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Cancer Neoantigens: Challenges and Future Directions for Prediction, Prioritization, and Validation
Prioritization of immunogenic neoantigens is key to enhancing cancer immunotherapy through the development of personalized vaccines, adoptive T cell therapy, and the prediction of response to immune checkpoint inhibition. Neoantigens are tumor-specific proteins that allow the immune system to recogn...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8929516/ https://www.ncbi.nlm.nih.gov/pubmed/35311072 http://dx.doi.org/10.3389/fonc.2022.836821 |
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author | Borden, Elizabeth S. Buetow, Kenneth H. Wilson, Melissa A. Hastings, Karen Taraszka |
author_facet | Borden, Elizabeth S. Buetow, Kenneth H. Wilson, Melissa A. Hastings, Karen Taraszka |
author_sort | Borden, Elizabeth S. |
collection | PubMed |
description | Prioritization of immunogenic neoantigens is key to enhancing cancer immunotherapy through the development of personalized vaccines, adoptive T cell therapy, and the prediction of response to immune checkpoint inhibition. Neoantigens are tumor-specific proteins that allow the immune system to recognize and destroy a tumor. Cancer immunotherapies, such as personalized cancer vaccines, adoptive T cell therapy, and immune checkpoint inhibition, rely on an understanding of the patient-specific neoantigen profile in order to guide personalized therapeutic strategies. Genomic approaches to predicting and prioritizing immunogenic neoantigens are rapidly expanding, raising new opportunities to advance these tools and enhance their clinical relevance. Predicting neoantigens requires acquisition of high-quality samples and sequencing data, followed by variant calling and variant annotation. Subsequently, prioritizing which of these neoantigens may elicit a tumor-specific immune response requires application and integration of tools to predict the expression, processing, binding, and recognition potentials of the neoantigen. Finally, improvement of the computational tools is held in constant tension with the availability of datasets with validated immunogenic neoantigens. The goal of this review article is to summarize the current knowledge and limitations in neoantigen prediction, prioritization, and validation and propose future directions that will improve personalized cancer treatment. |
format | Online Article Text |
id | pubmed-8929516 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89295162022-03-18 Cancer Neoantigens: Challenges and Future Directions for Prediction, Prioritization, and Validation Borden, Elizabeth S. Buetow, Kenneth H. Wilson, Melissa A. Hastings, Karen Taraszka Front Oncol Oncology Prioritization of immunogenic neoantigens is key to enhancing cancer immunotherapy through the development of personalized vaccines, adoptive T cell therapy, and the prediction of response to immune checkpoint inhibition. Neoantigens are tumor-specific proteins that allow the immune system to recognize and destroy a tumor. Cancer immunotherapies, such as personalized cancer vaccines, adoptive T cell therapy, and immune checkpoint inhibition, rely on an understanding of the patient-specific neoantigen profile in order to guide personalized therapeutic strategies. Genomic approaches to predicting and prioritizing immunogenic neoantigens are rapidly expanding, raising new opportunities to advance these tools and enhance their clinical relevance. Predicting neoantigens requires acquisition of high-quality samples and sequencing data, followed by variant calling and variant annotation. Subsequently, prioritizing which of these neoantigens may elicit a tumor-specific immune response requires application and integration of tools to predict the expression, processing, binding, and recognition potentials of the neoantigen. Finally, improvement of the computational tools is held in constant tension with the availability of datasets with validated immunogenic neoantigens. The goal of this review article is to summarize the current knowledge and limitations in neoantigen prediction, prioritization, and validation and propose future directions that will improve personalized cancer treatment. Frontiers Media S.A. 2022-03-03 /pmc/articles/PMC8929516/ /pubmed/35311072 http://dx.doi.org/10.3389/fonc.2022.836821 Text en Copyright © 2022 Borden, Buetow, Wilson and Hastings https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Borden, Elizabeth S. Buetow, Kenneth H. Wilson, Melissa A. Hastings, Karen Taraszka Cancer Neoantigens: Challenges and Future Directions for Prediction, Prioritization, and Validation |
title | Cancer Neoantigens: Challenges and Future Directions for Prediction, Prioritization, and Validation |
title_full | Cancer Neoantigens: Challenges and Future Directions for Prediction, Prioritization, and Validation |
title_fullStr | Cancer Neoantigens: Challenges and Future Directions for Prediction, Prioritization, and Validation |
title_full_unstemmed | Cancer Neoantigens: Challenges and Future Directions for Prediction, Prioritization, and Validation |
title_short | Cancer Neoantigens: Challenges and Future Directions for Prediction, Prioritization, and Validation |
title_sort | cancer neoantigens: challenges and future directions for prediction, prioritization, and validation |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8929516/ https://www.ncbi.nlm.nih.gov/pubmed/35311072 http://dx.doi.org/10.3389/fonc.2022.836821 |
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