Identification and Development of Inflammatory Response-Related Genes Signature Associated With Prognosis Evaluation and Immune Status of Bladder Cancer

Haoxiang Zheng; Weihan Luo; Yuqing Li; Guoyu Peng; Dewang Zhou; Dongdong Tang; Jiwen Cheng; Song Wu

doi:10.3389/fcell.2022.837849

Identification and Development of Inflammatory Response-Related Genes Signature Associated With Prognosis Evaluation and Immune Status of Bladder Cancer

Front Cell Dev Biol. 2022 Mar 3:10:837849. doi: 10.3389/fcell.2022.837849. eCollection 2022.

Authors

Haoxiang Zheng^{1

2

3}, Weihan Luo^{1

2}, Yuqing Li^{1

2}, Guoyu Peng², Dewang Zhou^{2

4}, Dongdong Tang^{2

5}, Jiwen Cheng³, Song Wu^{1

2

6}

Affiliations

¹ Luohu Clinical Medicine School, Shantou University Medical College, Shantou University, Shantou, China.
² Institute of Urology, The Third Affiliated Hospital of Shenzhen University (Luohu Hospital Group), Shenzhen University, Shenzhen, China.
³ Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
⁴ Kobilka Institute of Innovative Drug Discovery, School of Life and Health Sciences, Chinese University of Hong Kong, Shenzhen, China.
⁵ Department of Urology, Lanzhou University Second Hospital, Lanzhou, China.
⁶ Health Science Center, South China Hospital, Shenzhen University, Shenzhen, China.

Abstract

Background: Bladder urothelial carcinoma (BLCA) is one of the most common malignant tumors with high morbidity and recurrence rate. The study aims to establish a prediction model to elaborate the relation between inflammatory response and prognosis of BLCA and thus to evaluate the potential prognostic value of inflammatory response-related genes (IRGs) in therapeutic choices. Methods: The study utilized the gene expression profiles from the The Cancer Genome Atlas and Gene Expression Omnibus (GSE32894) datasets. Differentially expressed IRGs between normal and tumor tissues were identified, and 10 of them were correlated with overall survival (OS) (p < 0.05). Then, the LASSO-Cox regression analysis was applied to optimize the signature. RNA sequencing data of patients with BLCA from GSE32894 were applied as a validation set. Cox regression analyses of the seven-gene signature were performed to examine the efficiency of signature in predicting prognosis. Receiver operating characteristic curve analysis was applied to measure the predictive performance of the risk score for OS. Analysis of independent prognostic factors, downstream functional enrichment, drug sensitivity, and immune features were included in this study. Results: The IRG signature (LDLR, ROS1, MMP14, TNFAIP6, MYC, PTGER4, and RIPK2) was used to divide patients into high- and low-risk groups. Cox regression analyses revealed that the risk score was an independent predictive factor. Functional enrichment analysis revealed that genes were enriched in prognosis-related molecular functions and immune-related biological processes. Drug sensitivity and tumor microenvironment correlation analysis indicated that the signature was related to immunotherapy effect. Conclusion: The study defined a new prognostic signature consisting of seven IRGs, which could effectively predict the prognosis of patients with BLCA and reveal relationship of immune features in BLCA with different risk scores. The study also provided a possible indicator for targeted therapy.

Keywords: bladder cancer; drug sensitivity; immune status; inflammatory response; prognosis; tumor microenvironment.