Identification of cytotoxic T cells and their T cell receptor sequences targeting COVID-19 using MHC class I-binding peptides

Hikichi, Tetsuro; Sakamoto, Michiko; Harada, Makiko; Saito, Maki; Yamane, Yuka; Tokumura, Kimihisa; Nakamura, Yusuke

doi:10.1038/s10038-022-01013-4

Cited by 6 publications

(6 citation statements)

References 29 publications

(25 reference statements)

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“…The tested peptide was mixed with the tetramer and peptide exchange factor for 4.5 h at room temperature. The peptide exchange rate was quantitated by flow cytometry [ 21 , 22 ]. The reference positive peptide was provided by the QuickSwitch™ Quant HLA-A*02:01 Tetramer Kit-PE.…”

Section: Methodsmentioning

confidence: 99%

ImmuneMirror: A machine learning-based integrative pipeline and web server for neoantigen prediction

Chuwdhury,

Guo,

Chiang

et al. 2024

Briefings in Bioinformatics

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Neoantigens are derived from somatic mutations in the tumors but are absent in normal tissues. Emerging evidence suggests that neoantigens can stimulate tumor-specific T-cell-mediated antitumor immune responses, and therefore are potential immunotherapeutic targets. We developed ImmuneMirror as a stand-alone open-source pipeline and a web server incorporating a balanced random forest model for neoantigen prediction and prioritization. The prediction model was trained and tested using known immunogenic neopeptides collected from 19 published studies. The area under the curve of our trained model was 0.87 based on the testing data. We applied ImmuneMirror to the whole-exome sequencing and RNA sequencing data obtained from gastrointestinal tract cancers including 805 tumors from colorectal cancer (CRC), esophageal squamous cell carcinoma (ESCC) and hepatocellular carcinoma patients. We discovered a subgroup of microsatellite instability-high (MSI-H) CRC patients with a low neoantigen load but a high tumor mutation burden (> 10 mutations per Mbp). Although the efficacy of PD-1 blockade has been demonstrated in advanced MSI-H patients, almost half of such patients do not respond well. Our study identified a subset of MSI-H patients who may not benefit from this treatment with lower neoantigen load for major histocompatibility complex I (P < 0.0001) and II (P = 0.0008) molecules, respectively. Additionally, the neopeptide YMCNSSCMGV-TP53G245V, derived from a hotspot mutation restricted by HLA-A02, was identified as a potential actionable target in ESCC. This is so far the largest study to comprehensively evaluate neoantigen prediction models using experimentally validated neopeptides. Our results demonstrate the reliability and effectiveness of ImmuneMirror for neoantigen prediction.

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Section: Methodsmentioning

confidence: 99%

ImmuneMirror: A machine learning-based integrative pipeline and web server for neoantigen prediction

Chuwdhury,

Guo,

Chiang

et al. 2024

Briefings in Bioinformatics

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show abstract

“…The tested peptide was mixed with the tetramer and peptide exchange factor for 4.5 hours at room temperature. The peptide exchange rate was quantitated by flow cytometry (21,22). The reference positive peptide was provided by the QuickSwitch™ Quant HLA-A*02:01 Tetramer Kit-PE.…”

Section: Hla-a02:01 Peptide-binding Assaymentioning

confidence: 99%

ImmuneMirror: a Machine Learning-based Integrative Pipeline and Web Server for Neoantigen Prediction

Chuwdhury¹,

Guo²,

Cheung³

et al. 2023

Preprint

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Neoantigens are derived from tumors but are absent in normal tissues. Emerging evidence suggests that neoantigens can stimulate tumor-specific T-cell-mediated antitumor immune responses, and neoantigens are potential immunotherapy targets. We developed ImmuneMirror as a stand-alone open-source pipeline (https://github.com/weidai2/ImmuneMirror/) and a web server (http://immunemirror.hku.hk/App/) incorporating a balanced random forest model for neoantigen prediction and prioritization; the model was trained and tested using known immunogenic neopeptides collected from 19 published studies. The area under the curve (AUC) of our model was 0.87. We utilized ImmuneMirror in gastrointestinal tract cancers and discovered a subgroup of microsatellite instability-high (MSI-H) colorectal cancer (CRC) patients with a low neoantigen load but a high tumor mutation burden (TMB>10 mutations per Mbp). Although the efficacy of PD-1 blockade has been demonstrated in advanced MSI-H patients, almost half of such patients do not respond well. Our study may identify MSI-H patients who do not benefit from this treatment. Additionally, the neopeptide YMCNSSCMGV-TP53G245V, derived from a hotspot mutation restricted by HLA-A02, was identified as an actionable target in esophageal squamous cell carcinoma (ESCC). This is the largest study to comprehensively evaluate neoantigen prediction models using experimentally validated neopeptides. Our results demonstrate the reliability and effectiveness of ImmuneMirror for neoantigen prediction.

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“… Data obtained from: [ 4 , 5 , 7 – 10 , 12 , 13 , 16 , 18 , 22 , 24 , 28 , 30 , 33 ]. Abbreviation: ACE Angiotensin I-converting enzyme, FUT2 Fucosyltransferase 2, HLA Major histocompatibility complex, IFN Interferon, SNP Single nucleotide polymorphism, IFNAR2 Interferon-alpha, -beta, and -omega receptor 2, IL10RB Interleukin-10-receptor-beta, IRF7 IFN regulatory factor 7, OAS Oligoadenylate synthase, OR Odds ratio, r Correlation, TLR Toll-like receptor, TMPRSS2 Transmembrane serine protease 2 …”

Section: Introductionmentioning

confidence: 99%

“…Several SNPs and alleles of both human leukocyte antigen (HLA) class I and II (respectively located in 6p22.1 and 6p21.32) increase the risk of severe COVID-19, although it is still now not fully clear the mechanism induced severe COVID-19 HLA-mediated, growing evidence suggest that this can be induced by different SARS-CoV-2 antigen presentation HLA-mediated that correlate with abnormal immune cells response [ 12 , 22 – 24 ].…”

Section: Introductionmentioning

confidence: 99%

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Cellular and molecular features of COVID-19 associated ARDS: therapeutic relevance

et al. 2023

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The severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection can be asymptomatic or cause a disease (COVID-19) characterized by different levels of severity. The main cause of severe COVID-19 and death is represented by acute (or acute on chronic) respiratory failure and acute respiratory distress syndrome (ARDS), often requiring hospital admission and ventilator support.The molecular pathogenesis of COVID-19-related ARDS (by now termed c-ARDS) is still poorly understood. In this review we will discuss the genetic susceptibility to COVID-19, the pathogenesis and the local and systemic biomarkers correlated with c-ARDS and the therapeutic options that target the cell signalling pathways of c-ARDS.

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Identification of cytotoxic T cells and their T cell receptor sequences targeting COVID-19 using MHC class I-binding peptides

Cited by 6 publications

References 29 publications

ImmuneMirror: A machine learning-based integrative pipeline and web server for neoantigen prediction

ImmuneMirror: A machine learning-based integrative pipeline and web server for neoantigen prediction

ImmuneMirror: a Machine Learning-based Integrative Pipeline and Web Server for Neoantigen Prediction

Cellular and molecular features of COVID-19 associated ARDS: therapeutic relevance

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