STRING database. The Kaplan–Meier method was used to explore DEGs with predictive values in overall survival, and the prognostic DEGs were further validated in a Gene Expression Omnibus (GEO) dataset GSE29609. RESULTS: A higher immune score was associated with T3/4 (vs. T1/2, P < 0.001), N1 (vs. N0, P=0.05), M1 (vs. M0, P=0.004), G3/4 (vs. G1/2, P < 0.001), advanced AJCC stage (P < 0.001), and shorter overall survival (P=0.04). Intersected DEGs between immune and stromal score groups were 48 upregulated and 47 downregulated genes, with 43 DEGs associated with overall survival in ccRCC. After validation by a cohort of 39 ccRCC cases with detailed follow-up information from GSE29609, six immune-associated DEGs including CASP5, HSD11B1, VSIG4, HMGCS2, HSD11B2, and OGDHL were demonstrated to be predictive of prognosis in ccRCC. CONCLUSIONS: Our study elucidated tight associations between immune score and clinical characteristics as well as prognosis in ccRCC. Moreover, six DEGs were explored and validated to exert predictive values in overall survival of ccRCC. Hindawi 2019-12-07 /pmc/articles/PMC6925759/ /pubmed/31886185 http://dx.doi.org/10.1155/2019/2506843 Text en Copyright © 2019 Daixing Hu et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Hu, Daixing
Zhou, Mi
Zhu, Xin
Deciphering Immune-Associated Genes to Predict Survival in Clear Cell Renal Cell Cancer
title Deciphering Immune-Associated Genes to Predict Survival in Clear Cell Renal Cell Cancer
title_full Deciphering Immune-Associated Genes to Predict Survival in Clear Cell Renal Cell Cancer
title_fullStr Deciphering Immune-Associated Genes to Predict Survival in Clear Cell Renal Cell Cancer
title_full_unstemmed Deciphering Immune-Associated Genes to Predict Survival in Clear Cell Renal Cell Cancer
title_short Deciphering Immune-Associated Genes to Predict Survival in Clear Cell Renal Cell Cancer
title_sort deciphering immune-associated genes to predict survival in clear cell renal cell cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6925759/
https://www.ncbi.nlm.nih.gov/pubmed/31886185
http://dx.doi.org/10.1155/2019/2506843
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