Literature DB >> 33861991

A pan-cancer transcriptome analysis of exitron splicing identifies novel cancer driver genes and neoepitopes.

Ting-You Wang1, Qi Liu2, Yanan Ren1, Sk Kayum Alam1, Li Wang1, Zhu Zhu1, Luke H Hoeppner3, Scott M Dehm4, Qi Cao5, Rendong Yang6.   

Abstract

Exitron splicing (EIS) creates a cryptic intron (called an exitron) within a protein-coding exon to increase proteome diversity. EIS is poorly characterized, but emerging evidence suggests a role for EIS in cancer. Through a systematic investigation of EIS across 33 cancers from 9,599 tumor transcriptomes, we discovered that EIS affected 63% of human coding genes and that 95% of those events were tumor specific. Notably, we observed a mutually exclusive pattern between EIS and somatic mutations in their affected genes. Functionally, we discovered that EIS altered known and novel cancer driver genes for causing gain- or loss-of-function, which promotes tumor progression. Importantly, we identified EIS-derived neoepitopes that bind to major histocompatibility complex (MHC) class I or II. Analysis of clinical data from a clear cell renal cell carcinoma cohort revealed an association between EIS-derived neoantigen load and checkpoint inhibitor response. Our findings establish the importance of considering EIS alterations when nominating cancer driver events and neoantigens.
Copyright © 2021 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  GTEx; TCGA; cancer driver genes; checkpoint inhibition immunotherapy; exitron; immunopeptidome; neoantigens; non-canonical splicing; pan-cancer analysis; transcriptome alterations

Mesh:

Substances:

Year:  2021        PMID: 33861991      PMCID: PMC8141048          DOI: 10.1016/j.molcel.2021.03.028

Source DB:  PubMed          Journal:  Mol Cell        ISSN: 1097-2765            Impact factor:   17.970


  76 in total

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10.  pTuneos: prioritizing tumor neoantigens from next-generation sequencing data.

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Journal:  Genome Med       Date:  2019-10-30       Impact factor: 11.117

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Review 4.  ABA Mediates Plant Development and Abiotic Stress via Alternative Splicing.

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5.  Integrated protocol for exitron and exitron-derived neoantigen identification using human RNA-seq data with ScanExitron and ScanNeo.

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  7 in total

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