2-Hydroxyisobutyrylation and Phosphorylation Crosstalk Guides Metastasis Prediction and Immunotherapy in Esophageal Squamous Cell Carcinoma

Posttranslational modification (PTM) is pivotal in cancer progression. However, the mechanisms, biological function, andclinical 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 proteinsco-modified by Khib and phosphorylation on distinct residues. Interestingly, while the two PTMs target distinct motifs acrossproteins, 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 andpotentiating phosphorylation events. Machine learning-based artificial intelligence (AI) analysis of secreted proteins with PTMcrosstalk revealed an independent and highly effective plasma signature predicting lymph node metastasis. Moreover, molecularsubtyping 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 themechanistic basis of Khib-phosphorylation crosstalk, identifying a novel plasma biomarker for lymph node metastasis, andproviding a therapeutic strategy to sensitize tumors to immunotherapy, this work collectively advances the precision diagnosis and treatment of ESCC.