Open AccessIdentification of Microenvironment-Related Prognostic Genes in Bladder Cancer Based on Gene Expression Profile
Author(s) -
Yongxiang Luo,
Guohua Zeng,
Song Wu
Publication year - 2019
Publication title -
frontiers in genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.413
H-Index - 81
ISSN - 1664-8021
DOI - 10.3389/fgene.2019.01187
Subject(s) - kegg , stromal cell , bladder cancer , biology , tumor microenvironment , gene , transcriptome , cancer research , versican , thrombospondin 1 , cancer , computational biology , bioinformatics , gene expression , genetics , angiogenesis , extracellular matrix , proteoglycan
Background and Objective: Bladder cancer is the most common tumor in the urinary system, with a higher incidence in men than in women and a high recurrence rate. However, the mechanism of recurrence is still unclear, and it is urgent to clarify the pathophysiological mechanism of bladder cancer. To provide theoretical basis for the development of new therapies, investigating the effect of tumor microenvironment on the prognosis of bladder cancer is necessary. Methods: We applied the Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm to the downloaded TCGA (The Cancer Genome Atlas) transcriptome data to obtain the immune scores and stromal scores of each sample, and then divided the samples into two groups: high and low immune scores (or high and low stromal scores), and found that some differential genes were associated with poor prognosis of patients. We then performed protein-protein interaction (PPI) network analysis to explore the relationship between these differentially expressed genes. Moreover, we also performed (Gene Ontology) GO and (Kyoto Encyclopedia of Genes and Genomes) KEGG analyses to explore the potential functions of differentially expressed genes. Finally, our results were validated in an independent dataset. Results: We identified 136 tumor microenvironment-related genes associated with poor prognosis of bladder cancer. GO annotation and KEGG pathway enrichment analysis found that these genes are mainly involved in extracellular matrix, Focal adhesion and phosphatidylinositol 3 kinase-protein kinaseB (PI3k-Akt) signaling pathway. Next, PPI network analysis revealed some hub genes including Versican (VCAN), Thrombospondin 1 (THBS1) and Thrombospondin 1 (THBS2) . Finally, 27 genes were further verified in the independent data set. Conclusions: We found 27 tumor microenvironment-related genes of bladder cancer, which are associated with poor prognosis of bladder cancer. These genes may inspire researchers to develop new treatments for bladder cancer.