Human leukocyte antigen (HLA) can encode the human major histocompatibility complex (MHC)
proteins and play a key role in adaptive and innate immunity. Emerging clinical evidences suggest that the presentation of
tumor neoantigens and neoantigen-specific T cell response associated with
MHC class I molecules are of key importance to activate the adaptive immune
systemin cancer immunotherapy. Therefore, accurate HLA typing is very essential for the clinical application of
immunotherapy. In this study, we conducted performance evaluations of 4 widely used HLA typing tools (OptiType, Phlat, Polysolver and seq2hla) for predicting HLA class Ia genes from WES and
RNA-seq data of 28
cancer patients. HLA genotyping data using PCR-SBT method was firstly obtained as the golden standard and was subsequently compared with HLA typing data by using NGS techniques. For both WES data and
RNA-seq data, OptiType showed the highest accuracy for HLA-Ia typing than the other 3 programs at 2-digit and 4-digit resolution. Additionally, HLA typing accuracy from WES data was higher than from
RNA-seq data (99.11% for WES data versus 96.42% for
RNA-seq data). The accuracy of HLA-Ia typing by OptiType can reach 100% with the average depth of HLA gene regions >20x. Besides, the accuracy of 2-digit and 4-digit HLA-Ia typing based on control samples was higher than
tumor tissues. In conclusion, OptiType by using WES data from control samples with the high average depth (>20x) of HLA gene regions can present a probably superior performance for HLA-Ia typing, enabling its application in
cancer immunotherapy.