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Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) remain challenging to differentiate using conventional imaging and single-gene diagnostics. Here, we introduce a novel approach leveraging AlphaFold3-guided structural profiling of protein-protein interactions (PPIs), integrating evolutionary distances (ClustalW dnd) and structural affinity metrics (CS) derived from predicted PPI complexes. We systematically selected 294 PPI pairs from a cancer-wide interactome database with relevance to liver cancers and found that HCC- and ICC-specific PPIs exhibited distinct clustering based on structural and evolutionary features. Notably, discrepancies between sequence divergence and structural affinity suggested that even subtle mutations—previously assumed to be neutral—may have significant structural consequences. Network clustering analysis further revealed divergent oncogenic hubs, with CTNNB1 and TERT dominating HCC-specific interactions and SOX9 driving ICC-specific mesenchymal phenotypes. These findings highlight the power of integrative structural PPI mapping to uncover functionally significant distinctions in tumor biology and suggest a paradigm shift in cancer diagnostics enabled by next-generation structure-based analytics.