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.

可操作的肿瘤抗原的鉴定对于开发几种癌症免疫疗法是必不可少的，包括 T 细胞受体转导的 T 细胞和患者特异性 mRNA 或肽疫苗。大多数已知的肿瘤抗原已通过广泛的分子特征鉴定，如果它们来源于基因组的蛋白质编码区，则被认为是规范的。通过从肿瘤中洗脱与人类白细胞抗原结合的肽并对其进行质谱分析，可以通过将所得光谱与参考数据库进行匹配来识别肽。最近，基于质谱的免疫肽组学已经能够发现非经典抗原——来自蛋白质编码区之外的序列或由非经典抗原加工机制产生的抗原。与转录组学和核糖体分析相结合，这种方法能够识别数千种非规范肽，其中很大一部分可能仅在肿瘤中检测到。针对大量非规范参考的光谱匹配可能会产生误报。然而，灵敏的质谱、分析验证和先进的生物信息学解决方案有望揭示呈递抗原和临床相关靶点的全部情况。