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Immune regulation and prognosis indicating ability of a newly constructed multi-genes containing signature in clear cell renal cell carcinoma

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common renal malignancy, although newly developing targeted therapy and immunotherapy have been showing promising effects in clinical treatment, the effective biomarkers for immune response prediction are still lacking. The study is to...

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Autores principales: Gui, Ziwei, Du, Juan, Wu, Nan, Shen, Ningning, Yang, Zhiqing, Yang, Huijun, Wang, Xuzhi, Zhao, Na, Zeng, Zixin, Wei, Rong, Ma, Wenxia, Wang, Chen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10337188/
https://www.ncbi.nlm.nih.gov/pubmed/37438709
http://dx.doi.org/10.1186/s12885-023-11150-4
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author Gui, Ziwei
Du, Juan
Wu, Nan
Shen, Ningning
Yang, Zhiqing
Yang, Huijun
Wang, Xuzhi
Zhao, Na
Zeng, Zixin
Wei, Rong
Ma, Wenxia
Wang, Chen
author_facet Gui, Ziwei
Du, Juan
Wu, Nan
Shen, Ningning
Yang, Zhiqing
Yang, Huijun
Wang, Xuzhi
Zhao, Na
Zeng, Zixin
Wei, Rong
Ma, Wenxia
Wang, Chen
author_sort Gui, Ziwei
collection PubMed
description BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common renal malignancy, although newly developing targeted therapy and immunotherapy have been showing promising effects in clinical treatment, the effective biomarkers for immune response prediction are still lacking. The study is to construct a gene signature according to ccRCC immune cells infiltration landscape, thus aiding clinical prediction of patients response to immunotherapy. METHODS: Firstly, ccRCC transcriptome expression profiles from Gene Expression Omnibus (GEO) database as well as immune related genes information from IMMPORT database were combine applied to identify the differently expressed meanwhile immune related candidate genes in ccRCC comparing to normal control samples. Then, based on protein–protein interaction network (PPI) and following module analysis of the candidate genes, a hub gene cluster was further identified for survival analysis. Further, LASSO analysis was applied to construct a signature which was in succession assessed with Kaplan–Meier survival, Cox regression and ROC curve analysis. Moreover, ccRCC patients were divided as high and low-risk groups based on the gene signature followed by the difference estimation of immune treatment response and exploration of related immune cells infiltration by TIDE and Cibersort analysis respectively among the two groups of patients. RESULTS: Based on GEO and IMMPORT databases, a total of 269 differently expressed meanwhile immune related genes in ccRCC were identified, further PPI network and module analysis of the 269 genes highlighted a 46 genes cluster. Next step, Kaplan–Meier and Cox regression analysis of the 46 genes identified 4 genes that were supported to be independent prognosis indicators, and a gene signature was constructed based on the 4 genes. Furthermore, after assessing its prognosis indicating ability by both Kaplan–Meier and Cox regression analysis, immune relation of the signature was evaluated including its association with environment immune score, Immune checkpoint inhibitors expression as well as immune cells infiltration. Together, immune predicting ability of the signature was preliminary explored. CONCLUSIONS: Based on ccRCC genes expression profiles and multiple bioinformatic analysis, a 4 genes containing signature was constructed and the immune regulation of the signature was preliminary explored. Although more detailed experiments and clinical trials are needed before potential clinical use of the signature, the results shall provide meaningful insight into further ccRCC immune researches. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11150-4.
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spelling pubmed-103371882023-07-13 Immune regulation and prognosis indicating ability of a newly constructed multi-genes containing signature in clear cell renal cell carcinoma Gui, Ziwei Du, Juan Wu, Nan Shen, Ningning Yang, Zhiqing Yang, Huijun Wang, Xuzhi Zhao, Na Zeng, Zixin Wei, Rong Ma, Wenxia Wang, Chen BMC Cancer Research BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common renal malignancy, although newly developing targeted therapy and immunotherapy have been showing promising effects in clinical treatment, the effective biomarkers for immune response prediction are still lacking. The study is to construct a gene signature according to ccRCC immune cells infiltration landscape, thus aiding clinical prediction of patients response to immunotherapy. METHODS: Firstly, ccRCC transcriptome expression profiles from Gene Expression Omnibus (GEO) database as well as immune related genes information from IMMPORT database were combine applied to identify the differently expressed meanwhile immune related candidate genes in ccRCC comparing to normal control samples. Then, based on protein–protein interaction network (PPI) and following module analysis of the candidate genes, a hub gene cluster was further identified for survival analysis. Further, LASSO analysis was applied to construct a signature which was in succession assessed with Kaplan–Meier survival, Cox regression and ROC curve analysis. Moreover, ccRCC patients were divided as high and low-risk groups based on the gene signature followed by the difference estimation of immune treatment response and exploration of related immune cells infiltration by TIDE and Cibersort analysis respectively among the two groups of patients. RESULTS: Based on GEO and IMMPORT databases, a total of 269 differently expressed meanwhile immune related genes in ccRCC were identified, further PPI network and module analysis of the 269 genes highlighted a 46 genes cluster. Next step, Kaplan–Meier and Cox regression analysis of the 46 genes identified 4 genes that were supported to be independent prognosis indicators, and a gene signature was constructed based on the 4 genes. Furthermore, after assessing its prognosis indicating ability by both Kaplan–Meier and Cox regression analysis, immune relation of the signature was evaluated including its association with environment immune score, Immune checkpoint inhibitors expression as well as immune cells infiltration. Together, immune predicting ability of the signature was preliminary explored. CONCLUSIONS: Based on ccRCC genes expression profiles and multiple bioinformatic analysis, a 4 genes containing signature was constructed and the immune regulation of the signature was preliminary explored. Although more detailed experiments and clinical trials are needed before potential clinical use of the signature, the results shall provide meaningful insight into further ccRCC immune researches. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-023-11150-4. BioMed Central 2023-07-12 /pmc/articles/PMC10337188/ /pubmed/37438709 http://dx.doi.org/10.1186/s12885-023-11150-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Gui, Ziwei
Du, Juan
Wu, Nan
Shen, Ningning
Yang, Zhiqing
Yang, Huijun
Wang, Xuzhi
Zhao, Na
Zeng, Zixin
Wei, Rong
Ma, Wenxia
Wang, Chen
Immune regulation and prognosis indicating ability of a newly constructed multi-genes containing signature in clear cell renal cell carcinoma
title Immune regulation and prognosis indicating ability of a newly constructed multi-genes containing signature in clear cell renal cell carcinoma
title_full Immune regulation and prognosis indicating ability of a newly constructed multi-genes containing signature in clear cell renal cell carcinoma
title_fullStr Immune regulation and prognosis indicating ability of a newly constructed multi-genes containing signature in clear cell renal cell carcinoma
title_full_unstemmed Immune regulation and prognosis indicating ability of a newly constructed multi-genes containing signature in clear cell renal cell carcinoma
title_short Immune regulation and prognosis indicating ability of a newly constructed multi-genes containing signature in clear cell renal cell carcinoma
title_sort immune regulation and prognosis indicating ability of a newly constructed multi-genes containing signature in clear cell renal cell carcinoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10337188/
https://www.ncbi.nlm.nih.gov/pubmed/37438709
http://dx.doi.org/10.1186/s12885-023-11150-4
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