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
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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.

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全面分析膀胱癌肿瘤免疫浸润的预后替代剪接特征
背景:膀胱癌在遗传表达和组织学特征方面表现出很大的异质性。这种异质性主要归因于替代剪接(AS)和AS调控的剪接因子(SFs),它们反过来又影响膀胱癌的发生、发展和对治疗的反应:本研究旨在探索膀胱癌异常AS的免疫图谱,并建立预测生存的预后特征:方法:从癌症基因组图谱(TCGA)中下载膀胱癌相关的RNA-Seq、转录组和相应的临床信息。方法:从癌症基因组图谱(TCGA)中下载膀胱癌相关的RNA-Seq、转录组和相应的临床信息,利用基因组富集分析(GSEA)确定癌症相关AS事件的显著富集通路。差异表达基因(DEGs)与癌症相关强直性脊柱炎事件之间的潜在相互作用通过蛋白-蛋白相互作用网络进行评估。进行了单变量和多变量Cox回归分析,以确定与癌症相关AS事件(DEGAS)共存的对总生存至关重要的预后DEGs。接受者操作特征曲线(ROC)的曲线下面积(AUC)用于评估预后特征的效率。CIBERSORT算法用于探索免疫浸润细胞的丰度:结果:共鉴定出膀胱癌中 3755 个癌症相关 AS 事件和 3110 个 DEGs。其中,379个DEGs与癌症相关AS事件(DEGAS)共存,其中102个DEGAS与14个调控失调的SFs相关。GSEA和KEGG分析表明,癌症相关AS事件主要富集在与免疫、肿瘤发生和膀胱癌治疗困难相关的通路中。多变量Cox回归分析发现,8个DEGAS(CABP1、KCNN2、TNFRSF13B、PCDH7、SNRPA1、APOLD1、CX3CL1和DENND5A)与OS显著相关,它们被进一步整合到预测模型中,在3年、5年和7年的ROC曲线上具有良好的AUC(均大于0.7)。免疫浸润分析显示,三种免疫细胞类型(B细胞幼稚型、树突状细胞静止型和树突状细胞活化型)在高危膀胱癌患者中明显富集:这项研究不仅揭示了膀胱癌AS事件的综合预后特征,还根据与生存相关的DEGAS建立了一个稳健的预后模型。这些异常AS事件、调控失调的SFs和已确定的8个DEGAS作为膀胱癌的治疗靶点可能具有重大的临床潜力。
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