免疫编辑
免疫系统
免疫疗法
生物
抗原
转录组
癌症
癌症免疫疗法
免疫原性
逃避(道德)
肿瘤微环境
人类白细胞抗原
免疫学
癌症研究
免疫监视
免疫检查点
抗体
CTL公司*
获得性免疫系统
作者
Xutong Gong,Rachel Karchin
标识
DOI:10.1101/2021.05.17.444511
摘要
Abstract Human Leukocyte Antigen (HLA) expression contributes to the activation of anti-tumor immunity through interactions with T cell receptors. However, pan-cancer HLA-mediated immunogenicity and immunoediting mechanisms has not been systematically studied. In a retrospective analysis of 33 tumor types from the Cancer Genome Atlas, we uncovered HLA class I and class II differential expression, which outperformed traditional clinical metrics in predicting patient survival. We also characterized the distribution of HLA supertypes across cancers and showed that patients with high HLA allelic diversity and gene expression had better prognosis. Immune microenvironments with varied survival outcomes could be predicted using a neural network model trained on HLA expression data. Furthermore, we identified a subset of tumors which upregulated HLA class I but not class II genes and exploited HLA-mediated escape strategies. Our results suggest the potential of using HLA expression data to predict patient prognosis. Taken together, we emphasize the crucial role of HLA upregulation in shaping prolonged anti-tumor immunity. Synopsis In a retrospective analysis of 11080 patients of 33 TCGA cancer types, we showed HLA class I and class II differential expression shape various immune microenvironments and tumor immunoediting mechanisms, predicting tumor immunogenicity and patient survival.
科研通智能强力驱动
Strongly Powered by AbleSci AI