Cargando…

Development and Validation of a Hypoxia-Related Signature for Predicting Survival Outcomes in Patients With Bladder Cancer

OBJECTIVES: This study aimed to develop and validate a hypoxia signature for predicting survival outcomes in patients with bladder cancer. METHODS: We downloaded the RNA sequence and the clinicopathologic data of the patients with bladder cancer from The Cancer Genome Atlas (TCGA) (https://portal.gd...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Facai, Wang, Xiaoming, Bai, Yunjin, Hu, Huan, Yang, Yubo, Wang, Jiahao, Tang, Yin, Ma, Honggui, Feng, Dechao, Li, Dengxiong, Han, Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8188560/
https://www.ncbi.nlm.nih.gov/pubmed/34122523
http://dx.doi.org/10.3389/fgene.2021.670384
_version_ 1783705354970857472
author Zhang, Facai
Wang, Xiaoming
Bai, Yunjin
Hu, Huan
Yang, Yubo
Wang, Jiahao
Tang, Yin
Ma, Honggui
Feng, Dechao
Li, Dengxiong
Han, Ping
author_facet Zhang, Facai
Wang, Xiaoming
Bai, Yunjin
Hu, Huan
Yang, Yubo
Wang, Jiahao
Tang, Yin
Ma, Honggui
Feng, Dechao
Li, Dengxiong
Han, Ping
author_sort Zhang, Facai
collection PubMed
description OBJECTIVES: This study aimed to develop and validate a hypoxia signature for predicting survival outcomes in patients with bladder cancer. METHODS: We downloaded the RNA sequence and the clinicopathologic data of the patients with bladder cancer from The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/repository?facetTab=files) and the Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/) databases. Hypoxia genes were retrieved from the Molecular Signatures Database (https://www.gsea-msigdb.org/gsea/msigdb/index.jsp). Differentially expressed hypoxia-related genes were screened by univariate Cox regression analysis and Lasso regression analysis. Then, the selected genes constituted the hypoxia signature and were included in multivariate Cox regression to generate the risk scores. After that, we evaluate the predictive performance of this signature by multiple receiver operating characteristic (ROC) curves. The CIBERSORT tool was applied to investigate the relationship between the hypoxia signature and the immune cell infiltration, and the maftool was used to summarize and analyze the mutational data. Gene-set enrichment analysis (GSEA) was used to investigate the related signaling pathways of differentially expressed genes in both risk groups. Furthermore, we developed a model and presented it with a nomogram to predict survival outcomes in patients with bladder cancer. RESULTS: Eight genes (AKAP12, ALDOB, CASP6, DTNA, HS3ST1, JUN, KDELR3, and STC1) were included in the hypoxia signature. The patients with higher risk scores showed worse overall survival time than the ones with lower risk scores in the training set (TCGA) and two external validation sets (GSE13507 and GSE32548). Immune infiltration analysis showed that two types of immune cells (M0 and M1 macrophages) had a significant infiltration in the high-risk group. Tumor mutation burden (TMB) analysis showed that the risk scores between the wild types and the mutation types of TP53, MUC16, RB1, and FGFR3 were significantly different. Gene-Set Enrichment Analysis (GSEA) showed that immune or cancer-associated pathways belonged to the high-risk groups and metabolism-related signal pathways were enriched into the low-risk group. Finally, we constructed a predictive model with risk score, age, and stage and validated its performance in GEO datasets. CONCLUSION: We successfully constructed and validated a novel hypoxia signature in bladder cancer, which could accurately predict patients’ prognosis.
format Online
Article
Text
id pubmed-8188560
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-81885602021-06-10 Development and Validation of a Hypoxia-Related Signature for Predicting Survival Outcomes in Patients With Bladder Cancer Zhang, Facai Wang, Xiaoming Bai, Yunjin Hu, Huan Yang, Yubo Wang, Jiahao Tang, Yin Ma, Honggui Feng, Dechao Li, Dengxiong Han, Ping Front Genet Genetics OBJECTIVES: This study aimed to develop and validate a hypoxia signature for predicting survival outcomes in patients with bladder cancer. METHODS: We downloaded the RNA sequence and the clinicopathologic data of the patients with bladder cancer from The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/repository?facetTab=files) and the Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/) databases. Hypoxia genes were retrieved from the Molecular Signatures Database (https://www.gsea-msigdb.org/gsea/msigdb/index.jsp). Differentially expressed hypoxia-related genes were screened by univariate Cox regression analysis and Lasso regression analysis. Then, the selected genes constituted the hypoxia signature and were included in multivariate Cox regression to generate the risk scores. After that, we evaluate the predictive performance of this signature by multiple receiver operating characteristic (ROC) curves. The CIBERSORT tool was applied to investigate the relationship between the hypoxia signature and the immune cell infiltration, and the maftool was used to summarize and analyze the mutational data. Gene-set enrichment analysis (GSEA) was used to investigate the related signaling pathways of differentially expressed genes in both risk groups. Furthermore, we developed a model and presented it with a nomogram to predict survival outcomes in patients with bladder cancer. RESULTS: Eight genes (AKAP12, ALDOB, CASP6, DTNA, HS3ST1, JUN, KDELR3, and STC1) were included in the hypoxia signature. The patients with higher risk scores showed worse overall survival time than the ones with lower risk scores in the training set (TCGA) and two external validation sets (GSE13507 and GSE32548). Immune infiltration analysis showed that two types of immune cells (M0 and M1 macrophages) had a significant infiltration in the high-risk group. Tumor mutation burden (TMB) analysis showed that the risk scores between the wild types and the mutation types of TP53, MUC16, RB1, and FGFR3 were significantly different. Gene-Set Enrichment Analysis (GSEA) showed that immune or cancer-associated pathways belonged to the high-risk groups and metabolism-related signal pathways were enriched into the low-risk group. Finally, we constructed a predictive model with risk score, age, and stage and validated its performance in GEO datasets. CONCLUSION: We successfully constructed and validated a novel hypoxia signature in bladder cancer, which could accurately predict patients’ prognosis. Frontiers Media S.A. 2021-05-26 /pmc/articles/PMC8188560/ /pubmed/34122523 http://dx.doi.org/10.3389/fgene.2021.670384 Text en Copyright © 2021 Zhang, Wang, Bai, Hu, Yang, Wang, Tang, Ma, Feng, Li and Han. 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 Genetics
Zhang, Facai
Wang, Xiaoming
Bai, Yunjin
Hu, Huan
Yang, Yubo
Wang, Jiahao
Tang, Yin
Ma, Honggui
Feng, Dechao
Li, Dengxiong
Han, Ping
Development and Validation of a Hypoxia-Related Signature for Predicting Survival Outcomes in Patients With Bladder Cancer
title Development and Validation of a Hypoxia-Related Signature for Predicting Survival Outcomes in Patients With Bladder Cancer
title_full Development and Validation of a Hypoxia-Related Signature for Predicting Survival Outcomes in Patients With Bladder Cancer
title_fullStr Development and Validation of a Hypoxia-Related Signature for Predicting Survival Outcomes in Patients With Bladder Cancer
title_full_unstemmed Development and Validation of a Hypoxia-Related Signature for Predicting Survival Outcomes in Patients With Bladder Cancer
title_short Development and Validation of a Hypoxia-Related Signature for Predicting Survival Outcomes in Patients With Bladder Cancer
title_sort development and validation of a hypoxia-related signature for predicting survival outcomes in patients with bladder cancer
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8188560/
https://www.ncbi.nlm.nih.gov/pubmed/34122523
http://dx.doi.org/10.3389/fgene.2021.670384
work_keys_str_mv AT zhangfacai developmentandvalidationofahypoxiarelatedsignatureforpredictingsurvivaloutcomesinpatientswithbladdercancer
AT wangxiaoming developmentandvalidationofahypoxiarelatedsignatureforpredictingsurvivaloutcomesinpatientswithbladdercancer
AT baiyunjin developmentandvalidationofahypoxiarelatedsignatureforpredictingsurvivaloutcomesinpatientswithbladdercancer
AT huhuan developmentandvalidationofahypoxiarelatedsignatureforpredictingsurvivaloutcomesinpatientswithbladdercancer
AT yangyubo developmentandvalidationofahypoxiarelatedsignatureforpredictingsurvivaloutcomesinpatientswithbladdercancer
AT wangjiahao developmentandvalidationofahypoxiarelatedsignatureforpredictingsurvivaloutcomesinpatientswithbladdercancer
AT tangyin developmentandvalidationofahypoxiarelatedsignatureforpredictingsurvivaloutcomesinpatientswithbladdercancer
AT mahonggui developmentandvalidationofahypoxiarelatedsignatureforpredictingsurvivaloutcomesinpatientswithbladdercancer
AT fengdechao developmentandvalidationofahypoxiarelatedsignatureforpredictingsurvivaloutcomesinpatientswithbladdercancer
AT lidengxiong developmentandvalidationofahypoxiarelatedsignatureforpredictingsurvivaloutcomesinpatientswithbladdercancer
AT hanping developmentandvalidationofahypoxiarelatedsignatureforpredictingsurvivaloutcomesinpatientswithbladdercancer