metformin

metformin analyzes phosphoproteomic responses in colorectal cancer (CRC) cells to elucidate metformin's signaling mechanisms and pharmacodynamic interactions.

Key Features:

• Phosphoproteomics Integration: High-resolution data-independent acquisition mass spectrometry (DIA-MS) quantifies 10,142 proteins and 56,080 phosphosites in CRC cells treated with metformin over short and long durations.
• Signaling Network Analysis: Integrative analysis combining phosphoproteomics, bioinformatics, and cell proliferation assays across 12 molecularly heterogeneous CRC cell lines characterizes how metformin remodels signaling, primarily in the long term, with minimal changes to total proteome expression levels.
• Heterogeneous Response Mapping: Network analysis infers kinase and phosphatase activities to capture highly variable phosphorylation responses among different CRC cell lines and reconstruct affected signaling pathways.
• MetScore Development: The MetScore metric evaluates the relevance of individual phosphorylation sites to metformin treatment, highlighting robust phosphorylation nodes and pathways.
• Pharmacodynamic Interaction Identification: The metformin phosphosite signature is leveraged to identify pharmacodynamic interactions and candidate drugs interacting with metformin signaling, including navitoclax (a BCL-2/BCL-xL inhibitor).

Scientific Applications:

• Mechanistic dissection: Elucidating metformin's signaling mechanisms in colorectal cancer (CRC) at the phosphoproteome level.
• Therapeutic prioritization: Prioritizing phosphorylation sites and pathways for therapeutic targeting using the MetScore metric.
• Drug interaction discovery: Identifying candidate pharmacodynamic interactions and combination strategies, exemplified by navitoclax involvement.
• Heterogeneity-informed research: Enabling comparisons across 12 molecularly heterogeneous CRC cell lines to inform personalized oncology hypotheses.

Methodology:

Data-independent acquisition mass spectrometry (DIA-MS), integrative phosphoproteomics and bioinformatics analyses, cell proliferation assays, network inference of kinase and phosphatase activities, MetScore computation, and phosphosite-signature-based identification of pharmacodynamic interactions.