AUTHOR=Cai Dawei , Zhou Zhongbao , Wei Guangzhu , Wu Peishan , Kong Guangqi 

TITLE=Construction and verification of a novel hypoxia-related lncRNA signature related with survival outcomes and immune microenvironment of bladder urothelial carcinoma by weighted gene co-expression network analysis

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.952369

DOI=10.3389/fgene.2022.952369

ISSN=1664-8021

ABSTRACT=Bladder urothelial carcinoma (BLCA) is one of the most common malignant tumors and has the highest recurrence rate among all solid tumors. Hypoxia plays an important role in the development and immune escape of malignant tumors. It is necessary to establish a hypoxia-related long non-coding RNAs (HRlncRNAs) signature to predict clinical outcomes and immune microenvironment of patients with BLCA. We obtained the differentially expressed profile of HRlncRNAs and clinical data of patients with BLCA from The Cancer Genome Atlas (TCGA), and we performed weighted gene co-expression network analysis (WGCNA) to determine gene modules correlated with tumors. Finally, HRlncRNAs comprising 13 lncRNAs was identified to involved in the prognostic signature via the univariate and multivariate Cox regression analysis. Patients were divided into low- and high-risk groups according to the median of risk score in the training, testing and overall cohorts. Kaplan-Meier curves showed that the prognosis of patients in the high-risk group was poor, and the difference between subgroups was statistically significant. Receiver Operating Characteristic curves showed that the predictive ability of this signature was more accurate than traditional evaluation methods. Multivariate Cox regression analysis showed that the signature was an independent risk factor for overall survival (HR=1.411, 95%CI=1.259-1.582, P<0.001). Based on the HRlncRNAs signature and clinical features, a predictive nomogram was constructed. The nomogram can accurately predict the overall survival of patients, and it has high clinical practicability through stratification analysis and clinical influence analysis. The KEGG analysis showed that primary pathways were WNT, MAPK and ERBB signaling pathways. Additionally, we found two groups had a significant distinct pattern of immune function, immune checkpoint, immune infiltration and m6A, which may lead to different survival benefits. We then validated the differential expression of signature-related genes between tumors and normal tissues using TCGA paired data. In short, the 13 HRlncRNAs and their signature are accurate, reliable tools for predicting survival outcomes and immune microenvironment of patients with BLCA, which may be molecular biomarkers and therapeutic targets.