PMID- 36603583
OWN - NLM
STAT- MEDLINE
DCOM- 20230123
LR  - 20230205
IS  - 2405-4720 (Electronic)
IS  - 2405-4712 (Print)
IS  - 2405-4712 (Linking)
VI  - 14
IP  - 1
DP  - 2023 Jan 18
TI  - Improved predictions of antigen presentation and TCR recognition with 
      MixMHCpred2.2 and PRIME2.0 reveal potent SARS-CoV-2 CD8(+) T-cell epitopes.
PG  - 72-83.e5
LID - S2405-4712(22)00470-7 [pii]
LID - 10.1016/j.cels.2022.12.002 [doi]
AB  - The recognition of pathogen or cancer-specific epitopes by CD8(+) T cells is 
      crucial for the clearance of infections and the response to cancer immunotherapy. 
      This process requires epitopes to be presented on class I human leukocyte antigen 
      (HLA-I) molecules and recognized by the T-cell receptor (TCR). Machine learning 
      models capturing these two aspects of immune recognition are key to improve 
      epitope predictions. Here, we assembled a high-quality dataset of naturally 
      presented HLA-I ligands and experimentally verified neo-epitopes. We then 
      integrated these data in a refined computational framework to predict antigen 
      presentation (MixMHCpred2.2) and TCR recognition (PRIME2.0). The depth of our 
      training data and the algorithmic developments resulted in improved predictions 
      of HLA-I ligands and neo-epitopes. Prospectively applying our tools to SARS-CoV-2 
      proteins revealed several epitopes. TCR sequencing identified a monoclonal 
      response in effector/memory CD8(+) T cells against one of these epitopes and 
      cross-reactivity with the homologous peptides from other coronaviruses.
CI  - Copyright (c) 2022 Elsevier Inc. All rights reserved.
FAU - Gfeller, David
AU  - Gfeller D
AD  - Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University 
      of Lausanne, Lausanne, Switzerland; Agora Cancer Research Centre, 1011 Lausanne, 
      Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland; 
      Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland. Electronic address: 
      david.gfeller@unil.ch.
FAU - Schmidt, Julien
AU  - Schmidt J
AD  - Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University 
      Hospital of Lausanne, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), 
      Lausanne, Switzerland.
FAU - Croce, Giancarlo
AU  - Croce G
AD  - Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University 
      of Lausanne, Lausanne, Switzerland; Agora Cancer Research Centre, 1011 Lausanne, 
      Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland; 
      Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland.
FAU - Guillaume, Philippe
AU  - Guillaume P
AD  - Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University 
      Hospital of Lausanne, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), 
      Lausanne, Switzerland.
FAU - Bobisse, Sara
AU  - Bobisse S
AD  - Agora Cancer Research Centre, 1011 Lausanne, Switzerland; Department of Oncology, 
      Ludwig Institute for Cancer Research Lausanne, University Hospital of Lausanne, 
      Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland.
FAU - Genolet, Raphael
AU  - Genolet R
AD  - Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University 
      Hospital of Lausanne, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), 
      Lausanne, Switzerland.
FAU - Queiroz, Lise
AU  - Queiroz L
AD  - Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University 
      Hospital of Lausanne, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), 
      Lausanne, Switzerland.
FAU - Cesbron, Julien
AU  - Cesbron J
AD  - Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University 
      Hospital of Lausanne, Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), 
      Lausanne, Switzerland.
FAU - Racle, Julien
AU  - Racle J
AD  - Department of Oncology, Ludwig Institute for Cancer Research Lausanne, University 
      of Lausanne, Lausanne, Switzerland; Agora Cancer Research Centre, 1011 Lausanne, 
      Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland; 
      Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland.
FAU - Harari, Alexandre
AU  - Harari A
AD  - Agora Cancer Research Centre, 1011 Lausanne, Switzerland; Department of Oncology, 
      Ludwig Institute for Cancer Research Lausanne, University Hospital of Lausanne, 
      Lausanne, Switzerland; Swiss Cancer Center Leman (SCCL), Lausanne, Switzerland.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20230104
PL  - United States
TA  - Cell Syst
JT  - Cell systems
JID - 101656080
RN  - 0 (Epitopes, T-Lymphocyte)
RN  - 0 (Ligands)
RN  - 0 (Receptors, Antigen, T-Cell)
RN  - 0 (HLA Antigens)
SB  - IM
MH  - Humans
MH  - *CD8-Positive T-Lymphocytes
MH  - Epitopes, T-Lymphocyte
MH  - Antigen Presentation
MH  - SARS-CoV-2
MH  - Ligands
MH  - *COVID-19
MH  - Receptors, Antigen, T-Cell
MH  - HLA Antigens
PMC - PMC9811684
OTO - NOTNLM
OT  - CD8(+) T cell epitopes
OT  - HLA-I peptidomics
OT  - antigen presentation
OT  - computational biology
OT  - epitope predictions
OT  - immunology
OT  - machine learning
COIS- Declaration of interests The authors declare no competing interests.
EDAT- 2023/01/06 06:00
MHDA- 2023/01/24 06:00
PMCR- 2023/01/04
CRDT- 2023/01/05 18:41
PHST- 2022/06/23 00:00 [received]
PHST- 2022/10/12 00:00 [revised]
PHST- 2022/12/08 00:00 [accepted]
PHST- 2023/01/06 06:00 [pubmed]
PHST- 2023/01/24 06:00 [medline]
PHST- 2023/01/05 18:41 [entrez]
PHST- 2023/01/04 00:00 [pmc-release]
AID - S2405-4712(22)00470-7 [pii]
AID - 10.1016/j.cels.2022.12.002 [doi]
PST - ppublish
SO  - Cell Syst. 2023 Jan 18;14(1):72-83.e5. doi: 10.1016/j.cels.2022.12.002. Epub 2023 
      Jan 4.