Abstract Hepatocellular Carcinoma (HCC) is one of the leading causes of cancer-related death worldwide, ranked as the third most fatal cancer after lung and stomach carcinomas. The diverse etiology, high morbidity/mortality, lack of diagnostic markers for early diagnosis and the highly variable clinical course of HCC have hindered advances in diagnosis and treatment. After years of studying the HCC, the understanding of molecular mechanism operational in HCC remains incomplete. The genomic, transcriptomic and comparative proteomic profiles have yielded some important insights for HCC research. However, many studies focused on single aspect of the cellular changes associated with HCC, hindering the full understanding of biological systems in their true complexity and dynamics. We describe a novel approach combining the power of cell biology, integrated proteomics platforms and an informatics platform that generates causal protein networks. In order to delineate the role of post-translation modification and enzymes that partake in such mechanisms, we incorporated activity based proteomics employing kinase enrichment probes and phosphoproteome mapping of total proteins in HCC cellular models. Multikinase inhibitor Sorafenib, the first line chemotherapeuitc agent for the advanced HCC patients, was used to probe the global kinase activity and protein phosphorylation changes associated with this treatment. Comparative proteomics, phosphoproteome and kinase activity data was integrated into the AI based REFS™ informatics platform. Causal networks of protein interaction specifically from a functional stand point namely kinase activity and potential targets that kinases can phosphorylate were generated. In addition, using cellular functional read out, proteins/ kinases that modulate phosphorylation of targets and mechanistically drive pathophysiological cellular behavior were determined. The approach outlined here enables global characterization of cellular responses, insights into mechanisms of chemo sensitivity and potential targets/biomarkers for clinical management of HCC. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4934. doi:1538-7445.AM2012-4934