2-Hydroxyisobutyrylation and Phosphorylation Crosstalk Guides Metastasis Prediction and Immunotherapy in Esophageal...

Posttranslational modification (PTM) is pivotal in cancer progression. However, the mechanisms, biological function, and clinical significance underlying PTM crosstalk are unclear. Here, we performed systematic analyses of 2-hydroxyisobutyrylation (Khib), phosphoproteomic, proteomic, and transcriptomic profiles from 60 esophageal squamous cell carcinoma (ESCC) samples, comprising matched normal, primary tumor, and metastatic lymph node tissues. The integrative analysis identified 4499 proteins co-modified by Khib and phosphorylation on distinct residues. Interestingly, while the two PTMs target distinct motifs across proteins, they engage common motifs within individual proteins. Functionally, Khib and phosphorylation show prevalent positive crosstalk linked to metastatic progression. Mechanistically, Khib mediates this intra-protein crosstalk by recruiting kinases and potentiating phosphorylation events. Machine learning-based artificial intelligence (AI) analysis of secreted proteins with PTM crosstalk revealed an independent and highly effective plasma signature predicting lymph node metastasis. Moreover, molecular subtyping stratified ESCC into three groups, with immunotherapy-resistant Subtype 3 associated with the worst survival. While combined treatment of integrin inhibitor cilengitide and immunotherapy exhibited targeted efficacy. By deciphering the mechanistic basis of Khib-phosphorylation crosstalk, identifying a novel plasma biomarker for lymph node metastasis, and providing a therapeutic strategy to sensitize tumors to immunotherapy, this work collectively advances the precision diagnosis and treatment of ESCC.