Identification of prognostic biomarkers associated with stromal cell infiltration in muscle‐invasive bladder cancer by bioinformatics analyses

Abstract Muscle‐invasive bladder cancer (MIBC) is one of the common malignant tumors. Patients with MIBC still have high tumor recurrence and progression rates after surgery. Bioinformatics analysis of stromal infiltration‐related genes in the tumor microenvironment (TME) of MIBC patients was perfor...

Full description

Bibliographic Details
Main Authors: Pan Li, Jinlong Cao, Jianpeng Li, Zhiqiang Yao, Dali Han, Lijun Ying, Zhiping Wang, Junqiang Tian
Format: Article
Language:English
Published: Wiley 2020-10-01
Series:Cancer Medicine
Subjects:
Online Access:https://doi.org/10.1002/cam4.3372
id doaj-96785c364287491a98be01d88ced1121
record_format Article
spelling doaj-96785c364287491a98be01d88ced11212020-11-25T03:51:56ZengWileyCancer Medicine2045-76342020-10-019197253726710.1002/cam4.3372Identification of prognostic biomarkers associated with stromal cell infiltration in muscle‐invasive bladder cancer by bioinformatics analysesPan Li0Jinlong Cao1Jianpeng Li2Zhiqiang Yao3Dali Han4Lijun Ying5Zhiping Wang6Junqiang Tian7Department of Urology Lanzhou University Second Hospital Lanzhou ChinaDepartment of Urology Lanzhou University Second Hospital Lanzhou ChinaDepartment of Urology Lanzhou University Second Hospital Lanzhou ChinaDepartment of Urology Lanzhou University Second Hospital Lanzhou ChinaDepartment of Urology Lanzhou University Second Hospital Lanzhou ChinaDepartment of Urology Lanzhou University Second Hospital Lanzhou ChinaDepartment of Urology Lanzhou University Second Hospital Lanzhou ChinaDepartment of Urology Lanzhou University Second Hospital Lanzhou ChinaAbstract Muscle‐invasive bladder cancer (MIBC) is one of the common malignant tumors. Patients with MIBC still have high tumor recurrence and progression rates after surgery. Bioinformatics analysis of stromal infiltration‐related genes in the tumor microenvironment (TME) of MIBC patients was performed in this study to determine the major stromal cells types and biomarkers for their progression and poor prognosis. The ESTIMATE algorithm was applied to evaluate the stromal score and immune score of samples from MIBC patients in The Cancer Genome Atlas (TCGA) and found that stromal score was closely related to the clinical characteristics of the patients. The Gene Set Enrichment Analysis (GSEA) further revealed that stromal cells were involved in biological processes such as activation of leukocytes and positive regulation of cell migration during MIBC progression, as well as PI3K‐Akt, MAPK, and Rap1 signaling pathways. Five hub genes related to prognosis, including ACTA2, COL5A1, DCN, LUM, and PRRX1 were identified by the Weighted Gene Co‐Expression Network Analysis (WGCNA), Protein‐Protein Interaction (PPI), survival analysis, and Oncomine, Gene Expression Omnibus (GEO) database validation. Besides, we identified five stromal cell types associated with overall survival time, among which chondrocytes and fibroblasts were identified as the major stromal cell types through correlation analysis. Finally, the Receiver Operating Characteristic (ROC) curve and immunohistochemistry were used to verify the diagnostic value and expression of hub genes in different invasive tumors. In summary, we investigated the biological behavior of stromal cells in the TME of MIBC to promote tumor progression obtained hub genes associated with progression and poor prognosis and identified the main stromal cells types in the TME.https://doi.org/10.1002/cam4.3372bioinformaticshub genesmuscle‐invasive bladder cancerstromal cellstumor microenvironment
collection DOAJ
language English
format Article
sources DOAJ
author Pan Li
Jinlong Cao
Jianpeng Li
Zhiqiang Yao
Dali Han
Lijun Ying
Zhiping Wang
Junqiang Tian
spellingShingle Pan Li
Jinlong Cao
Jianpeng Li
Zhiqiang Yao
Dali Han
Lijun Ying
Zhiping Wang
Junqiang Tian
Identification of prognostic biomarkers associated with stromal cell infiltration in muscle‐invasive bladder cancer by bioinformatics analyses
Cancer Medicine
bioinformatics
hub genes
muscle‐invasive bladder cancer
stromal cells
tumor microenvironment
author_facet Pan Li
Jinlong Cao
Jianpeng Li
Zhiqiang Yao
Dali Han
Lijun Ying
Zhiping Wang
Junqiang Tian
author_sort Pan Li
title Identification of prognostic biomarkers associated with stromal cell infiltration in muscle‐invasive bladder cancer by bioinformatics analyses
title_short Identification of prognostic biomarkers associated with stromal cell infiltration in muscle‐invasive bladder cancer by bioinformatics analyses
title_full Identification of prognostic biomarkers associated with stromal cell infiltration in muscle‐invasive bladder cancer by bioinformatics analyses
title_fullStr Identification of prognostic biomarkers associated with stromal cell infiltration in muscle‐invasive bladder cancer by bioinformatics analyses
title_full_unstemmed Identification of prognostic biomarkers associated with stromal cell infiltration in muscle‐invasive bladder cancer by bioinformatics analyses
title_sort identification of prognostic biomarkers associated with stromal cell infiltration in muscle‐invasive bladder cancer by bioinformatics analyses
publisher Wiley
series Cancer Medicine
issn 2045-7634
publishDate 2020-10-01
description Abstract Muscle‐invasive bladder cancer (MIBC) is one of the common malignant tumors. Patients with MIBC still have high tumor recurrence and progression rates after surgery. Bioinformatics analysis of stromal infiltration‐related genes in the tumor microenvironment (TME) of MIBC patients was performed in this study to determine the major stromal cells types and biomarkers for their progression and poor prognosis. The ESTIMATE algorithm was applied to evaluate the stromal score and immune score of samples from MIBC patients in The Cancer Genome Atlas (TCGA) and found that stromal score was closely related to the clinical characteristics of the patients. The Gene Set Enrichment Analysis (GSEA) further revealed that stromal cells were involved in biological processes such as activation of leukocytes and positive regulation of cell migration during MIBC progression, as well as PI3K‐Akt, MAPK, and Rap1 signaling pathways. Five hub genes related to prognosis, including ACTA2, COL5A1, DCN, LUM, and PRRX1 were identified by the Weighted Gene Co‐Expression Network Analysis (WGCNA), Protein‐Protein Interaction (PPI), survival analysis, and Oncomine, Gene Expression Omnibus (GEO) database validation. Besides, we identified five stromal cell types associated with overall survival time, among which chondrocytes and fibroblasts were identified as the major stromal cell types through correlation analysis. Finally, the Receiver Operating Characteristic (ROC) curve and immunohistochemistry were used to verify the diagnostic value and expression of hub genes in different invasive tumors. In summary, we investigated the biological behavior of stromal cells in the TME of MIBC to promote tumor progression obtained hub genes associated with progression and poor prognosis and identified the main stromal cells types in the TME.
topic bioinformatics
hub genes
muscle‐invasive bladder cancer
stromal cells
tumor microenvironment
url https://doi.org/10.1002/cam4.3372
work_keys_str_mv AT panli identificationofprognosticbiomarkersassociatedwithstromalcellinfiltrationinmuscleinvasivebladdercancerbybioinformaticsanalyses
AT jinlongcao identificationofprognosticbiomarkersassociatedwithstromalcellinfiltrationinmuscleinvasivebladdercancerbybioinformaticsanalyses
AT jianpengli identificationofprognosticbiomarkersassociatedwithstromalcellinfiltrationinmuscleinvasivebladdercancerbybioinformaticsanalyses
AT zhiqiangyao identificationofprognosticbiomarkersassociatedwithstromalcellinfiltrationinmuscleinvasivebladdercancerbybioinformaticsanalyses
AT dalihan identificationofprognosticbiomarkersassociatedwithstromalcellinfiltrationinmuscleinvasivebladdercancerbybioinformaticsanalyses
AT lijunying identificationofprognosticbiomarkersassociatedwithstromalcellinfiltrationinmuscleinvasivebladdercancerbybioinformaticsanalyses
AT zhipingwang identificationofprognosticbiomarkersassociatedwithstromalcellinfiltrationinmuscleinvasivebladdercancerbybioinformaticsanalyses
AT junqiangtian identificationofprognosticbiomarkersassociatedwithstromalcellinfiltrationinmuscleinvasivebladdercancerbybioinformaticsanalyses
_version_ 1724485496044781568