Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy
By D. Chowell, L. Morris, C. Grigg, J. Weber, Robert Samstein, V. Makarov, F. Kuo, S. Kendall, David Requena, N. Riaz and 10 more. 2017
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HLA genotype affects response Immunotherapy works by activating the patient's own immune system to fight cancer. For effective tumor killing, CD8+ T cells recognize tumor peptides presented by human leukocyte antigen class I (HLA-I) molecules. In humans, there are three major HLA-I genes (HLA-A, HLA-B, and HLA-C). Chowell et al. asked whether germline HLA-I genotype influences how T cells recognize tumor peptides and respond to checkpoint inhibitor immunotherapies (see the Perspective by Kvistborg and Yewdell). They examined more than 1500 patients and found that heterozygosity at HLA-I loci was associated with better survival than homozygosity for one or more HLA-I genes. Thus, specific HLA-I mutations could have implications for immune recognition and for the design of epitopes for cancer vaccines and immunotherapies. Science, this issue p. 582; see also p. 516 Human leukocyte antigen superfamilies predict immunotherapy response. CD8+ T cell–dependent killing of cancer cells requires efficient presentation of tumor antigens by human leukocyte antigen class I (HLA-I) molecules. However, the extent to which patient-specific HLA-I genotype influences response to anti–programmed cell death protein 1 or anti–cytotoxic T lymphocyte–associated protein 4 is currently unknown. We determined the HLA-I genotype of 1535 advanced cancer patients treated with immune checkpoint blockade (ICB). Maximal heterozygosity at HLA-I loci (“A,” “B,” and “C”) improved overall survival after ICB compared with patients who were homozygous for at least one HLA locus. In two independent melanoma cohorts, patients with the HLA-B44 supertype had extended survival, whereas the HLA-B62 supertype (including HLA-B*15:01) or somatic loss of heterozygosity at HLA-I was associated with poor outcome. Molecular dynamics simulations of HLA-B*15:01 revealed different elements that may impair CD8+ T cell recognition of neoantigens. Our results have important implications for predicting response to ICB and for the design of neoantigen-based therapeutic vaccines.
Subfields: Immunology, Molecular Biology, Oncology
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Citations in the corpus
- Simulation-assisted machine learning (2018, neutral): “, 2018), human leukocyte antigen type (Chowell et al., 2018), tumor epigenetic DNA modifications, microbiome, and comorbidity set.”
- Development of tumor mutation burden as an immunotherapy biomarker: utility for the oncology clinic (2018, background): “Moreover, the impact of how HLA genotype and other germline variations influences the effect of TMB and response to ICB needs to be explored further [106].”