非常规 T 细胞在泌尿系统肿瘤中:能抓住就抓住
Unconventional T cells in urological cancers: catch them if you can.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Tumor Immune Infiltration in Bladder Cancer.
Comprehensive Analysis of Prognostic Alternative Splicing Signatures in Tumor Immune Infiltration in Bladder Cancer.
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本研究不仅揭示了膀胱癌中 AS 事件的全面预后特征,还基于生存相关的 DEGAS 建立了一个稳健的预后模型。这些异常 AS 事件、失调的 SF 以及所识别的 8 个 DEGAS 可能作为膀胱癌的治疗靶点具有重要的临床潜力。
膀胱癌在基因表达和组织学特征方面表现出显著的异质性。这种异质性主要归因于可变剪接(AS)和AS调控的剪接因子(SFs),进而影响膀胱癌的发生、进展和治疗反应。
本研究旨在探索膀胱癌中异常AS的免疫景观,并建立用于生存预测的预后特征。
膀胱癌相关的RNA-Seq、转录组及相应临床信息从癌症基因组图谱(TCGA)下载。基因集富集分析(GSEA)用于识别癌症相关AS事件的显著富集通路。通过蛋白质-蛋白质相互作用网络评估差异表达基因(DEGs)与癌症相关AS事件之间的潜在相互作用。进行单因素和多因素Cox回归分析,以识别与癌症相关AS事件共发生的关键预后DEGs(DEGAS)对总生存期的影响。受试者工作特征(ROC)曲线的曲线下面积(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。
在膀胱癌中,共鉴定出3755个癌症相关AS事件和3110个DEGs。其中,379个DEGs与癌症相关AS事件共发生(DEGAS),其中102个DEGAS与14个失调的SFs相关。GSEA和KEGG分析显示,癌症相关AS事件主要富集于与膀胱癌免疫、肿瘤发生和治疗困难相关的通路。多因素Cox回归分析鉴定出8个DEGAS(CABP1、KCNN2、TNFRSF13B、PCDH7、SNRPA1、APOLD1、CX3CL1和DENND5A)与OS显著相关,并进一步将其整合到预测模型中,在3年、5年和7年ROC曲线中均具有良好的AUCs(均>0.7)。免疫浸润分析显示,三种免疫细胞类型(B cells naïve、dendritic cells resting和dendritic cell activated)在高风险膀胱癌患者中显著富集。
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.
This study aimed to explore the immune landscape of aberrant AS in bladder cancer and establish the prognostic signatures for survival prediction.
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.
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.
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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