Abstract
BackgroundHigh-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 MethodsWe 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.ResultsRegardless 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%.ConclusionsHLA 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.
Highlights
The major histocompatibility complex (MHC) is located on chromosome 6p21.3 in humans, occupying a continuous 3.6 Mb segment of the human genome [1]
We developed a new algorithm with higher accuracy by combining existing tools, suggesting guidelines to select the most likely human leukocyte antigen (HLA) genotype
In many cases of 1,005 samples, HLA genotypes obtained from 1000 Genomes using polymerase chain reaction (PCR)-SBT were multiple types or were not available
Summary
The major histocompatibility complex (MHC) is located on chromosome 6p21.3 in humans, occupying a continuous 3.6 Mb segment of the human genome [1]. The MHC has three distinct loci: classes I, II, and III. Class I and II loci belong to the subgroup associated with HLA genes. HLA genes encode cellsurface antigen-presenting proteins, which play a central role in discriminating self and non-self. Class I (HLA-A, HLA-B, and HLA-C) and II genes (HLA-DP, HLA-DQ, and HLA-DR) are responsible for presenting processed antigens to cytotoxic T cells and helper T cells, respectively. An individual has a distinct HLA allele combination called an HLA haplotype (an entire set of HLA-A, -B, -C, -DP, -DQ, and -DR). As of January 2021, over 29,000 HLA allele variants have been reported according to the IPD-IMGT (ImMunoGeneTics)/ HLA reference database (release 3.43) [2]. High-precision human leukocyte antigen (HLA) genotyping is crucial for anti-cancer immunotherapy, but existing tools predicting HLA genotypes using nextgeneration sequencing (NGS) data are insufficiently accurate
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