Identification of Immuno-infiltrating MAP1A As a Prognosis-related Biomarker for Bladder Cancer and Its CeRNA Network Construction

Backgrounds: Approximately 75% of bladder cancer occurrences are of the non-muscle-invasive type. The estimated five-year survival rate is 26%-55%. Currently, there is no reliable biomarker available for early diagnosis and prognosis of bladder cancer. The present study aims to identify a biomarker using bioinformatic approaches to provide a new insight in clinical research for early diagnosis and prognosis of bladder cancer.

Methods: Clinical data and a transcriptome of bladder cancer were obtained from TCGA, GEO, GETx, and UCSC Xena. The differential expressed gene (DEG) analysis, weighted gene co-expression network analysis (WGCNA), and survival analysis using the Kaplan-Meier and Cox proportional-hazards models were used to identify the Microtubule-associated Proteins 1A (MAP1A). on overall survival (OS) and disease-free survival (DFS) was analyzed using GEPIA and GETx databases. The TIMER 2.0 database predicted the correlation between MAP1A and immunocytes and immune checkpoints. Target prediction of the regulated competing endogenous RNAs (ceRNAs) network of MAP1A was performed using starBase and TargetScan. Cystoscope v3.7.2 software was used to visualize the ceRNA coexpression network. The R programming language v4.0.2 was applied as an analytic tool. Gene expression of MAP1A verified by RT-qPCR.

Results: The low expression of MAP1A was verified in bladder cancer tissues and bladder cancer cell lines SW780 and 5637. P < 0.001 were obtained by Kaplan-Meier survival analysis and Cox proportional hazards model, with a hazard ratio (HR) of 1.4. Significant correlations between MAP1A and OS (P < 0.001, HR = 1.9) as well as DFS (P < 0.05, HR = 1.7) in bladder cancer were identified through gene expression profiling interactive analysis (GEPIA), indicating MAP1A may be a high-risk factor. Significant correlation in single copy-number variation of MAP1A gene with CD8 T cells, and myeloid dendritic cells (MDCs) (P < 0.05) was noted. MAP1A expression was shown to be significantly correlated with the amount of CD4 T cells and CD8 T cells, MDCs, macrophages, and neutrophils in a statistically significant positive manner (P < 0.001). However, the MAP1A expression demonstrated a strong negative connection with B cells (P < 0.001). Except for macrophage M1 genes IRF5 and PTGS2, MAP1A expression was significantly correlated with the gene levels in immunocytes such as CD4 T cells, CD8 T cells, B cells, dendritic cells (DCs), macrophages, and neutrophils (Cor > 0.2, P < 0.001), as well as immune checkpoint related genes including cytotoxic t-lymphocyte-associated protein 4 (CTLA-4), programmed death 1 (PD-1), programmed death ligand 1 (PD-L1) (P < 0.001). Finally, we predicted that the MAP1A-interacting miRNA was miR-34a-5p, and the MAP1A endogenous competing RNAs were LNC00667, circ_MAP1B, and circ_MYLK, respectively. These findings support the need for further studies on the mechanism underlying the pathogenesis of this disease.

Conclusion: MAP1A is considered as a prospective biomarker for early diagnosis, therapeutic observation, and prognosis analysis in bladder cancer.