Identification and validation of a prognostic immune-related lncRNA signature in bladder cancer

Recently, researches have implied that immune-related lncRNAs (IR-lncRNAs) have a vital role in tumor occurrence and development. However, the study in bladder cancer (Bca) is still unclear. New biomarkers and reliable prognostic models for Bca are still limited. Here, we investigated the potential application value of immune-related lncRNAs in the prognostic evaluation of Bca patients.

We obtained clinical information and corresponding sequencing data from the The Cancer Genome Atlas (TCGA) database, and the cohort of Bca patients was divided into training and validation cohorts (ratio 7:3) randomly. An immune-related lncRNA co-expression network was constructed to identify immune-related lncRNAs. The candidate module intimately associated with overall survival (OS) was identified by using weighted gene co-expression network analysis (WGCNA). Univariate, multivariate Cox regression and LASSO analysis were performed to build the immune-related lncRNA signature. A prognostic model was further developed and its prognostic value was evaluated by Kaplan-Meier (KM) analysis. GSEA, KEGG analysis and GO annotation were used for functional annotation in this study.

Totally, we identified 1,249 differentially expressed IR-lncRNAs were and six of which (AC005674.2, AC090948.1, TFAP2A-AS1, AL354919.2, AC011468.1 and AC018809.2) were finally selected in the gene signature. According to survival analysis, patients with high-risk scores were significantly related to poor survival outcomes. Furthermore, we established a novel gene signature demonstrated high prognostic value, and can be utilized as an independent risk factor (validation cohort: P<0.001, HR =3.832; training cohort: P<0.001, HR =2.843). Additionally, we built a nomogram on account of the clinicopathologic characteristics and gene signature to predict the survival probability of 1-, 3- and 5-year in Bca patients. The value of AUC curve of 1-, 3- and 5-year survival probability was 0.724, 0.777 and 0.77, severally. Furthermore, some enrichment pathways were identified by KEGG and GO analysis, and might be useful to display the potential mechanism for Bca.

Our results indicated that the signature of six immune-related lncRNAs had an underlying value in the prognosis of Bca patients and might be helpful for the immunotherapy of Bca.