Shaojun Tang, Suthee Rapisuwon, A. Wellstein, Subha Madhavan
{"title":"Tumor Neoantigens Derived from RNA Sequencing Analysis","authors":"Shaojun Tang, Suthee Rapisuwon, A. Wellstein, Subha Madhavan","doi":"10.1145/3107411.3108210","DOIUrl":null,"url":null,"abstract":"Successful treatment of cancers with Immune Checkpoint Inhibitors (ICIs) has been associated with the mutational load of tumors. The biological rationale for this association between mutational load and ICI response is that neoantigens are generated by mutations in protein coding sequences that provide a steady flow of neoantigens to prime the immune system for the production of antigen-specific tumor-infiltrating lymphocytes (TILs). It is thought that mutant protein fragments will lead to altered MHC/peptide recognition and immune cell activation; ICI treatment enhances TIL functionality. Neoantigens are also relevant for an alternative, cell-based immunotherapeutic approach, i.e. Adoptive Cell Transfer (ACT). This concept of neoantigens derived from DNA mutations has led to an intense line of investigation to uncover relevant neoantigens. However, there has been mixed success with the current neoantigen discovery approach based on DNA mutation analysis of tumor samples by exome sequencing of genomic DNA. The current concept of neoantigens derived from mutant DNA ignores an alternative mechanism that can also generate neoantigens in cancers: Posttranscriptional editing of primary RNA. Here we propose to use full-length Single Molecule Real Time (SMRT) RNAseq to uncover pathologically edited mRNAs in cancers and complement the discovery of pathologic mRNA. We will discuss the respective algorithms and propose the combination with identification of candidate neoantigen peptides by mass spectrometry.","PeriodicalId":246388,"journal":{"name":"Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics","volume":"119 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3107411.3108210","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Successful treatment of cancers with Immune Checkpoint Inhibitors (ICIs) has been associated with the mutational load of tumors. The biological rationale for this association between mutational load and ICI response is that neoantigens are generated by mutations in protein coding sequences that provide a steady flow of neoantigens to prime the immune system for the production of antigen-specific tumor-infiltrating lymphocytes (TILs). It is thought that mutant protein fragments will lead to altered MHC/peptide recognition and immune cell activation; ICI treatment enhances TIL functionality. Neoantigens are also relevant for an alternative, cell-based immunotherapeutic approach, i.e. Adoptive Cell Transfer (ACT). This concept of neoantigens derived from DNA mutations has led to an intense line of investigation to uncover relevant neoantigens. However, there has been mixed success with the current neoantigen discovery approach based on DNA mutation analysis of tumor samples by exome sequencing of genomic DNA. The current concept of neoantigens derived from mutant DNA ignores an alternative mechanism that can also generate neoantigens in cancers: Posttranscriptional editing of primary RNA. Here we propose to use full-length Single Molecule Real Time (SMRT) RNAseq to uncover pathologically edited mRNAs in cancers and complement the discovery of pathologic mRNA. We will discuss the respective algorithms and propose the combination with identification of candidate neoantigen peptides by mass spectrometry.