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Cited by 28vaccines and immunoinformatics approachesCancer Immunotherapy and BiomarkersImmunotherapy and Immune Responses

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In Silico Pipeline to Identify Tumor-Specific Antigens for Cancer Immunotherapy Using Exome Sequencing Data

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Morazán-Fernández, Diego, Mora, Javier, Molina-Mora, Jose Arturo·2023·Phenomics
DOI 10.1007/s43657-022-00084-9PMC PMC10110822
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Abstract

Tumor-specific antigens or neoantigens are peptides that are expressed only in cancer cells and not in healthy cells. Some of these molecules can induce an immune response, and therefore, their use in immunotherapeutic strategies based on cancer vaccines has been extensively explored. Studies based on these approaches have been triggered by the current high-throughput DNA sequencing technologies. However, there is no universal nor straightforward bioinformatic protocol to discover neoantigens using DNA sequencing data. Thus, we propose a bioinformatic protocol to detect tumor-specific antigens associated with single nucleotide variants (SNVs) or "mutations" in tumoral tissues. For this purpose, we used publicly available data to build our model, including exome sequencing data from colorectal cancer and healthy cells obtained from a single case, as well as frequent human leukocyte antigen (HLA) class I alleles in a specific population. HLA data from Costa Rican Central Valley population was selected as an example. The strategy included three main steps: (1) pre-processing of sequencing data; (2) variant calling analysis to detect tumor-specific SNVs in comparison with healthy tissue; and (3) prediction and characterization of peptides (protein fragments, the tumor-specific antigens) derived from the variants, in the context of their affinity with frequent alleles of the selected population. In our model data, we found 28 non-silent SNVs, present in 17 genes in chromosome one. The protocol yielded 23 strong binders peptides derived from the SNVs for frequent HLA class I alleles for the Costa Rican population. Although the analyses were performed as an example to implement the pipeline, to our knowledge, this is the first study of an in silico cancer vaccine using DNA sequencing data in the context of the HLA alleles. It is concluded that the standardized protocol was not only able to identify neoantigens in a specific but also provides a complete pipeline for the eventual design of cancer vaccines using the best bioinformatic practices. Supplementary information The online version contains supplementary material available at 10.1007/s43657-022-00084-9.

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Metadata

Authors
Morazán-Fernández, D., Mora, J., & Molina-Mora, J. A.
Affiliations
  • Costa Rican Department of Social Security (CR)
  • Universidad de Costa Rica (CR)
Corresponding author
  • Morazán-Fernández, Diego
  • Mora, Javier
ORCID
Venue
Phenomics
Publisher
Springer Science and Business Media LLC
Published
2022-12-08
Volume
3
Issue
2
Pages
130-137
ISSN
  • 2730-583X (ISSN-L)
  • 2730-5848
DOI
10.1007/s43657-022-00084-9
PMC
PMC10110822
OpenAlex
W4311881633
Cited by
28
References
2
Citations by year
2026: 5 · 2025: 9 · 2024: 12 · 2023: 2
FWCI
1.88
Type
journal article
Language
en
Open access
Licence
Locations
  • Phenomics (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
Vicerrectoría de Investigación, Universidad de Costa Rica (C1163)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
  • Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
  • Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
Keywords
tumor-specific antigens, neoantigens, cancer immunotherapy, cancer vaccines, single nucleotide variants, HLA class I alleles, peptide binding prediction, exome sequencing, colorectal cancer, Costa Rican population

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