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Identification of Survival Risk and Immune-Related Characteristics of Kidney Renal Clear Cell Carcinoma

BACKGROUND: Immunity exerts momentous functions in the progression and treatment of kidney renal clear cell carcinoma (KIRC). A better understanding of the relationship between KIRC and immunity may make a great contribution to evaluating the prognosis and immune-related therapeutic response of KIRC...

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Autores principales: Wu, Xiaobin, Liang, Yonghui, Chen, Xian, Long, Xiangyang, Xu, Wujun, Liu, Li, Wang, Binhui, Zou, Xiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273399/
https://www.ncbi.nlm.nih.gov/pubmed/35832648
http://dx.doi.org/10.1155/2022/6149369
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author Wu, Xiaobin
Liang, Yonghui
Chen, Xian
Long, Xiangyang
Xu, Wujun
Liu, Li
Wang, Binhui
Zou, Xiong
author_facet Wu, Xiaobin
Liang, Yonghui
Chen, Xian
Long, Xiangyang
Xu, Wujun
Liu, Li
Wang, Binhui
Zou, Xiong
author_sort Wu, Xiaobin
collection PubMed
description BACKGROUND: Immunity exerts momentous functions in the progression and treatment of kidney renal clear cell carcinoma (KIRC). A better understanding of the relationship between KIRC and immunity may make a great contribution to evaluating the prognosis and immune-related therapeutic response of KIRC. METHODS: A series of information such as RNA sequence, clinical data, and tumor mutation burden (TMB) of KIRC patients were downloaded through The Cancer Genome Atlas (TCGA). Next, combining the survival information and gene expression data of TCGA and Gene Expression Omnibus (GEO), we established an immune gene-related prognosis model (IGRPM) and analyzed it. Then we constructed a nomogram which was convenient for clinicians to judge the prognosis of KIRC. Last but not the least, the expressions of some genes used to construct IGRPM in early KIRC, and adjacent normal tissues were verified through real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). Perl (strawberry-perl-5.30.0.1-64bit), R software (4.0.3), and GraphPad Prism 7 were used to process the relevant data. RESULTS: The single-sample gene set enrichment analysis (ssGSEA) showed that there were significant differences in StromalScore, ImmuneScore, ESTIMATEScore, TumorPurity, 22 kinds of human immune cells infiltration, and HLA genes expression between high immunity group (Immunity_H) and low immunity group (Immunity_L). The Immunity_H expressed more immune-related genes and enriched more immune-related functions than the Immunity_L. In addition, compared with the low-risk group, the high-risk group had worse survival outcome and higher TMB. Combining IGRPM-based risk characteristic and TMB, we found that low-TMB + low-risk was the most beneficial to the survival outcome of KIRC patients. The risk characteristic based on IGRPM could be used as an independent prognostic factor for KIRC, and the nomogram constructed for evaluating the prognosis of KIRC showed excellent predictive potential. The RT-qPCR results suggested that not all the genes used to construct IGRPM showed differential expression in early KIRC compared with adjacent normal tissues, but all these genes had significant influence on the prognosis of KIRC. CONCLUSION: These comprehensive immune assessments and survival predictions, integrating multiple aspects of data and clinical information, can provide additional value to the current Tumor Node Metastasis staging system for risk stratification of KIRC and may facilitate the development of KIRC immunotherapy.
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spelling pubmed-92733992022-07-12 Identification of Survival Risk and Immune-Related Characteristics of Kidney Renal Clear Cell Carcinoma Wu, Xiaobin Liang, Yonghui Chen, Xian Long, Xiangyang Xu, Wujun Liu, Li Wang, Binhui Zou, Xiong J Immunol Res Research Article BACKGROUND: Immunity exerts momentous functions in the progression and treatment of kidney renal clear cell carcinoma (KIRC). A better understanding of the relationship between KIRC and immunity may make a great contribution to evaluating the prognosis and immune-related therapeutic response of KIRC. METHODS: A series of information such as RNA sequence, clinical data, and tumor mutation burden (TMB) of KIRC patients were downloaded through The Cancer Genome Atlas (TCGA). Next, combining the survival information and gene expression data of TCGA and Gene Expression Omnibus (GEO), we established an immune gene-related prognosis model (IGRPM) and analyzed it. Then we constructed a nomogram which was convenient for clinicians to judge the prognosis of KIRC. Last but not the least, the expressions of some genes used to construct IGRPM in early KIRC, and adjacent normal tissues were verified through real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). Perl (strawberry-perl-5.30.0.1-64bit), R software (4.0.3), and GraphPad Prism 7 were used to process the relevant data. RESULTS: The single-sample gene set enrichment analysis (ssGSEA) showed that there were significant differences in StromalScore, ImmuneScore, ESTIMATEScore, TumorPurity, 22 kinds of human immune cells infiltration, and HLA genes expression between high immunity group (Immunity_H) and low immunity group (Immunity_L). The Immunity_H expressed more immune-related genes and enriched more immune-related functions than the Immunity_L. In addition, compared with the low-risk group, the high-risk group had worse survival outcome and higher TMB. Combining IGRPM-based risk characteristic and TMB, we found that low-TMB + low-risk was the most beneficial to the survival outcome of KIRC patients. The risk characteristic based on IGRPM could be used as an independent prognostic factor for KIRC, and the nomogram constructed for evaluating the prognosis of KIRC showed excellent predictive potential. The RT-qPCR results suggested that not all the genes used to construct IGRPM showed differential expression in early KIRC compared with adjacent normal tissues, but all these genes had significant influence on the prognosis of KIRC. CONCLUSION: These comprehensive immune assessments and survival predictions, integrating multiple aspects of data and clinical information, can provide additional value to the current Tumor Node Metastasis staging system for risk stratification of KIRC and may facilitate the development of KIRC immunotherapy. Hindawi 2022-07-04 /pmc/articles/PMC9273399/ /pubmed/35832648 http://dx.doi.org/10.1155/2022/6149369 Text en Copyright © 2022 Xiaobin Wu et al. https://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
Wu, Xiaobin
Liang, Yonghui
Chen, Xian
Long, Xiangyang
Xu, Wujun
Liu, Li
Wang, Binhui
Zou, Xiong
Identification of Survival Risk and Immune-Related Characteristics of Kidney Renal Clear Cell Carcinoma
title Identification of Survival Risk and Immune-Related Characteristics of Kidney Renal Clear Cell Carcinoma
title_full Identification of Survival Risk and Immune-Related Characteristics of Kidney Renal Clear Cell Carcinoma
title_fullStr Identification of Survival Risk and Immune-Related Characteristics of Kidney Renal Clear Cell Carcinoma
title_full_unstemmed Identification of Survival Risk and Immune-Related Characteristics of Kidney Renal Clear Cell Carcinoma
title_short Identification of Survival Risk and Immune-Related Characteristics of Kidney Renal Clear Cell Carcinoma
title_sort identification of survival risk and immune-related characteristics of kidney renal clear cell carcinoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273399/
https://www.ncbi.nlm.nih.gov/pubmed/35832648
http://dx.doi.org/10.1155/2022/6149369
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