POTN: A Human Leukocyte Antigen-A2 Immunogenic Peptides Screening Model and Its Applications in Tumor Antigens Prediction
Whole genome/exome sequencing data for tumors are now abundant, and many tumor antigens, especially mutant antigens (neoantigens), have been identified for cancer immunotherapy. However, only a small fraction of the peptides from these antigens induce cytotoxic T cell responses. Therefore, efficient...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-10-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fimmu.2020.02193/full |
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| author | Qingqing Meng Yahong Wu Xinghua Sui Jingjie Meng Tingting Wang Yan Lin Zhiwei Wang Xiuman Zhou Yuanming Qi Jiangfeng Du Yanfeng Gao Yanfeng Gao |
| author_facet | Qingqing Meng Yahong Wu Xinghua Sui Jingjie Meng Tingting Wang Yan Lin Zhiwei Wang Xiuman Zhou Yuanming Qi Jiangfeng Du Yanfeng Gao Yanfeng Gao |
| author_sort | Qingqing Meng |
| collection | DOAJ |
| description | Whole genome/exome sequencing data for tumors are now abundant, and many tumor antigens, especially mutant antigens (neoantigens), have been identified for cancer immunotherapy. However, only a small fraction of the peptides from these antigens induce cytotoxic T cell responses. Therefore, efficient methods to identify these antigenic peptides are crucial. The current models of major histocompatibility complex (MHC) binding and antigenic prediction are still inaccurate. In this study, 360 9-mer peptides with verified immunological activity were selected to construct a prediction of tumor neoantigen (POTN) model, an immunogenic prediction model specifically for the human leukocyte antigen-A2 allele. Based on the physicochemical properties of amino acids, such as the residue propensity, hydrophobicity, and organic solvent/water, we found that the predictive capability of POTN is superior to that of the prediction programs SYPEITHI, IEDB, and NetMHCpan 4.0. We used POTN to screen peptides for the cancer-testis antigen located on the X chromosome, and we identified several peptides that may trigger immunogenicity. We synthesized and measured the binding affinity and immunogenicity of these peptides and found that the accuracy of POTN is higher than that of NetMHCpan 4.0. Identifying the properties related to the T cell response or immunogenicity paves the way to understanding the MHC/peptide/T cell receptor complex. In conclusion, POTN is an efficient prediction model for screening high-affinity immunogenic peptides from tumor antigens, and thus provides useful information for developing cancer immunotherapy. |
| first_indexed | 2024-12-12T17:03:33Z |
| format | Article |
| id | doaj.art-1f00219c9f3f44c9a542d2a3b6eb2f53 |
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| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-12-12T17:03:33Z |
| publishDate | 2020-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Immunology |
| spelling | doaj.art-1f00219c9f3f44c9a542d2a3b6eb2f532022-12-22T00:18:04ZengFrontiers Media S.A.Frontiers in Immunology1664-32242020-10-011110.3389/fimmu.2020.02193542334POTN: A Human Leukocyte Antigen-A2 Immunogenic Peptides Screening Model and Its Applications in Tumor Antigens PredictionQingqing Meng0Yahong Wu1Xinghua Sui2Jingjie Meng3Tingting Wang4Yan Lin5Zhiwei Wang6Xiuman Zhou7Yuanming Qi8Jiangfeng Du9Yanfeng Gao10Yanfeng Gao11School of Life Sciences, Zhengzhou University, Zhengzhou, ChinaSchool of Life Sciences, Zhengzhou University, Zhengzhou, ChinaSchool of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Shenzhen, ChinaSchool of Life Sciences, Zhengzhou University, Zhengzhou, ChinaSchool of Life Sciences, Zhengzhou University, Zhengzhou, ChinaSchool of Life Sciences, Zhengzhou University, Zhengzhou, ChinaSchool of Life Sciences, Zhengzhou University, Zhengzhou, ChinaSchool of Life Sciences, Zhengzhou University, Zhengzhou, ChinaSchool of Life Sciences, Zhengzhou University, Zhengzhou, ChinaSchool of Life Sciences, Zhengzhou University, Zhengzhou, ChinaSchool of Life Sciences, Zhengzhou University, Zhengzhou, ChinaSchool of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Shenzhen, ChinaWhole genome/exome sequencing data for tumors are now abundant, and many tumor antigens, especially mutant antigens (neoantigens), have been identified for cancer immunotherapy. However, only a small fraction of the peptides from these antigens induce cytotoxic T cell responses. Therefore, efficient methods to identify these antigenic peptides are crucial. The current models of major histocompatibility complex (MHC) binding and antigenic prediction are still inaccurate. In this study, 360 9-mer peptides with verified immunological activity were selected to construct a prediction of tumor neoantigen (POTN) model, an immunogenic prediction model specifically for the human leukocyte antigen-A2 allele. Based on the physicochemical properties of amino acids, such as the residue propensity, hydrophobicity, and organic solvent/water, we found that the predictive capability of POTN is superior to that of the prediction programs SYPEITHI, IEDB, and NetMHCpan 4.0. We used POTN to screen peptides for the cancer-testis antigen located on the X chromosome, and we identified several peptides that may trigger immunogenicity. We synthesized and measured the binding affinity and immunogenicity of these peptides and found that the accuracy of POTN is higher than that of NetMHCpan 4.0. Identifying the properties related to the T cell response or immunogenicity paves the way to understanding the MHC/peptide/T cell receptor complex. In conclusion, POTN is an efficient prediction model for screening high-affinity immunogenic peptides from tumor antigens, and thus provides useful information for developing cancer immunotherapy.https://www.frontiersin.org/article/10.3389/fimmu.2020.02193/fullneoantigen predictionpeptidesimmunogenicityprediction modelcancer immunotherapy |
| spellingShingle | Qingqing Meng Yahong Wu Xinghua Sui Jingjie Meng Tingting Wang Yan Lin Zhiwei Wang Xiuman Zhou Yuanming Qi Jiangfeng Du Yanfeng Gao Yanfeng Gao POTN: A Human Leukocyte Antigen-A2 Immunogenic Peptides Screening Model and Its Applications in Tumor Antigens Prediction Frontiers in Immunology neoantigen prediction peptides immunogenicity prediction model cancer immunotherapy |
| title | POTN: A Human Leukocyte Antigen-A2 Immunogenic Peptides Screening Model and Its Applications in Tumor Antigens Prediction |
| title_full | POTN: A Human Leukocyte Antigen-A2 Immunogenic Peptides Screening Model and Its Applications in Tumor Antigens Prediction |
| title_fullStr | POTN: A Human Leukocyte Antigen-A2 Immunogenic Peptides Screening Model and Its Applications in Tumor Antigens Prediction |
| title_full_unstemmed | POTN: A Human Leukocyte Antigen-A2 Immunogenic Peptides Screening Model and Its Applications in Tumor Antigens Prediction |
| title_short | POTN: A Human Leukocyte Antigen-A2 Immunogenic Peptides Screening Model and Its Applications in Tumor Antigens Prediction |
| title_sort | potn a human leukocyte antigen a2 immunogenic peptides screening model and its applications in tumor antigens prediction |
| topic | neoantigen prediction peptides immunogenicity prediction model cancer immunotherapy |
| url | https://www.frontiersin.org/article/10.3389/fimmu.2020.02193/full |
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