Protective and Susceptibility Effects of Human Leukocyte Antigen on Melanoma Prevalence and their Implications for Predicting Checkpoint Blockade Immunotherapy Outcomes
{"title":"Protective and Susceptibility Effects of Human Leukocyte Antigen on Melanoma Prevalence and their Implications for Predicting Checkpoint Blockade Immunotherapy Outcomes","authors":"Lisa M. James, A. Georgopoulos","doi":"10.29245/2578-3009/2022/2.1238","DOIUrl":null,"url":null,"abstract":"The association of Human Leukocyte Antigen (HLA) with melanoma has been well documented. Similarly, the outcome of checkpoint blockade immunotherapy (CBI) in melanoma depends, to some extent, on the HLA genotype of the patient. Although specific favorable (or unfavorable) HLA alleles for CBI outcome for melanoma have been identified, there is currently no reliable way to predict a positive, neutral or negative melanoma CBI outcome for other alleles. Here we used an immunogenetic epidemiological approach to identify HLA alleles whose frequency is negatively (or positively) associated with melanoma prevalence (protective or susceptibility alleles, respectively). The findings demonstrated that, indeed, HLA alleles that are negatively associated with melanoma prevalence in the population have been associated with good CBI outcome at the individual level and, conversely, HLA alleles that are positively associated with melanoma prevalence have been associated with poor CBI outcome in individuals. Given this good prediction of CBI cancer immunotherapy by specific immunogenetically discovered HLA alleles, we used this epidemiologic immunogenetic approach to identify more HLA Class I and II alleles protective (or susceptibility) for melanoma which would thus be good predictors of CBI outcomes in those cancers. This is a new approach to successfully (a) identify HLA protective or susceptibility alleles for melanoma, and (b) use that information in anticipating outcomes in CBI cancer immunotherapy.","PeriodicalId":73785,"journal":{"name":"Journal of immunological sciences","volume":"29 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of immunological sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29245/2578-3009/2022/2.1238","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The association of Human Leukocyte Antigen (HLA) with melanoma has been well documented. Similarly, the outcome of checkpoint blockade immunotherapy (CBI) in melanoma depends, to some extent, on the HLA genotype of the patient. Although specific favorable (or unfavorable) HLA alleles for CBI outcome for melanoma have been identified, there is currently no reliable way to predict a positive, neutral or negative melanoma CBI outcome for other alleles. Here we used an immunogenetic epidemiological approach to identify HLA alleles whose frequency is negatively (or positively) associated with melanoma prevalence (protective or susceptibility alleles, respectively). The findings demonstrated that, indeed, HLA alleles that are negatively associated with melanoma prevalence in the population have been associated with good CBI outcome at the individual level and, conversely, HLA alleles that are positively associated with melanoma prevalence have been associated with poor CBI outcome in individuals. Given this good prediction of CBI cancer immunotherapy by specific immunogenetically discovered HLA alleles, we used this epidemiologic immunogenetic approach to identify more HLA Class I and II alleles protective (or susceptibility) for melanoma which would thus be good predictors of CBI outcomes in those cancers. This is a new approach to successfully (a) identify HLA protective or susceptibility alleles for melanoma, and (b) use that information in anticipating outcomes in CBI cancer immunotherapy.