Improvement in neoantigen prediction via integration of RNA sequencing data for variant calling

Abstract

IntroductionNeoantigen-based immunotherapy has emerged as a promising strategy for improving the life expectancy of cancer patients. This therapeutic approach heavily relies on accurate identification of cancer mutations using DNA sequencing (DNAseq) data. However, current workflows tend to provide a large number of neoantigen candidates, of which only a limited number elicit efficient and immunogenic T-cell responses suitable for downstream clinical evaluation. To overcome this limitation and increase the number of high-quality immunogenic neoantigens, we propose integrating RNA sequencing (RNAseq) data into the mutation identification step in the neoantigen prediction workflow.MethodsIn this study, we characterize the mutation profiles identified from DNAseq and/or RNAseq data in tumor tissues of 25 patients with colorectal cancer (CRC). Immunogenicity was then validated by ELISpot assay using long synthesis peptides (sLP).ResultsWe detected only 22.4% of variants shared between the two methods. In contrast, RNAseq-derived variants displayed unique features of affinity and immunogenicity. We further established that neoantigen candidates identified by RNAseq data significantly increased the number of highly immunogenic neoantigens (confirmed by ELISpot) that would otherwise be overlooked if relying solely on DNAseq data.DiscussionThis integrative approach holds great potential for improving the selection of neoantigens for personalized cancer immunotherapy, ultimately leading to enhanced treatment outcomes and improved survival rates for cancer patients.

Targeting Neoantigens in Pancreatic Ductal Adenocarcinoma

“…This process is much faster than sequencing and provides information on what genes are present in the individual. Mapping the tumor-specific genetic abnormalities of the tumor and normal DNA while comparing them helps in identifying the neoantigens [ 85 , 86 , 87 ]. In the context of identifying neoantigens in PDAC, variants detected in tumor microarrays undergo analysis using epitope prediction algorithms.…”

“…Neoantigen-based therapies have shown promising results in the initial trials; however, studies in PDAC are limited and more research on developing personalized neoantigens must be completed before combination therapies can be considered in PDAC. Identification of accurate mutations and high-quality immunogenic neoantigens by integrating DNA sequencing data with RNA sequencing data may be advantageous in improving the therapy and clinical outcomes [ 87 ].…”

Targeting Neoantigens in Cancer: Possibilities and Opportunities in Breast Cancer

“…However, a combination of tumor RNA-seq data and normal WES data detected neoantigen candidates that have higher expression and rich variant transcripts than WES data alone. Nguyen et al [ 83 ] have also explored using RNA-seq data from 25 colorectal patients to predict neoantigen candidates. In contrast to the Hashimoto et al study [ 82 ], utilizing RNA-seq data alone significantly increased the number of highly immunogenic validated neoantigens detected compared to utilizing DNA seq data [ 83 ].…”

“…Nguyen et al [ 83 ] have also explored using RNA-seq data from 25 colorectal patients to predict neoantigen candidates. In contrast to the Hashimoto et al study [ 82 ], utilizing RNA-seq data alone significantly increased the number of highly immunogenic validated neoantigens detected compared to utilizing DNA seq data [ 83 ].…”

A Worldwide Preventative Cancer Vaccine Is Achievable With New Discoveries And Comparative Oncology

“…Nonetheless, researchers have shown that a number of variants can be identified in cancer patients with predicted HLA-binding affinity [42]. Recently, RNA-Seq databases have been purposed as means of verifying DNA-seq results and indicating which DNA mutations are transcribed in a tumor [43,44]. While useful for neoantigen discovery based on DNA mutations, this approach does not search the RNA error derived neoantigen source.…”