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

Molecular Oncology, 2021 · DOI: 10.1002/1878-0261.12895 · Published: January 24, 2021

Simple Explanation

Human leukocyte antigen (HLA) genotyping is important in cancer immunotherapy because of its role in immune recognition. However, generating reliable HLA genotyping results using computational tools remains a challenge, and the impact of HLA alleles on survival in tumor immunotherapy is still debated. This study benchmarks HLA genotyping on TCGA and presents a model to clarify the survival impact of HLA alleles. The study found that HLA class I genotyping is generally more accurate than class II genotyping. Specifically, POLY-SOLVER, OptiType, and xHLA performed well at HLA class I calling. HLA-HD showed the highest accuracy in HLA class II allele calling. Combining the top-performing tools improved overall accuracy. HLA alleles also show different survival impacts across various cancers. A 'Gun-Bullet' model was proposed, suggesting cytolytic activity (CYT) as a mechanism to explain how HLA alleles affect survival in cancer. The model suggests that strong HLA alleles, combined with a high tumor mutation burden (TMB), can stimulate intense immune activity, leading to extended survival. Therefore, reliable HLA genotyping should integrate multiple tools and incorporate TMB to improve survival prediction.

Study Duration

Not specified

Participants

10,479 tumor-normal paired whole exome sequencing (WES) data from TCGA

Evidence Level

Not specified

Key Findings

1
POLY-SOLVER, OptiType, and xHLA show high accuracy in HLA class I genotyping, with accuracies of 0.954, 0.949, and 0.937, respectively.
2
HLA-HD achieves the highest accuracy of 0.904 in HLA class II allele calling.
3
The 'Gun-Bullet' model suggests that a strong HLA allele combined with high tumor mutation burden (TMB) stimulates intensive immune cytolytic activity (CYT), leading to extended survival.

Research Summary

This study benchmarks HLA genotyping on TCGA data using multiple tools to generate reliable HLA genotyping results. It finds that HLA class I genotyping is generally better than class II genotyping, with POLY-SOLVER, OptiType, and xHLA performing well for class I, and HLA-HD for class II. The study proposes a 'Gun-Bullet' model, suggesting that the combination of strong HLA alleles and high tumor mutation burden stimulates intensive immune cytolytic activity, leading to extended survival. This model provides a framework for understanding the complex interplay between HLA genotype, TMB, and immune response. The study concludes that reliable HLA genotyping should be performed using multiple tools and incorporating TMB, which improves survival prediction compared to HLA genotyping alone. These findings have implications for personalized immunotherapy strategies.

Practical Implications

Improved HLA Genotyping

Using an ensemble of HLA genotyping tools, particularly POLY-SOLVER, OptiType, xHLA, and HLA-HD, can provide more reliable and accurate HLA genotyping results.

Personalized Immunotherapy Strategies

Integrating HLA genotype and tumor mutation burden (TMB) information can help identify patients who are more likely to benefit from immunotherapy.

Understanding Immune Response

The 'Gun-Bullet' model provides a framework for understanding how HLA alleles and TMB interact to stimulate immune cytolytic activity (CYT) and influence survival in cancer patients.

Study Limitations

1
The benchmark dataset may not perfectly represent the ground truth.
2
The study is limited by the tools selected; other HLA genotyping tools may achieve higher accuracy.
3
More ICB-treated cohorts with both RNA-seq and WES data are needed to verify the 'Gun-Bullet' model.

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