Neoepitopes prediction strategies: an integration of cancer genomics and immunoinformatics approaches

Abstract

A major near-term medical impact of the genomic technology revolution will be the elucidation of mechanisms of cancer pathogenesis, leading to improvements in the diagnosis of cancer and the selection of cancer treatment. Next-generation sequencing technologies have accelerated the characterization of a tumor, leading to the comprehensive discovery of all the major alterations in a given cancer genome, followed by the translation of this information using computational and immunoinformatics approaches to cancer diagnostics and therapeutic efforts. In the current article, we review various components of cancer immunoinformatics applied to a series of fields of cancer research, including computational tools for cancer mutation detection, cancer mutation and immunological databases, and computational vaccinology.

Designing neoantigen cancer vaccines, trials, and outcomes

“…These criteria include proper selection of target somatic mutations, the exclusivity of the peptide production in the cancer cells, abundant expression, processing by antigen presentation pathway, binding of the peptide fragment to host specific HLA proteins, and mutated allele frequency. All of these criteria are difficult to satisfy and a compromised or prioritized choice is made using immunoinformatics approaches ( 20 ). Researchers have developed multiple pipelines for the selection of neopeptides, such as pVACtools ( 21 ), Vaxrank ( 22 ), MuPeXI ( 23 ), TSNAD ( 24 ), and pTuneos ( 25 ).…”