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Identification of immune-related and autophagy-related genes for the prediction of survival in bladder cancer

BACKGROUND: Bladder cancer has the characteristics of high morbidity and mortality, and the prevalence of bladder cancer has been increasing in recent years. Immune and autophagy related genes play important roles in cancer, but there are few studies on their effects on the prognosis of bladder canc...

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Autores principales: Zhu, Quanfeng, Zhang, Lingdi, Deng, Yaping, Tang, Leilei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9341065/
https://www.ncbi.nlm.nih.gov/pubmed/35909123
http://dx.doi.org/10.1186/s12863-022-01073-7
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author Zhu, Quanfeng
Zhang, Lingdi
Deng, Yaping
Tang, Leilei
author_facet Zhu, Quanfeng
Zhang, Lingdi
Deng, Yaping
Tang, Leilei
author_sort Zhu, Quanfeng
collection PubMed
description BACKGROUND: Bladder cancer has the characteristics of high morbidity and mortality, and the prevalence of bladder cancer has been increasing in recent years. Immune and autophagy related genes play important roles in cancer, but there are few studies on their effects on the prognosis of bladder cancer patients. METHODS: Using gene expression data from the TCGA-BLCA database, we clustered bladder cancer samples into 6 immune-related and autophagy-related molecular subtypes with different prognostic outcomes based on 2208 immune-related and autophagy-related genes. Six subtypes were divided into two groups which had significantly different prognosis. Differential expression analysis was used to explore genes closely related to the progression of bladder cancer. Then we used Cox stepwise regression to define a combination of gene expression levels and immune infiltration indexes to construct the risk model. Finally, we built a Nomogram which consist of risk score and several other prognosis-related clinical indicators. RESULTS: The risk model suggested that high expression of C5AR2, CSF3R, FBXW10, FCAR, GHR, OLR1, PGLYRP3, RASGRP4, S100A12 was associated with poor prognosis, while high expression level of CD96, IL10, MEFV pointed to a better prognosis. Validation by internal and external dataset suggested that our risk model had a high ability to discriminate between the outcomes of patients with bladder cancer. The immunohistochemical results basically confirmed our results. The C-Index value and Calibration curves verified the robustness of Nomogram. CONCLUSIONS: Our study constructed a model that included a risk score for patients with bladder cancer, which provided a lot of helps to predict the prognosis of patients with bladder cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12863-022-01073-7.
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spelling pubmed-93410652022-08-02 Identification of immune-related and autophagy-related genes for the prediction of survival in bladder cancer Zhu, Quanfeng Zhang, Lingdi Deng, Yaping Tang, Leilei BMC Genom Data Research BACKGROUND: Bladder cancer has the characteristics of high morbidity and mortality, and the prevalence of bladder cancer has been increasing in recent years. Immune and autophagy related genes play important roles in cancer, but there are few studies on their effects on the prognosis of bladder cancer patients. METHODS: Using gene expression data from the TCGA-BLCA database, we clustered bladder cancer samples into 6 immune-related and autophagy-related molecular subtypes with different prognostic outcomes based on 2208 immune-related and autophagy-related genes. Six subtypes were divided into two groups which had significantly different prognosis. Differential expression analysis was used to explore genes closely related to the progression of bladder cancer. Then we used Cox stepwise regression to define a combination of gene expression levels and immune infiltration indexes to construct the risk model. Finally, we built a Nomogram which consist of risk score and several other prognosis-related clinical indicators. RESULTS: The risk model suggested that high expression of C5AR2, CSF3R, FBXW10, FCAR, GHR, OLR1, PGLYRP3, RASGRP4, S100A12 was associated with poor prognosis, while high expression level of CD96, IL10, MEFV pointed to a better prognosis. Validation by internal and external dataset suggested that our risk model had a high ability to discriminate between the outcomes of patients with bladder cancer. The immunohistochemical results basically confirmed our results. The C-Index value and Calibration curves verified the robustness of Nomogram. CONCLUSIONS: Our study constructed a model that included a risk score for patients with bladder cancer, which provided a lot of helps to predict the prognosis of patients with bladder cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12863-022-01073-7. BioMed Central 2022-08-01 /pmc/articles/PMC9341065/ /pubmed/35909123 http://dx.doi.org/10.1186/s12863-022-01073-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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
Zhu, Quanfeng
Zhang, Lingdi
Deng, Yaping
Tang, Leilei
Identification of immune-related and autophagy-related genes for the prediction of survival in bladder cancer
title Identification of immune-related and autophagy-related genes for the prediction of survival in bladder cancer
title_full Identification of immune-related and autophagy-related genes for the prediction of survival in bladder cancer
title_fullStr Identification of immune-related and autophagy-related genes for the prediction of survival in bladder cancer
title_full_unstemmed Identification of immune-related and autophagy-related genes for the prediction of survival in bladder cancer
title_short Identification of immune-related and autophagy-related genes for the prediction of survival in bladder cancer
title_sort identification of immune-related and autophagy-related genes for the prediction of survival in bladder cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9341065/
https://www.ncbi.nlm.nih.gov/pubmed/35909123
http://dx.doi.org/10.1186/s12863-022-01073-7
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