SF3B1 is the most frequently mutated spliceosomal gene in cancer. Several hotspot mutations are known to disrupt the interaction of SF3B1 with another splicing factor, SUGP1, resulting in the RNA missplicing that characterizes mutant SF3B1 cancers. Properties of SUGP1, especially the presence of a G-patch motif, a structure known to function by activating DEAH-box RNA helicases, suggest the requirement of such an enzyme in SUGP1 function in splicing. However, the identity of this putative helicase has remained an important unanswered question. Here, using a variety of protein–protein interaction assays, we identify DHX15 as the critical helicase. We further show that depletion of DHX15 or expression of any of several DHX15 mutants, including one implicated in acute myeloid leukemia, partially recapitulates the splicing defects of mutant SF3B1. Moreover, a DHX15-SUGP1 G-patch fusion protein is able to incorporate into the spliceosome to rescue the splicing defects of mutant SF3B1. We also present the crystal structure of the human DHX15-SUGP1 G-patch complex, which reveals the molecular basis of their direct interaction. Our data thus demonstrate that DHX15 is the RNA helicase that functions with SUGP1 and additionally provide important insight into how mutant SF3B1 disrupts splicing in cancer.

Tumor immunotherapy has made great progress in cancer treatment but still faces several challenges, such as a limited number of targetable antigens and varying responses among patients. Alternative splicing (AS) is an essential process for the maturation of nearly all mammalian mRNAs. Recent studies show that AS contributes to expanding cancer-specific antigens and modulating immunogenicity, making it a promising solution to the above challenges. The organoid technology preserves the individual immune microenvironment and reduces the time/economic costs of the experiment model, facilitating the development of splicing-based immunotherapy. Here, we summarize three critical roles of AS in immunotherapy: resources for generating neoantigens, targets for immune-therapeutic modulation, and biomarkers to guide immunotherapy options. Subsequently, we highlight the benefits of adopting organoids to develop AS-based immunotherapies. Finally, we discuss the current challenges in studying AS-based immunotherapy in terms of existing bioinformatics algorithms and biological technologies.