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人类癌症的免疫原性和免疫沉默

Immunogenicity and Immune Silence in Human Cancer.

机构信息

Division of Oncology and Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA, United States.

Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States.

出版信息

Front Immunol. 2020 Mar 6;11:69. doi: 10.3389/fimmu.2020.00069. eCollection 2020.

DOI:10.3389/fimmu.2020.00069
PMID:32256484
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7092187/
Abstract

Despite recent advances in cancer immunotherapy, the process of immunoediting early in tumorigenesis remains obscure. Here, we employ a mathematical model that utilizes the Cancer Genome Atlas (TCGA) data to elucidate the contribution of individual mutations and HLA alleles to the immunoediting process. We find that common cancer mutations including BRAF-V600E and KRAS-G12D are predicted to bind none of the common HLA alleles, and are thus "immunogenically silent" in the human population. We identify regions of proteins that are not presented by HLA at a population scale, coinciding with frequently mutated hotspots in cancer, and other protein regions broadly presented across the population in which few mutations occur. We also find that 9/29 common HLA alleles contribute disproportionately to the immunoediting of early oncogenic mutations. These data provide insights into immune evasion of common driver mutations and a molecular basis for the association of particular HLA genotypes with cancer susceptibility.

摘要

尽管癌症免疫疗法最近取得了进展,但肿瘤发生早期的免疫编辑过程仍不清楚。在这里,我们采用了一种数学模型,利用癌症基因组图谱(TCGA)数据来阐明个体突变和 HLA 等位基因对免疫编辑过程的贡献。我们发现,常见的癌症突变,包括 BRAF-V600E 和 KRAS-G12D,预计不会与任何常见的 HLA 等位基因结合,因此在人类群体中是“免疫沉默的”。我们确定了在人群中没有 HLA 呈递的蛋白质区域,这些区域与癌症中经常发生突变的热点区域以及在人群中广泛呈递但发生突变较少的其他蛋白质区域相吻合。我们还发现,29 个常见的 HLA 等位基因中有 9 个不成比例地促进了早期致癌突变的免疫编辑。这些数据为常见驱动突变的免疫逃逸提供了深入了解,并为特定 HLA 基因型与癌症易感性的关联提供了分子基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f906/7092187/2b32315733ce/fimmu-11-00069-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f906/7092187/cb1f84794f53/fimmu-11-00069-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f906/7092187/f7435f7e3f3d/fimmu-11-00069-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f906/7092187/b30f8b749bc3/fimmu-11-00069-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f906/7092187/2b32315733ce/fimmu-11-00069-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f906/7092187/cb1f84794f53/fimmu-11-00069-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f906/7092187/f7435f7e3f3d/fimmu-11-00069-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f906/7092187/b30f8b749bc3/fimmu-11-00069-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f906/7092187/2b32315733ce/fimmu-11-00069-g0004.jpg

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Mass Spectrometry Profiling of HLA-Associated Peptidomes in Mono-allelic Cells Enables More Accurate Epitope Prediction.
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