Perturbation biology links temporal protein changes to drug responses in a melanoma cell line.

Publication date: Jul 15, 2020

Cancer cells have genetic alterations that often directly affect intracellular protein signaling processes allowing them to bypass control mechanisms for cell death, growth and division. Cancer drugs targeting these alterations often work initially, but resistance is common. Combinations of targeted drugs may overcome or prevent resistance, but their selection requires context-specific knowledge of signaling pathways including complex interactions such as feedback loops and crosstalk. To infer quantitative pathway models, we collected a rich dataset on a melanoma cell line: Following perturbation with 54 drug combinations, we measured 124 (phospho-)protein levels and phenotypic response (cell growth, apoptosis) in a time series from 10 minutes to 67 hours. From these data, we trained time-resolved mathematical models that capture molecular interactions and the coupling of molecular levels to cellular phenotype, which in turn reveal the main direct or indirect molecular responses to each drug. Systematic model simulations identified novel combinations of drugs predicted to reduce the survival of melanoma cells, with partial experimental verification. This particular application of perturbation biology demonstrates the potential impact of combining time-resolved data with modeling for the discovery of new combinations of cancer drugs.

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Concepts Keywords
Apoptosis Apoptosis
Cell Growth Interactome
Coupling Medicine
Crosstalk RTT
Division Melanoma
Genetic Molecular biology
Intracellular Systems biology
Melanoma Rich melanoma
Perturbation Survival melanoma
Phenotype Bypass
Phenotypic Branches of biology
Protein Cancer
Time Resolved

Semantics

Type Source Name
drug DRUGBANK Flunarizine
drug DRUGBANK Trestolone
drug DRUGBANK Trametinib
drug DRUGBANK Medium-chain triglycerides
pathway KEGG Insulin resistance
disease MESH insulin resistance
drug DRUGBANK Erythropoietin
disease MESH B Cell Lymphoma
drug DRUGBANK Esomeprazole
drug DRUGBANK Cysteamine
drug DRUGBANK Serine
drug DRUGBANK L-Tyrosine
drug DRUGBANK Technetium Tc-99m pertechnetate
drug DRUGBANK L-Phenylalanine
drug DRUGBANK Iron
drug DRUGBANK Lapatinib
drug DRUGBANK Erlotinib
drug DRUGBANK Mecasermin
disease MESH uncertainty
drug DRUGBANK Alpelisib
drug DRUGBANK Streptomycin
drug DRUGBANK Rifampicin
disease MESH Spotting
disease MESH immuno
drug DRUGBANK Tantalum
drug DRUGBANK Caffeine
drug DRUGBANK L-Arginine
disease MESH dedifferentiated liposarcoma
drug DRUGBANK Rasagiline
drug DRUGBANK Vemurafenib
drug DRUGBANK Coenzyme M
disease MESH death
drug DRUGBANK Dimethyl sulfoxide
drug DRUGBANK Ademetionine
disease MESH growth
disease MESH Cancer
pathway KEGG Melanoma
disease MESH melanoma
drug DRUGBANK Gefitinib
drug DRUGBANK Honey
pathway KEGG Apoptosis

Original Article

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