Xu Qianhui, Xu Hao, Deng Rongshan, Li Nanjun, Mu Ruiqi, Qi Zhixuan, Shen Yunuo, Wang Zijie, Wen Jingchao, Zhao Jiaxin, Weng Di, Huang Wen
The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, No 109. Xueyuan West Road, Wenzhou, 325000, Zhejiang, China.
Zhejiang University School of Medicine, Hangzhou, 310009, Zhejiang, China.
Cancer Cell Int. 2021 Apr 1;21(1):190. doi: 10.1186/s12935-021-01894-z.
Hepatocellular carcinoma (HCC) ranks the sixth prevalent tumors with high mortality globally. Alternative splicing (AS) drives protein diversity, the imbalance of which might act an important factor in tumorigenesis. This study aimed to construct of AS-based prognostic signature and elucidate the role in tumor immune microenvironment (TIME) and immunotherapy in HCC.
Univariate Cox regression analysis was performed to determine the prognosis-related AS events and gene set enrichment analysis (GSEA) was employed for functional annotation, followed by the development of prognostic signatures using univariate Cox, LASSO and multivariate Cox regression. K-M survival analysis, proportional hazards model, and ROC curves were conducted to validate prognostic value. ESTIMATE R package, ssGSEA algorithm and CIBERSORT method and TIMER database exploration were performed to uncover the context of TIME in HCC. Quantitative real-time polymerase chain reaction was implemented to detect ZDHHC16 mRNA expression. Cytoscape software 3.8.0 were employed to visualize AS-splicing factors (SFs) regulatory networks.
A total of 3294 AS events associated with survival of HCC patients were screened. Based on splicing subtypes, eight AS prognostic signature with robust prognostic predictive accuracy were constructed. Furthermore, quantitative prognostic nomogram was developed and exhibited robust validity in prognostic prediction. Besides, the consolidated signature was significantly correlated with TIME diversity and ICB-related genes. ZDHHC16 presented promising prospect as prognostic factor in HCC. Finally, the splicing regulatory network uncovered the potential functions of splicing factors (SFs).
Herein, exploration of AS patterns may provide novel and robust indicators (i.e., risk signature, prognostic nomogram, etc.,) for prognostic prediction of HCC. The AS-SF networks could open up new approach for investigation of potential regulatory mechanisms. And pivotal players of AS events in context of TIME and immunotherapy efficiency were revealed, contributing to clinical decision-making and personalized prognosis monitoring of HCC.
肝细胞癌(HCC)是全球第六大常见肿瘤,死亡率很高。可变剪接(AS)驱动蛋白质多样性,其失衡可能是肿瘤发生的重要因素。本研究旨在构建基于AS的预后特征,并阐明其在HCC肿瘤免疫微环境(TIME)和免疫治疗中的作用。
进行单变量Cox回归分析以确定与预后相关的AS事件,并采用基因集富集分析(GSEA)进行功能注释,随后使用单变量Cox、LASSO和多变量Cox回归开发预后特征。进行K-M生存分析、比例风险模型和ROC曲线以验证预后价值。使用ESTIMATE R包、ssGSEA算法、CIBERSORT方法和TIMER数据库探索来揭示HCC中TIME的情况。实施定量实时聚合酶链反应以检测ZDHHC16 mRNA表达。使用Cytoscape软件3.8.0可视化AS剪接因子(SFs)调控网络。
共筛选出3294个与HCC患者生存相关的AS事件。基于剪接亚型,构建了8个具有强大预后预测准确性的AS预后特征。此外,开发了定量预后列线图,并在预后预测中表现出强大的有效性。此外,整合特征与TIME多样性和ICB相关基因显著相关。ZDHHC16作为HCC的预后因素具有广阔前景。最后,剪接调控网络揭示了剪接因子(SFs)的潜在功能。
在此,对AS模式的探索可能为HCC的预后预测提供新的、强大的指标(即风险特征、预后列线图等)。AS-SF网络可为潜在调控机制的研究开辟新途径。并且揭示了AS事件在TIME和免疫治疗效率方面的关键作用,有助于HCC的临床决策和个性化预后监测。