抗原
计算生物学
假阳性悖论
生物
转录组
蛋白质组
基因组
质谱法
分子生物学
化学
基因
遗传学
计算机科学
基因表达
色谱法
机器学习
作者
Chloé Chong,George Coukos,Michal Bassani‐Sternberg
标识
DOI:10.1038/s41587-021-01038-8
摘要
The identification of actionable tumor antigens is indispensable for the development of several cancer immunotherapies, including T cell receptor-transduced T cells and patient-specific mRNA or peptide vaccines. Most known tumor antigens have been identified through extensive molecular characterization and are considered canonical if they derive from protein-coding regions of the genome. By eluting human leukocyte antigen-bound peptides from tumors and subjecting these to mass spectrometry analysis, the peptides can be identified by matching the resulting spectra against reference databases. Recently, mass-spectrometry-based immunopeptidomics has enabled the discovery of noncanonical antigens-antigens derived from sequences outside protein-coding regions or generated by noncanonical antigen-processing mechanisms. Coupled with transcriptomics and ribosome profiling, this method enables the identification of thousands of noncanonical peptides, of which a substantial fraction may be detected exclusively in tumors. Spectral matching against the immense noncanonical reference may generate false positives. However, sensitive mass spectrometry, analytical validation and advanced bioinformatics solutions are expected to uncover the full landscape of presented antigens and clinically relevant targets.
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