Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Tumor Immune Infiltration in Bladder Cancer

Gao-Lei Liu; Hao Luo; Dan-Dan Liang; Li Zhong; Nan Dai; Wei-Hua Lan

doi:10.2174/0115748928329276241020184935

Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Tumor Immune Infiltration in Bladder Cancer

Recent Pat Anticancer Drug Discov. 2024 Oct 29. doi: 10.2174/0115748928329276241020184935. Online ahead of print.

Authors

Gao-Lei Liu¹, Hao Luo², Dan-Dan Liang³, Li Zhong², Nan Dai², Wei-Hua Lan¹

Affiliations

¹ Department of Urology, Army Medical Center, Chongqing, 400042, China.
² Department of Oncology, Army Medical Center, Chongqing, 400042, China.
³ People's Hospital of Chong Qing Liang Jiang New Are, Chongqing, 400042, China.

PMID: 39473202
DOI: 10.2174/0115748928329276241020184935

Abstract

Background: Bladder cancer exhibits substantial heterogeneity encompassing genetic expressions and histological features. This heterogeneity is predominantly attributed to alternative splicing (AS) and AS-regulated splicing factors (SFs), which, in turn, influence bladder cancer development, progression, and response to treatment.

Objective: This study aimed to explore the immune landscape of aberrant AS in bladder cancer and establish the prognostic signatures for survival prediction.

Methods: Bladder cancer-related RNA-Seq, transcriptome, and corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA). Gene set enrichment analysis (GSEA) was used to identify significantly enriched pathways of cancer-related AS events. The underlying interactions among differentially expressed genes (DEGs) and cancer-related AS events were assessed by a protein-protein interaction network. Univariate and multivariate Cox regression analyses were performed to identify crucial prognostic DEGs that co-occurred with cancer-related AS events (DEGAS) for overall survival. The area under the curve (AUC) of receiver operating characteristic (ROC) curves was used to assess the efficiency of the prognostic signatures. The CIBERSORT algorithm was used to explore the abundance of immune infiltrating cells.

Results: A total of 3755 cancer-related AS events and 3110 DEGs in bladder cancer were identified. Among them, 379 DEGs co-occurred with cancer-related AS events (DEGAS), of which 102 DEGAS were associated with 14 dysregulated SFs. GSEA and KEGG analysis showed that cancer-related AS events were predominantly enriched in pathways related to immunity, tumorigenesis, and treatment difficulties of bladder cancer. Multivariate Cox regression analysis identified 8 DEGAS (CABP1, KCNN2, TNFRSF13B, PCDH7, SNRPA1, APOLD1, CX3CL1, and DENND5A) significantly associated with OS, and they were further integrated into the prediction model with good AUCs at 3-year, 5-year and 7-year ROC curves (all>0.7). Immune infiltration analysis revealed the significant enrichment of three immune cell types (B cells naïve, dendritic cells resting, and dendritic cell activated) in high-risk bladder cancer patients.

Conclusion: This study not only unveiled comprehensive prognostic signatures of AS events in bladder cancer but also established a robust prognostic model based on survival-related DEGAS. These aberrant AS events, dysregulated SFs, and the identified 8 DEGAS may have significant clinical potential as therapeutic targets for bladder cancer.

Keywords: Bladder cancer; alternative splicing; prognosis.; tumor immune.