PMID- 33338400
OWN - NLM
STAT- MEDLINE
DCOM- 20210225
LR  - 20210304
IS  - 2405-4720 (Electronic)
IS  - 2405-4712 (Print)
IS  - 2405-4712 (Linking)
VI  - 12
IP  - 2
DP  - 2021 Feb 17
TI  - RBM-MHC: A Semi-Supervised Machine-Learning Method for Sample-Specific Prediction 
      of Antigen Presentation by HLA-I Alleles.
PG  - 195-202.e9
LID - S2405-4712(20)30456-7 [pii]
LID - 10.1016/j.cels.2020.11.005 [doi]
AB  - The recent increase of immunopeptidomics data, obtained by mass spectrometry or 
      binding assays, opens up possibilities for investigating endogenous antigen 
      presentation by the highly polymorphic human leukocyte antigen class I (HLA-I) 
      protein. State-of-the-art methods predict with high accuracy presentation by HLA 
      alleles that are well represented in databases at the time of release but have a 
      poorer performance for rarer and less characterized alleles. Here, we introduce a 
      method based on Restricted Boltzmann Machines (RBMs) for prediction of antigens 
      presented on the Major Histocompatibility Complex (MHC) encoded by HLA 
      genes-RBM-MHC. RBM-MHC can be trained on custom and newly available samples with 
      no or a small amount of HLA annotations. RBM-MHC ensures improved predictions for 
      rare alleles and matches state-of-the-art performance for well-characterized 
      alleles while being less data demanding. RBM-MHC is shown to be a flexible and 
      easily interpretable method that can be used as a predictor of cancer neoantigens 
      and viral epitopes, as a tool for feature discovery, and to reconstruct peptide 
      motifs presented on specific HLA molecules.
CI  - Copyright (c) 2020 The Authors. Published by Elsevier Inc. All rights reserved.
FAU - Bravi, Barbara
AU  - Bravi B
AD  - Laboratoire de Physique de l'Ecole Normale Superieure, ENS, Universite PSL, CNRS, 
      Sorbonne Universite, Universite de Paris, F-75005 Paris, France. Electronic 
      address: bbravi.bb@gmail.com.
FAU - Tubiana, Jerome
AU  - Tubiana J
AD  - Blavatnik School of Computer Science, Tel Aviv University, 6139601 Tel Aviv, 
      Israel.
FAU - Cocco, Simona
AU  - Cocco S
AD  - Laboratoire de Physique de l'Ecole Normale Superieure, ENS, Universite PSL, CNRS, 
      Sorbonne Universite, Universite de Paris, F-75005 Paris, France. Electronic 
      address: simona.cocco@phys.ens.fr.
FAU - Monasson, Remi
AU  - Monasson R
AD  - Laboratoire de Physique de l'Ecole Normale Superieure, ENS, Universite PSL, CNRS, 
      Sorbonne Universite, Universite de Paris, F-75005 Paris, France. Electronic 
      address: remi.monasson@phys.ens.fr.
FAU - Mora, Thierry
AU  - Mora T
AD  - Laboratoire de Physique de l'Ecole Normale Superieure, ENS, Universite PSL, CNRS, 
      Sorbonne Universite, Universite de Paris, F-75005 Paris, France. Electronic 
      address: thierry.mora@phys.ens.fr.
FAU - Walczak, Aleksandra M
AU  - Walczak AM
AD  - Laboratoire de Physique de l'Ecole Normale Superieure, ENS, Universite PSL, CNRS, 
      Sorbonne Universite, Universite de Paris, F-75005 Paris, France. Electronic 
      address: aleksandra.walczak@phys.ens.fr.
LA  - eng
PT  - Journal Article
DEP - 20201217
PL  - United States
TA  - Cell Syst
JT  - Cell systems
JID - 101656080
RN  - 0 (Epitopes)
RN  - 0 (HLA Antigens)
RN  - 0 (Histocompatibility Antigens Class I)
RN  - 0 (Peptides)
SB  - IM
MH  - Algorithms
MH  - Alleles
MH  - Antigen Presentation/genetics/*immunology
MH  - Computational Biology/*methods
MH  - Databases, Protein
MH  - Epitopes
MH  - HLA Antigens/genetics/immunology
MH  - Histocompatibility Antigens Class I/*genetics/*immunology
MH  - Humans
MH  - Machine Learning
MH  - Major Histocompatibility Complex/immunology
MH  - Mass Spectrometry/methods
MH  - Models, Theoretical
MH  - Peptides/chemistry
MH  - Protein Binding
PMC - PMC7895905
OTO - NOTNLM
OT  - HLA prediction
OT  - Restricted Boltzmann Machines
OT  - SARS-CoV-2 epitopes
OT  - antigen presentation
OT  - immunopeptidomics
OT  - machine learning
OT  - neoantigen discovery
COIS- Declaration of Interests The authors declare no competing interests.
EDAT- 2020/12/19 06:00
MHDA- 2021/02/26 06:00
PMCR- 2021/02/17
CRDT- 2020/12/18 20:08
PHST- 2020/05/19 00:00 [received]
PHST- 2020/09/18 00:00 [revised]
PHST- 2020/11/17 00:00 [accepted]
PHST- 2020/12/19 06:00 [pubmed]
PHST- 2021/02/26 06:00 [medline]
PHST- 2020/12/18 20:08 [entrez]
PHST- 2021/02/17 00:00 [pmc-release]
AID - S2405-4712(20)30456-7 [pii]
AID - 10.1016/j.cels.2020.11.005 [doi]
PST - ppublish
SO  - Cell Syst. 2021 Feb 17;12(2):195-202.e9. doi: 10.1016/j.cels.2020.11.005. Epub 
      2020 Dec 17.