Abstract 2028: Using bioinformatic analysis of proteomic data to probe novel drug mechanism of action

Abstract Introduction: Metastasis is a major cause of death for patients with solid tumors. Our group has discovered a selective inhibitor of cell motility, KBU2046, that blocks the activation of Raf1 by inhibiting the phosphorylation of ser338 on its activation motif (Nature Communications 2018). To better understand the effect of KBU2046 on human prostate cancer (PCa) cells, we undertook a proteomic analysis. Experimental Procedures: After treatment of PC3 cells with KBU2046 or vehicle (N=3/group), protein expression of whole cell lysate was quantified by Liquid Chromatography/Tandem Mass Spectrometry analysis (LC-MS/MS). In separate experiments (N=4), membrane fractions were isolated, and LC-MS/MS was performed after Tandem Mass Tag (TMT) labeling. Resultant data were analyzed by several complementary bioinformatics tools, including: Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO) term analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, Ingenuity Pathway Analysis (IPA), and protein-protein interaction (PPI) network analysis to characterize the proteins that were significantly differentially expressed upon KBU2046 treatment. Results: Independent bioinformatic analyses of differentially expressed proteins affected by KBU2046 treatment identify significantly enriched processes related to cell motility, inclusive of effects on structural machinery. This constitutes orthogonal confirmation of KBU2046’s known effects on cell motility. Of importance, major effects on cellular energy-generating processes were also identified. This is consistent with prior studies that found changes in motility induce obligatorye changes in cellular energy requirements. Our focused analysis of membrane fractions identified changes in membranous compartments, providing a relevant positive control for bioinformatic analysis, which we confirmed by Western blot. Analytics also pointed to a major role for adhesion proteins in response to KBU2046, consistent with our prior identification of primary effects on cell migration. Conclusions: These findings provide orthogonal mechanistically relevant support for a novel acting agent. They highlight the ability of proteomics and bioinformatic tools to efficiently probe the mechanism of action and global impact on PCa in response to treatment. Citation Format: Weining Chen, Nicholas Woods, Fangfang Qiao, Henry Chun Hin Law, Sankarasubramanian Jagadesan, Chittibabu Guda, Raymond C. Bergan. Using bioinformatic analysis of proteomic data to probe novel drug mechanism of action [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2028.