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Streamlined selection of cancer antigens for vaccine development through integrative multi-omics and high-content cell imaging

Identification of tumor antigens that induce cytotoxic T lymphocytes (CTLs) is crucial for cancer-vaccine development. Despite their predictive ability, current algorithmic approaches and human leukocyte antigen (HLA)-peptidomic analysis allow limited selectivity. Here, we optimized a method to rapi...

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Autores principales: Han, Ki-Cheol, Park, Daechan, Ju, Shinyeong, Lee, Young Eun, Heo, Sun-Hee, Kim, Young-Ae, Lee, Ji Eun, Lee, Yuna, Park, Kyong Hwa, Park, Se-Ho, Lee, Hee Jin, Lee, Cheolju, Jang, Mihue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125174/
https://www.ncbi.nlm.nih.gov/pubmed/32245999
http://dx.doi.org/10.1038/s41598-020-62244-z
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author Han, Ki-Cheol
Park, Daechan
Ju, Shinyeong
Lee, Young Eun
Heo, Sun-Hee
Kim, Young-Ae
Lee, Ji Eun
Lee, Yuna
Park, Kyong Hwa
Park, Se-Ho
Lee, Hee Jin
Lee, Cheolju
Jang, Mihue
author_facet Han, Ki-Cheol
Park, Daechan
Ju, Shinyeong
Lee, Young Eun
Heo, Sun-Hee
Kim, Young-Ae
Lee, Ji Eun
Lee, Yuna
Park, Kyong Hwa
Park, Se-Ho
Lee, Hee Jin
Lee, Cheolju
Jang, Mihue
author_sort Han, Ki-Cheol
collection PubMed
description Identification of tumor antigens that induce cytotoxic T lymphocytes (CTLs) is crucial for cancer-vaccine development. Despite their predictive ability, current algorithmic approaches and human leukocyte antigen (HLA)-peptidomic analysis allow limited selectivity. Here, we optimized a method to rapidly screen and identify highly immunogenic epitopes that trigger CTL responses. We used a combined application of this method involving immune-specific signature analysis and HLA-associated peptidomics using samples from six patients with triple-negative breast cancer (TNBC) in order to select immunogenic HLA epitopes for in vitro testing. Additionally, we applied high-throughput imaging at the single-cell level in order to confirm the immunoreactivity of the selected peptides. The results indicated that this method enabled identification of promising CTL peptides capable of inducing antitumor immunity. This platform combining high-resolution computational analysis, HLA-peptidomics, and high-throughput immunogenicity testing allowed rapid and robust identification of highly immunogenic epitopes and represents a powerful technique for cancer-vaccine development.
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spelling pubmed-71251742020-04-08 Streamlined selection of cancer antigens for vaccine development through integrative multi-omics and high-content cell imaging Han, Ki-Cheol Park, Daechan Ju, Shinyeong Lee, Young Eun Heo, Sun-Hee Kim, Young-Ae Lee, Ji Eun Lee, Yuna Park, Kyong Hwa Park, Se-Ho Lee, Hee Jin Lee, Cheolju Jang, Mihue Sci Rep Article Identification of tumor antigens that induce cytotoxic T lymphocytes (CTLs) is crucial for cancer-vaccine development. Despite their predictive ability, current algorithmic approaches and human leukocyte antigen (HLA)-peptidomic analysis allow limited selectivity. Here, we optimized a method to rapidly screen and identify highly immunogenic epitopes that trigger CTL responses. We used a combined application of this method involving immune-specific signature analysis and HLA-associated peptidomics using samples from six patients with triple-negative breast cancer (TNBC) in order to select immunogenic HLA epitopes for in vitro testing. Additionally, we applied high-throughput imaging at the single-cell level in order to confirm the immunoreactivity of the selected peptides. The results indicated that this method enabled identification of promising CTL peptides capable of inducing antitumor immunity. This platform combining high-resolution computational analysis, HLA-peptidomics, and high-throughput immunogenicity testing allowed rapid and robust identification of highly immunogenic epitopes and represents a powerful technique for cancer-vaccine development. Nature Publishing Group UK 2020-04-03 /pmc/articles/PMC7125174/ /pubmed/32245999 http://dx.doi.org/10.1038/s41598-020-62244-z Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Han, Ki-Cheol
Park, Daechan
Ju, Shinyeong
Lee, Young Eun
Heo, Sun-Hee
Kim, Young-Ae
Lee, Ji Eun
Lee, Yuna
Park, Kyong Hwa
Park, Se-Ho
Lee, Hee Jin
Lee, Cheolju
Jang, Mihue
Streamlined selection of cancer antigens for vaccine development through integrative multi-omics and high-content cell imaging
title Streamlined selection of cancer antigens for vaccine development through integrative multi-omics and high-content cell imaging
title_full Streamlined selection of cancer antigens for vaccine development through integrative multi-omics and high-content cell imaging
title_fullStr Streamlined selection of cancer antigens for vaccine development through integrative multi-omics and high-content cell imaging
title_full_unstemmed Streamlined selection of cancer antigens for vaccine development through integrative multi-omics and high-content cell imaging
title_short Streamlined selection of cancer antigens for vaccine development through integrative multi-omics and high-content cell imaging
title_sort streamlined selection of cancer antigens for vaccine development through integrative multi-omics and high-content cell imaging
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125174/
https://www.ncbi.nlm.nih.gov/pubmed/32245999
http://dx.doi.org/10.1038/s41598-020-62244-z
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