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Identification and Development of Inflammatory Response–Related Genes Signature Associated With Prognosis Evaluation and Immune Status of Bladder Cancer

Background: Bladder urothelial carcinoma (BLCA) is one of the most common malignant tumors with high morbidity and recurrence rate. The study aims to establish a prediction model to elaborate the relation between inflammatory response and prognosis of BLCA and thus to evaluate the potential prognost...

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Autores principales: Zheng, Haoxiang, Luo, Weihan, Li, Yuqing, Peng, Guoyu, Zhou, Dewang, Tang, Dongdong, Cheng, Jiwen, Wu, Song
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8927776/
https://www.ncbi.nlm.nih.gov/pubmed/35309900
http://dx.doi.org/10.3389/fcell.2022.837849
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author Zheng, Haoxiang
Luo, Weihan
Li, Yuqing
Peng, Guoyu
Zhou, Dewang
Tang, Dongdong
Cheng, Jiwen
Wu, Song
author_facet Zheng, Haoxiang
Luo, Weihan
Li, Yuqing
Peng, Guoyu
Zhou, Dewang
Tang, Dongdong
Cheng, Jiwen
Wu, Song
author_sort Zheng, Haoxiang
collection PubMed
description Background: Bladder urothelial carcinoma (BLCA) is one of the most common malignant tumors with high morbidity and recurrence rate. The study aims to establish a prediction model to elaborate the relation between inflammatory response and prognosis of BLCA and thus to evaluate the potential prognostic value of inflammatory response–related genes (IRGs) in therapeutic choices. Methods: The study utilized the gene expression profiles from the The Cancer Genome Atlas and Gene Expression Omnibus (GSE32894) datasets. Differentially expressed IRGs between normal and tumor tissues were identified, and 10 of them were correlated with overall survival (OS) (p < 0.05). Then, the LASSO–Cox regression analysis was applied to optimize the signature. RNA sequencing data of patients with BLCA from GSE32894 were applied as a validation set. Cox regression analyses of the seven-gene signature were performed to examine the efficiency of signature in predicting prognosis. Receiver operating characteristic curve analysis was applied to measure the predictive performance of the risk score for OS. Analysis of independent prognostic factors, downstream functional enrichment, drug sensitivity, and immune features were included in this study. Results: The IRG signature (LDLR, ROS1, MMP14, TNFAIP6, MYC, PTGER4, and RIPK2) was used to divide patients into high- and low-risk groups. Cox regression analyses revealed that the risk score was an independent predictive factor. Functional enrichment analysis revealed that genes were enriched in prognosis-related molecular functions and immune-related biological processes. Drug sensitivity and tumor microenvironment correlation analysis indicated that the signature was related to immunotherapy effect. Conclusion: The study defined a new prognostic signature consisting of seven IRGs, which could effectively predict the prognosis of patients with BLCA and reveal relationship of immune features in BLCA with different risk scores. The study also provided a possible indicator for targeted therapy.
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spelling pubmed-89277762022-03-18 Identification and Development of Inflammatory Response–Related Genes Signature Associated With Prognosis Evaluation and Immune Status of Bladder Cancer Zheng, Haoxiang Luo, Weihan Li, Yuqing Peng, Guoyu Zhou, Dewang Tang, Dongdong Cheng, Jiwen Wu, Song Front Cell Dev Biol Cell and Developmental Biology Background: Bladder urothelial carcinoma (BLCA) is one of the most common malignant tumors with high morbidity and recurrence rate. The study aims to establish a prediction model to elaborate the relation between inflammatory response and prognosis of BLCA and thus to evaluate the potential prognostic value of inflammatory response–related genes (IRGs) in therapeutic choices. Methods: The study utilized the gene expression profiles from the The Cancer Genome Atlas and Gene Expression Omnibus (GSE32894) datasets. Differentially expressed IRGs between normal and tumor tissues were identified, and 10 of them were correlated with overall survival (OS) (p < 0.05). Then, the LASSO–Cox regression analysis was applied to optimize the signature. RNA sequencing data of patients with BLCA from GSE32894 were applied as a validation set. Cox regression analyses of the seven-gene signature were performed to examine the efficiency of signature in predicting prognosis. Receiver operating characteristic curve analysis was applied to measure the predictive performance of the risk score for OS. Analysis of independent prognostic factors, downstream functional enrichment, drug sensitivity, and immune features were included in this study. Results: The IRG signature (LDLR, ROS1, MMP14, TNFAIP6, MYC, PTGER4, and RIPK2) was used to divide patients into high- and low-risk groups. Cox regression analyses revealed that the risk score was an independent predictive factor. Functional enrichment analysis revealed that genes were enriched in prognosis-related molecular functions and immune-related biological processes. Drug sensitivity and tumor microenvironment correlation analysis indicated that the signature was related to immunotherapy effect. Conclusion: The study defined a new prognostic signature consisting of seven IRGs, which could effectively predict the prognosis of patients with BLCA and reveal relationship of immune features in BLCA with different risk scores. The study also provided a possible indicator for targeted therapy. Frontiers Media S.A. 2022-03-03 /pmc/articles/PMC8927776/ /pubmed/35309900 http://dx.doi.org/10.3389/fcell.2022.837849 Text en Copyright © 2022 Zheng, Luo, Li, Peng, Zhou, Tang, Cheng and Wu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cell and Developmental Biology
Zheng, Haoxiang
Luo, Weihan
Li, Yuqing
Peng, Guoyu
Zhou, Dewang
Tang, Dongdong
Cheng, Jiwen
Wu, Song
Identification and Development of Inflammatory Response–Related Genes Signature Associated With Prognosis Evaluation and Immune Status of Bladder Cancer
title Identification and Development of Inflammatory Response–Related Genes Signature Associated With Prognosis Evaluation and Immune Status of Bladder Cancer
title_full Identification and Development of Inflammatory Response–Related Genes Signature Associated With Prognosis Evaluation and Immune Status of Bladder Cancer
title_fullStr Identification and Development of Inflammatory Response–Related Genes Signature Associated With Prognosis Evaluation and Immune Status of Bladder Cancer
title_full_unstemmed Identification and Development of Inflammatory Response–Related Genes Signature Associated With Prognosis Evaluation and Immune Status of Bladder Cancer
title_short Identification and Development of Inflammatory Response–Related Genes Signature Associated With Prognosis Evaluation and Immune Status of Bladder Cancer
title_sort identification and development of inflammatory response–related genes signature associated with prognosis evaluation and immune status of bladder cancer
topic Cell and Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8927776/
https://www.ncbi.nlm.nih.gov/pubmed/35309900
http://dx.doi.org/10.3389/fcell.2022.837849
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