Alternative polyadenylation (APA) is an important posttranscriptional modification commonly involved in tumor development. However, the functional roles of APA in tumor immunity remain largely unknown. Here, we performed an in-depth analysis of the 3′UTR usage of protein-coding genes and tumor immune response in 10,303 tumor samples across 31 cancer types to develop the immune-related APA event (ImmAPA) score pipeline, an integrated algorithm to characterize the regulatory landscape of APA events in cancer immunity–related pathways. Tumor-specific ImmAPAs that strongly correlate with immune cell infiltration and immune checkpoint blockade (ICB) treatment–related biomarkers were identified. Among these ImmAPAs, the top-ranking COL1A1 3′UTR usage was strongly associated with worse prognosis and tumor immune evasion. Furthermore, a machine learning approach to construct an ICB-related ImmAPA score model predicted immunotherapy efficacy. Overall, the characterization of immune-related APA that corresponds to tumor progression and tumor immunity highlights the clinical utility of APA events as potential biomarkers in cancer immunotherapy. Significance: Elucidation of the landscape of immune-related alternative polyadenylation in cancer identifies alternative polyadenylation events that may play a role in immune modulation and immunotherapy efficacy.

中文翻译：

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癌症免疫治疗中免疫相关替代多腺苷酸化事件的表征

选择性多腺苷酸化（APA）是一种重要的转录后修饰，通常参与肿瘤的发展。然而，APA 在肿瘤免疫中的功能作用仍然很大程度上未知。在这里，我们对 31 种癌症类型的 10,303 个肿瘤样本中蛋白质编码基因的 3'UTR 使用情况和肿瘤免疫反应进行了深入分析，开发了免疫相关 APA 事件 (ImmAPA) 评分流程，这是一种集成算法描述癌症免疫相关途径中 APA 事件的监管格局。确定了与免疫细胞浸润和免疫检查点阻断 (ICB) 治疗相关生物标志物密切相关的肿瘤特异性 ImmAPA。在这些 ImmAPA 中，排名最高的 COL1A1 3'UTR 使用与较差的预后和肿瘤免疫逃避密切相关。此外，使用机器学习方法构建 ICB 相关 ImmAPA 评分模型来预测免疫治疗效果。总体而言，与肿瘤进展和肿瘤免疫相对应的免疫相关 APA 的特征突出了 APA 事件作为癌症免疫治疗中潜在生物标志物的临床效用。意义：阐明癌症中免疫相关的替代多腺苷酸化的情况，确定了可能在免疫调节和免疫治疗功效中发挥作用的替代多腺苷酸化事件。