Serial multi-omic analysis of proteome, phosphoproteome, and acetylome provides insights into changes in protein expression, cell signaling, cross-talk and epigenetic pathways involved in disease pathology and treatment. However, ubiquitylome and HLA peptidome data collection used to understand protein degradation and antigen presentation have not together been serialized, and instead require separate samples for parallel processing using distinct protocols. Here we present MONTE, a highly sensitive multi-omic native tissue enrichment workflow, that enables serial, deep-scale analysis of HLA-I and HLA-II immunopeptidome, ubiquitylome, proteome, phosphoproteome, and acetylome from the same tissue sample. We demonstrate that the depth of coverage and quantitative precision of each ‘ome is not compromised by serialization, and the addition of HLA immunopeptidomics enables the identification of peptides derived from cancer/testis antigens and patient specific neoantigens. We evaluate the technical feasibility of the MONTE workflow using a small cohort of patient lung adenocarcinoma tumors.

对蛋白质组、磷酸蛋白质组和乙酰组的连续多组学分析可深入了解疾病病理学和治疗中涉及的蛋白质表达、细胞信号传导、串扰和表观遗传途径的变化。然而，用于了解蛋白质降解和抗原呈递的泛素组和 HLA 肽组数据收集尚未一起序列化，而是需要使用不同协议进行单独的样本并行处理。在这里，我们介绍 MONTE，一种高度灵敏的多组学天然组织富集工作流程，可对同一组织样本中的 HLA-I 和 HLA-II 免疫肽组、泛素组、蛋白质组、磷酸蛋白质组和乙酰组进行连续、深度分析。我们证明每个组的覆盖深度和定量精度不会因序列化而受到影响，并且 HLA 免疫肽组学的添加能够识别源自癌症/睾丸抗原和患者特异性新抗原的肽。我们使用一小群肺腺癌患者来评估 MONTE 工作流程的技术可行性。