Mapping the tumour human leukocyte antigen (HLA) ligandome by mass spectrometry

被引:83
作者
Freudenmann, Lena Katharina [1 ,2 ]
Marcu, Ana [1 ]
Stevanovic, Stefan [1 ,2 ]
机构
[1] Univ Tubingen, Interfac Inst Cell Biol, Dept Immunol, Morgenstelle 15, D-72076 Tubingen, Germany
[2] German Canc Consortium DKTK, DKFZ Partner Site Tubingen, Tubingen, Germany
关键词
cancer immunotherapy; HLA ligand; immunopeptidome; mass spectrometry; tumour-associated antigen; TAA; BREAST-CANCER PATIENTS; CLASS-I; T-CELLS; PRESENTED PEPTIDES; HUMAN-MELANOMA; PHOSPHORYLATED PEPTIDES; HIGH-THROUGHPUT; MHC LIGANDS; IDENTIFICATION; IMMUNOTHERAPY;
D O I
10.1111/imm.12936
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
The entirety of human leukocyte antigen (HLA)-presented peptides is referred to as the HLA ligandome of a cell or tissue, in tumours often termed immunopeptidome. Mapping the tumour immunopeptidome by mass spectrometry (MS) comprehensively views the pathophysiologically relevant antigenic signature of human malignancies. MS is an unbiased approach stringently filtering the candidates to be tested as opposed to epitope prediction algorithms. In the setting of peptide-specific immunotherapies, MS-based strategies significantly diminish the risk of lacking clinical benefit, as they yield highly enriched amounts of truly presented peptides. Early immunopeptidomic efforts were severely limited by technical sensitivity and manual spectra interpretation. The technological progress with development of orbitrap mass analysers and enhanced chromatographic performance led to vast improvements in mass accuracy, sensitivity, resolution, and speed. Concomitantly, bioinformatic tools were developed to process MS data, integrate sequencing results, and deconvolute multi-allelic datasets. This enabled the immense advancement of tumour immunopeptidomics. Studying the HLA-presented peptide repertoire bears high potential for both answering basic scientific questions and translational application. Mapping the tumour HLA ligandome has started to significantly contribute to target identification for the design of peptide-specific cancer immunotherapies in clinical trials and compassionate need treatments. In contrast to prediction algorithms, rare HLA allotypes and HLA class II can be adequately addressed when choosing MS-guided target identification platforms. Herein, we review the identification of tumour HLA ligands focusing on sources, methods, bioinformatic data analysis, translational application, and provide an outlook on future developments.
引用
收藏
页码:331 / 345
页数:15
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