PMID- 34113354
OWN - NLM
STAT- MEDLINE
DCOM- 20211027
LR  - 20211027
IS  - 1664-3224 (Electronic)
IS  - 1664-3224 (Linking)
VI  - 12
DP  - 2021
TI  - Improvement of Neoantigen Identification Through Convolution Neural Network.
PG  - 682103
LID - 10.3389/fimmu.2021.682103 [doi]
LID - 682103
AB  - Accurate prediction of neoantigens and the subsequent elicited protective 
      anti-tumor response are particularly important for the development of cancer 
      vaccine and adoptive T-cell therapy. However, current algorithms for predicting 
      neoantigens are limited by in vitro binding affinity data and algorithmic 
      constraints, inevitably resulting in high false positives. In this study, we 
      proposed a deep convolutional neural network named APPM (antigen presentation 
      prediction model) to predict antigen presentation in the context of human 
      leukocyte antigen (HLA) class I alleles. APPM is trained on large mass 
      spectrometry (MS) HLA-peptides datasets and evaluated with an independent MS 
      benchmark. Results show that APPM outperforms the methods recommended by the 
      immune epitope database (IEDB) in terms of positive predictive value (PPV) (0.40 
      vs. 0.22), which will further increase after combining these two approaches (PPV 
      = 0.51). We further applied our model to the prediction of neoantigens from 
      consensus driver mutations and identified 16,000 putative neoantigens with 
      hallmarks of 'drivers'.
CI  - Copyright (c) 2021 Hao, Wei, Shu, Zhang, Xu and Zhao.
FAU - Hao, Qing
AU  - Hao Q
AD  - College of Pharmaceutical Sciences, Southwest Medical University, Luzhou, China.
FAU - Wei, Ping
AU  - Wei P
AD  - Sichuan Center for Translational Medicine of Traditional Chinese Medicine, State 
      Key Laboratory of Quality Evaluation of Traditional Chinese Medicine, Sichuan 
      Geoherbs System Engineering Technology Research Center of Chinese Medicine, 
      Sichuan Provincial Key Laboratory of Quality Evaluation of Traditional Chinese 
      Medicine and Innovative Chinese Medicine Research, Institute of Translational 
      Pharmacology of Sichuan Academy of Chinese Medicine Sciences, Chengdu, China.
FAU - Shu, Yang
AU  - Shu Y
AD  - Department of Laboratory Medicine, State Key Laboratory of Biotherapy, West China 
      Hospital, Sichuan University, Chengdu, China.
FAU - Zhang, Yi-Guan
AU  - Zhang YG
AD  - College of Pharmaceutical Sciences, Southwest Medical University, Luzhou, China.
AD  - Sichuan Center for Translational Medicine of Traditional Chinese Medicine, State 
      Key Laboratory of Quality Evaluation of Traditional Chinese Medicine, Sichuan 
      Geoherbs System Engineering Technology Research Center of Chinese Medicine, 
      Sichuan Provincial Key Laboratory of Quality Evaluation of Traditional Chinese 
      Medicine and Innovative Chinese Medicine Research, Institute of Translational 
      Pharmacology of Sichuan Academy of Chinese Medicine Sciences, Chengdu, China.
FAU - Xu, Heng
AU  - Xu H
AD  - Department of Laboratory Medicine, State Key Laboratory of Biotherapy, West China 
      Hospital, Sichuan University, Chengdu, China.
FAU - Zhao, Jun-Ning
AU  - Zhao JN
AD  - Sichuan Center for Translational Medicine of Traditional Chinese Medicine, State 
      Key Laboratory of Quality Evaluation of Traditional Chinese Medicine, Sichuan 
      Geoherbs System Engineering Technology Research Center of Chinese Medicine, 
      Sichuan Provincial Key Laboratory of Quality Evaluation of Traditional Chinese 
      Medicine and Innovative Chinese Medicine Research, Institute of Translational 
      Pharmacology of Sichuan Academy of Chinese Medicine Sciences, Chengdu, China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20210525
PL  - Switzerland
TA  - Front Immunol
JT  - Frontiers in immunology
JID - 101560960
RN  - 0 (Antigens, Neoplasm)
RN  - 0 (Biomarkers, Tumor)
RN  - 0 (Epitopes)
RN  - 0 (HLA Antigens)
SB  - IM
MH  - Algorithms
MH  - Alleles
MH  - Amino Acid Motifs
MH  - Amino Acid Sequence
MH  - Antigen Presentation
MH  - Antigens, Neoplasm/genetics/*immunology
MH  - Biomarkers, Tumor
MH  - Computational Biology/methods
MH  - Conserved Sequence
MH  - Epitope Mapping/*methods
MH  - Epitopes/genetics/*immunology
MH  - HLA Antigens/genetics/immunology
MH  - Humans
MH  - *Neural Networks, Computer
PMC - PMC8186784
OTO - NOTNLM
OT  - CNN
OT  - HLA
OT  - driver mutation
OT  - neoantigen
OT  - prediction
COIS- The authors declare that the research was conducted in the absence of any 
      commercial or financial relationships that could be construed as a potential 
      conflict of interest.
EDAT- 2021/06/12 06:00
MHDA- 2021/10/28 06:00
PMCR- 2021/01/01
CRDT- 2021/06/11 06:43
PHST- 2021/03/17 00:00 [received]
PHST- 2021/05/05 00:00 [accepted]
PHST- 2021/06/11 06:43 [entrez]
PHST- 2021/06/12 06:00 [pubmed]
PHST- 2021/10/28 06:00 [medline]
PHST- 2021/01/01 00:00 [pmc-release]
AID - 10.3389/fimmu.2021.682103 [doi]
PST - epublish
SO  - Front Immunol. 2021 May 25;12:682103. doi: 10.3389/fimmu.2021.682103. eCollection 
      2021.