Benchmarking HLA genotyping and clarifying HLA impact on survival in tumor immunotherapy

Abstract

Human Leucocyte Antigen (HLA) genotyping gains intensive attention due to its critical role in cancer immunotherapy. It is still a challenging issue to generate reliable HLA genotyping results through in silico tools. In addition, the survival impact of HLA alleles in tumor prognosis and immunotherapy remains controversial. In this study, the benchmarking of HLA genotyping on TCGA is performed and a "Gun-Bullet" model which helps to clarify the survival impact of HLA allele is presented. The performance of HLA class I genotyping is generally better than class II. POLYSOLVER, OptiType and xHLA perform generally better at HLA class I calling with an accuracy of 0.954, 0.949 and 0.937, respectively. HLA-HD obtained the highest accuracy of 0.904 on HLA class II alleles calling. Each HLA-genotyping tool displayed specific error patterns. The ensemble HLA calling from the top-3 tools is superior to any individual one. HLA alleles show distinct survival impact among cancers. Cytolytic activity (CYT) was proposed as the underlying mechanism to interpret the survival impact of HLA alleles in the "Gun-Bullet" model for fighting cancer. A strong HLA allele plus a high tumor mutation burden (TMB) could stimulate intensive immune CYT, leading to extended survival. We established an up-to-now most reliable TCGA HLA benchmark dataset, composing of concordance alleles generated from eight prevalently used HLA genotyping tools. Our findings indicate that reliable HLA genotyping should be performed based on concordance alleles integrating multiple tools and incorporating TMB background with HLA genotype, which helps to improve the survival prediction compared to HLA genotyping alone.

Human Leucocyte Antigens as Prognostic Markers in Head and Neck Squamous Cell Carcinoma

“…The observed association of the HLA composition with the outcomes of HNSCC patients (PFS and OS) is in line with previously conducted studies, also suggesting an influence of HLA allele traits on survival [ 12 , 17 , 21 , 22 ]. For example, Wichmann et al investigated a comparable HNSCC cohort (n = 90) and reported HLA-B*13, HLA-B*35, and HLA-B*51 as independent predictors of PFS in HNSCCs [ 12 , 22 ].…”

Benchmark of tools for in silico prediction of MHC class I and class II genotypes from NGS data

“…For MHC-II genotyping there is currently no consensus about the best method. Several benchmarks have been performed previously [14,[16][17][18][19][20][21][22][23], but these were either not applied to MHC class II or did not include some recently published tools.…”

The Immunogenetic Basis of Idiopathic Bone Marrow Failure Syndromes: A Paradox of Similarity and Self-Presentation

“…High resolution six-digit HLA typing was then inferred with HLA-HD v 1.3, 69,70 based on the nomenclature of the IPD-IMGT-HLA database v. 3.40. 71 This tool previously showed its ability to provide an highly accurate HLA inference (miscall rate <4%) in independent studies 72,73 and was crossvalidated in our cohort, for patients with available SSO-PCR HLA typing (Table S14).…”