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A New Human Leukocyte Antigen Typing Algorithm Combined With Currently Available Genotyping Tools Based on Next-Generation Sequencing Data and Guidelines to Select the Most Likely Human Leukocyte Antigen Genotype

BACKGROUND: High-precision human leukocyte antigen (HLA) genotyping is crucial for anti-cancer immunotherapy, but existing tools predicting HLA genotypes using next-generation sequencing (NGS) data are insufficiently accurate. MATERIALS AND METHODS: We compared availability, accuracy, correction sco...

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Autores principales: Lee, Miseon, Seo, Jeong-Han, Song, Sungjae, Song, In Hye, Kim, Su Yeon, Kim, Young-Ae, Gong, Gyungyub, Kim, Jeong Eun, Lee, Hee Jin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8517438/
https://www.ncbi.nlm.nih.gov/pubmed/34659196
http://dx.doi.org/10.3389/fimmu.2021.688183
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author Lee, Miseon
Seo, Jeong-Han
Song, Sungjae
Song, In Hye
Kim, Su Yeon
Kim, Young-Ae
Gong, Gyungyub
Kim, Jeong Eun
Lee, Hee Jin
author_facet Lee, Miseon
Seo, Jeong-Han
Song, Sungjae
Song, In Hye
Kim, Su Yeon
Kim, Young-Ae
Gong, Gyungyub
Kim, Jeong Eun
Lee, Hee Jin
author_sort Lee, Miseon
collection PubMed
description BACKGROUND: High-precision human leukocyte antigen (HLA) genotyping is crucial for anti-cancer immunotherapy, but existing tools predicting HLA genotypes using next-generation sequencing (NGS) data are insufficiently accurate. MATERIALS AND METHODS: We compared availability, accuracy, correction score, and complementary ratio of eight HLA genotyping tools (OptiType, HLA-HD, PHLAT, seq2HLA, arcasHLA, HLAscan, HLA*LA, and Kourami) using 1,005 cases from the 1000 Genomes Project data. We created a new HLA-genotyping algorithm combining tools based on the precision and the accuracy of tools’ combinations. Then, we assessed the new algorithm’s performance in 39 in-house samples with normal whole-exome sequencing (WES) data and polymerase chain reaction–sequencing-based typing (PCR-SBT) results. RESULTS: Regardless of the type of tool, the calls presented by more than six tools concordantly showed high accuracy and precision. The accuracy of the group with at least six concordant calls was 100% (97/97) in HLA-A, 98.2% (112/114) in HLA-B, 97.3% (142/146) in HLA-C. The precision of the group with at least six concordant calls was over 98% in HLA-ABC. We additionally calculated the accuracy of the combination tools considering the complementary ratio of each tool and the accuracy of each tool, and the accuracy was over 98% in all groups with six or more concordant calls. We created a new algorithm that matches the above results. It was to select the HLA type if more than six out of eight tools presented a matched type. Otherwise, determine the HLA type experimentally through PCR-SBT. When we applied the new algorithm to 39 in-house cases, there were more than six matching calls in all HLA-A, B, and C, and the accuracy of these concordant calls was 100%. CONCLUSIONS: HLA genotyping accuracy using NGS data could be increased by combining the current HLA genotyping tools. This new algorithm could also be useful for preliminary screening to decide whether to perform an additional PCR-based experimental method instead of using tools with NGS data.
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spelling pubmed-85174382021-10-16 A New Human Leukocyte Antigen Typing Algorithm Combined With Currently Available Genotyping Tools Based on Next-Generation Sequencing Data and Guidelines to Select the Most Likely Human Leukocyte Antigen Genotype Lee, Miseon Seo, Jeong-Han Song, Sungjae Song, In Hye Kim, Su Yeon Kim, Young-Ae Gong, Gyungyub Kim, Jeong Eun Lee, Hee Jin Front Immunol Immunology BACKGROUND: High-precision human leukocyte antigen (HLA) genotyping is crucial for anti-cancer immunotherapy, but existing tools predicting HLA genotypes using next-generation sequencing (NGS) data are insufficiently accurate. MATERIALS AND METHODS: We compared availability, accuracy, correction score, and complementary ratio of eight HLA genotyping tools (OptiType, HLA-HD, PHLAT, seq2HLA, arcasHLA, HLAscan, HLA*LA, and Kourami) using 1,005 cases from the 1000 Genomes Project data. We created a new HLA-genotyping algorithm combining tools based on the precision and the accuracy of tools’ combinations. Then, we assessed the new algorithm’s performance in 39 in-house samples with normal whole-exome sequencing (WES) data and polymerase chain reaction–sequencing-based typing (PCR-SBT) results. RESULTS: Regardless of the type of tool, the calls presented by more than six tools concordantly showed high accuracy and precision. The accuracy of the group with at least six concordant calls was 100% (97/97) in HLA-A, 98.2% (112/114) in HLA-B, 97.3% (142/146) in HLA-C. The precision of the group with at least six concordant calls was over 98% in HLA-ABC. We additionally calculated the accuracy of the combination tools considering the complementary ratio of each tool and the accuracy of each tool, and the accuracy was over 98% in all groups with six or more concordant calls. We created a new algorithm that matches the above results. It was to select the HLA type if more than six out of eight tools presented a matched type. Otherwise, determine the HLA type experimentally through PCR-SBT. When we applied the new algorithm to 39 in-house cases, there were more than six matching calls in all HLA-A, B, and C, and the accuracy of these concordant calls was 100%. CONCLUSIONS: HLA genotyping accuracy using NGS data could be increased by combining the current HLA genotyping tools. This new algorithm could also be useful for preliminary screening to decide whether to perform an additional PCR-based experimental method instead of using tools with NGS data. Frontiers Media S.A. 2021-10-01 /pmc/articles/PMC8517438/ /pubmed/34659196 http://dx.doi.org/10.3389/fimmu.2021.688183 Text en Copyright © 2021 Lee, Seo, Song, Song, Kim, Kim, Gong, Kim and Lee 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 Immunology
Lee, Miseon
Seo, Jeong-Han
Song, Sungjae
Song, In Hye
Kim, Su Yeon
Kim, Young-Ae
Gong, Gyungyub
Kim, Jeong Eun
Lee, Hee Jin
A New Human Leukocyte Antigen Typing Algorithm Combined With Currently Available Genotyping Tools Based on Next-Generation Sequencing Data and Guidelines to Select the Most Likely Human Leukocyte Antigen Genotype
title A New Human Leukocyte Antigen Typing Algorithm Combined With Currently Available Genotyping Tools Based on Next-Generation Sequencing Data and Guidelines to Select the Most Likely Human Leukocyte Antigen Genotype
title_full A New Human Leukocyte Antigen Typing Algorithm Combined With Currently Available Genotyping Tools Based on Next-Generation Sequencing Data and Guidelines to Select the Most Likely Human Leukocyte Antigen Genotype
title_fullStr A New Human Leukocyte Antigen Typing Algorithm Combined With Currently Available Genotyping Tools Based on Next-Generation Sequencing Data and Guidelines to Select the Most Likely Human Leukocyte Antigen Genotype
title_full_unstemmed A New Human Leukocyte Antigen Typing Algorithm Combined With Currently Available Genotyping Tools Based on Next-Generation Sequencing Data and Guidelines to Select the Most Likely Human Leukocyte Antigen Genotype
title_short A New Human Leukocyte Antigen Typing Algorithm Combined With Currently Available Genotyping Tools Based on Next-Generation Sequencing Data and Guidelines to Select the Most Likely Human Leukocyte Antigen Genotype
title_sort new human leukocyte antigen typing algorithm combined with currently available genotyping tools based on next-generation sequencing data and guidelines to select the most likely human leukocyte antigen genotype
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8517438/
https://www.ncbi.nlm.nih.gov/pubmed/34659196
http://dx.doi.org/10.3389/fimmu.2021.688183
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