Characterization of Immune-Related Alternative Polyadenylation Events in Cancer Immunotherapy

Abstract 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.