PMID- 34659196
OWN - NLM
STAT- MEDLINE
DCOM- 20211213
LR  - 20211214
IS  - 1664-3224 (Electronic)
IS  - 1664-3224 (Linking)
VI  - 12
DP  - 2021
TI  - A New Human Leukocyte Antigen Typing Algorithm Combined With Currently Available 
      Genotyping Tools Based on Next-Generation Sequencing Data and Guidelines to 
      Select the Most Likely Human Leukocyte Antigen Genotype.
PG  - 688183
LID - 10.3389/fimmu.2021.688183 [doi]
LID - 688183
AB  - BACKGROUND: High-precision human leukocyte antigen (HLA) genotyping is crucial 
      for anti-cancer immunotherapy, but existing tools predicting HLA genotypes using 
      next-generation sequencing (NGS) data are insufficiently accurate. MATERIALS AND 
      METHODS: We compared availability, accuracy, correction score, and complementary 
      ratio of eight HLA genotyping tools (OptiType, HLA-HD, PHLAT, seq2HLA, arcasHLA, 
      HLAscan, HLA*LA, and Kourami) using 1,005 cases from the 1000 Genomes Project 
      data. We created a new HLA-genotyping algorithm combining tools based on the 
      precision and the accuracy of tools' combinations. Then, we assessed the new 
      algorithm's performance in 39 in-house samples with normal whole-exome sequencing 
      (WES) data and polymerase chain reaction-sequencing-based typing (PCR-SBT) 
      results. RESULTS: Regardless of the type of tool, the calls presented by more 
      than six tools concordantly showed high accuracy and precision. The accuracy of 
      the group with at least six concordant calls was 100% (97/97) in HLA-A, 98.2% 
      (112/114) in HLA-B, 97.3% (142/146) in HLA-C. The precision of the group with at 
      least six concordant calls was over 98% in HLA-ABC. We additionally calculated 
      the accuracy of the combination tools considering the complementary ratio of each 
      tool and the accuracy of each tool, and the accuracy was over 98% in all groups 
      with six or more concordant calls. We created a new algorithm that matches the 
      above results. It was to select the HLA type if more than six out of eight tools 
      presented a matched type. Otherwise, determine the HLA type experimentally 
      through PCR-SBT. When we applied the new algorithm to 39 in-house cases, there 
      were more than six matching calls in all HLA-A, B, and C, and the accuracy of 
      these concordant calls was 100%. CONCLUSIONS: HLA genotyping accuracy using NGS 
      data could be increased by combining the current HLA genotyping tools. This new 
      algorithm could also be useful for preliminary screening to decide whether to 
      perform an additional PCR-based experimental method instead of using tools with 
      NGS data.
CI  - Copyright (c) 2021 Lee, Seo, Song, Song, Kim, Kim, Gong, Kim and Lee.
FAU - Lee, Miseon
AU  - Lee M
AD  - Department of Hospital Pathology, Seoul St. Mary's Hospital, College of Medicine, 
      The Catholic University of Korea, Seoul, South Korea.
FAU - Seo, Jeong-Han
AU  - Seo JH
AD  - Department of Biomedical Sciences, Asan Medical Institute of Convergence Science 
      and Technology, University of Ulsan College of Medicine, Asan Medical Center, 
      Seoul, South Korea.
AD  - NeogenTC Corp, Seoul, South Korea.
FAU - Song, Sungjae
AU  - Song S
AD  - NeogenTC Corp, Seoul, South Korea.
FAU - Song, In Hye
AU  - Song IH
AD  - Department of Hospital Pathology, Seoul St. Mary's Hospital, College of Medicine, 
      The Catholic University of Korea, Seoul, South Korea.
FAU - Kim, Su Yeon
AU  - Kim SY
AD  - University of Ulsan College of Medicine, Seoul, South Korea.
FAU - Kim, Young-Ae
AU  - Kim YA
AD  - NeogenTC Corp, Seoul, South Korea.
FAU - Gong, Gyungyub
AU  - Gong G
AD  - Department of Pathology, University of Ulsan College of Medicine, Asan Medical 
      Center, Seoul, South Korea.
FAU - Kim, Jeong Eun
AU  - Kim JE
AD  - Department of Oncology, University of Ulsan College of Medicine, Asan Medical 
      Center, Seoul, South Korea.
FAU - Lee, Hee Jin
AU  - Lee HJ
AD  - Department of Biomedical Sciences, Asan Medical Institute of Convergence Science 
      and Technology, University of Ulsan College of Medicine, Asan Medical Center, 
      Seoul, South Korea.
AD  - NeogenTC Corp, Seoul, South Korea.
AD  - Department of Pathology, University of Ulsan College of Medicine, Asan Medical 
      Center, Seoul, South Korea.
LA  - eng
PT  - Comparative Study
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20211001
PL  - Switzerland
TA  - Front Immunol
JT  - Frontiers in immunology
JID - 101560960
RN  - 0 (HLA Antigens)
SB  - IM
MH  - *Algorithms
MH  - Clinical Decision-Making
MH  - Databases, Genetic
MH  - Genotype
MH  - HLA Antigens/*genetics/immunology
MH  - *High-Throughput Nucleotide Sequencing
MH  - Histocompatibility/*genetics
MH  - *Histocompatibility Testing
MH  - Humans
MH  - Immunotherapy
MH  - Neoplasms/*genetics/immunology/therapy
MH  - Phenotype
MH  - Predictive Value of Tests
MH  - Reproducibility of Results
MH  - Software
PMC - PMC8517438
OTO - NOTNLM
OT  - HLA genotype
OT  - HLA typing algorithm
OT  - human leukocyte antigen (HLA)
OT  - immunotherapy
OT  - neoantigen
OT  - next-generation sequencing data (NGS)
COIS- Authors SS and Y-AK were employed by company NeogenTC Corp. The remaining 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- 2021/10/19 06:00
MHDA- 2021/12/15 06:00
PMCR- 2021/01/01
CRDT- 2021/10/18 08:55
PHST- 2021/03/30 00:00 [received]
PHST- 2021/09/15 00:00 [accepted]
PHST- 2021/10/18 08:55 [entrez]
PHST- 2021/10/19 06:00 [pubmed]
PHST- 2021/12/15 06:00 [medline]
PHST- 2021/01/01 00:00 [pmc-release]
AID - 10.3389/fimmu.2021.688183 [doi]
PST - epublish
SO  - Front Immunol. 2021 Oct 1;12:688183. doi: 10.3389/fimmu.2021.688183. eCollection 
      2021.