IRIS: Discovery of cancer immunotherapy targets arising from pre-mRNA alternative splicing

Yang Pan(Children's Hospital of Philadelphia), John W. Phillips(University of California, Los Angeles), Beatrice Zhang(Children's Hospital of Philadelphia), Miyako Noguchi(University of California, Los Angeles), Eric Kutschera(Children's Hospital of Philadelphia), Jami McLaughlin(University of California, Los Angeles), Pavlo A. Nesterenko(University of California, Los Angeles), Zhiyuan Mao(University of California, Los Angeles), Nathanael J. Bangayan(University of California, Los Angeles), Robert Wang(Children's Hospital of Philadelphia), Wendy Tran(University of California, Los Angeles), Harry Yang(University of California, Los Angeles), Yuanyuan Wang(Children's Hospital of Philadelphia), Yang Xu(Children's Hospital of Philadelphia), Matthew B. Obusan(University of California, Los Angeles), Donghui Cheng(University of California, Los Angeles), Alex Lee(University of California, Los Angeles), Kathryn E. Kadash-Edmondson(Children's Hospital of Philadelphia), Ameya S. Champhekar(University of California, Los Angeles), Cristina Puig-Saus(University of California, Los Angeles), Antoni Ribas(University of California, Los Angeles), Robert M. Prins(University of California, Los Angeles), Christopher S. Seet(University of California, Los Angeles), Gay M. Crooks(University of California, Los Angeles), Owen N. Witte(University of California, Los Angeles), Yi Xing(Children's Hospital of Philadelphia)
Proceedings of the National Academy of Sciences
May 16, 2023
10.1073/pnas.2221116120
Cited by 48Open Access
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Abstract

creening (IRIS), a computational platform capable of discovering AS-derived tumor antigens (TAs) for T cell receptor (TCR) and chimeric antigen receptor T cell (CAR-T) therapies. IRIS leverages large-scale tumor and normal transcriptome data and incorporates multiple screening approaches to discover AS-derived TAs with tumor-associated or tumor-specific expression. In a proof-of-concept analysis integrating transcriptomics and immunopeptidomics data, we showed that hundreds of IRIS-predicted TCR targets are presented by human leukocyte antigen (HLA) molecules. We applied IRIS to RNA-seq data of neuroendocrine prostate cancer (NEPC). From 2,939 NEPC-associated AS events, IRIS predicted 1,651 epitopes from 808 events as potential TCR targets for two common HLA types (A*02:01 and A*03:01). A more stringent screening test prioritized 48 epitopes from 20 events with "neoantigen-like" NEPC-specific expression. Predicted epitopes are often encoded by microexons of ≤30 nucleotides. To validate the immunogenicity and T cell recognition of IRIS-predicted TCR epitopes, we performed in vitro T cell priming in combination with single-cell TCR sequencing. Seven TCRs transduced into human peripheral blood mononuclear cells (PBMCs) showed high activity against individual IRIS-predicted epitopes, providing strong evidence of isolated TCRs reactive to AS-derived peptides. One selected TCR showed efficient cytotoxicity against target cells expressing the target peptide. Our study illustrates the contribution of AS to the TA repertoire of cancer cells and demonstrates the utility of IRIS for discovering AS-derived TAs and expanding cancer immunotherapies.

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