SignificanceDespite the success of cancer immunotherapy, discovering actionable tumor antigens as immunotherapy targets remains a major challenge. Aberrant alternative splicing (AS) is widespread in cancer and generates a large repertoire of potential immunotherapy targets. However, there is no well-established strategy to discover AS-derived immunotherapy targets. We describe an integrated computational workflow for comprehensive discovery and characterization of AS-derived immunotherapy targets, leveraging large-scale RNA-seq resources of tumor and normal tissues. We demonstrate the application of this workflow for target discovery of neuroendocrine prostate cancer, a highly lethal cancer with no effective therapies. We experimentally confirm the immunogenicity and T cell recognition of AS-derived T cell receptor targets. Collectively, this work introduces a broadly applicable framework for discovering cancer immunotherapy targets arising from AS.