{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Rosenberger G"],"funding":["U.S. Department of Health & Human Services | NIH | National Cancer Institute","NCI NIH HHS","NIH HHS","NIGMS NIH HHS"],"pagination":["3909"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11082183"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["15(1)"],"pubmed_abstract":["Aberrant signaling pathway activity is a hallmark of tumorigenesis and progression, which has guided targeted inhibitor design for over 30 years. Yet, adaptive resistance mechanisms, induced by rapid, context-specific signaling network rewiring, continue to challenge therapeutic efficacy. Leveraging progress in proteomic technologies and network-based methodologies, we introduce Virtual Enrichment-based Signaling Protein-activity Analysis (VESPA)-an algorithm designed to elucidate mechanisms of cell response and adaptation to drug perturbations-and use it to analyze 7-point phosphoproteomic time series from colorectal cancer cells treated with clinically-relevant inhibitors and control media. Interrogating tumor-specific enzyme/substrate interactions accurately infers kinase and phosphatas"],"journal":["Nature communications"],"pubmed_title":["Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis."],"pmcid":["PMC11082183"],"funding_grant_id":["R01 GM137031","U54 CA209997","U54 CA274506","S10 OD012351","S10 OD032433","R35 GM139585","U01 CA272610","S10 OD021764"],"pubmed_authors":["Kerwin P","Karan C","Rosenberger G","He J","Griffin AT","Turunen M","Honig B","Li W","Liu Y","Pampou S","Murray D","Califano A","Subramaniam PS"],"additional_accession":[]},"is_claimable":false,"name":"Network-based elucidation of colon cancer drug resistance mechanisms by phosphoproteomic time-series analysis.","description":"Aberrant signaling pathway activity is a hallmark of tumorigenesis and progression, which has guided targeted inhibitor design for over 30 years. Yet, adaptive resistance mechanisms, induced by rapid, context-specific signaling network rewiring, continue to challenge therapeutic efficacy. Leveraging progress in proteomic technologies and network-based methodologies, we introduce Virtual Enrichment-based Signaling Protein-activity Analysis (VESPA)-an algorithm designed to elucidate mechanisms of cell response and adaptation to drug perturbations-and use it to analyze 7-point phosphoproteomic time series from colorectal cancer cells treated with clinically-relevant inhibitors and control media. Interrogating tumor-specific enzyme/substrate interactions accurately infers kinase and phosphatas","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 May","modification":"2026-07-15T14:04:35.38Z","creation":"2025-09-01T03:08:12.44Z"},"accession":"S-EPMC11082183","cross_references":{"pubmed":["38724493"],"doi":["10.1038/s41467-024-47957-3"]}}