Mechanistically detailed systems biology modeling of the HGF/Met pathway in hepatocellular carcinoma

Autor: Yu Zhang, Phuoc T. Tran, Aleksander S. Popel, Richard J. Sové, Ludmila Danilova, Elana J. Fertig, Mark Yarchoan, Adam C. Mirando, Mohammad Jafarnejad, Niranjan B. Pandey
Jazyk: angličtina
Rok vydání: 2019
Předmět:
MAPK/ERK pathway
Sorafenib
Integrins
Carcinoma
Hepatocellular
Pyridines
Integrin
Rilotumumab
Antibodies
Monoclonal
Humanized
General Biochemistry
Genetics and Molecular Biology
Receptor tyrosine kinase
Article
03 medical and health sciences
0302 clinical medicine
Cell Movement
Cell Line
Tumor
Drug Discovery
medicine
Humans
Anilides
Computer Simulation
Protein kinase B
lcsh:QH301-705.5
030304 developmental biology
Cancer
0303 health sciences
biology
Chemistry
Hepatocyte Growth Factor
Applied Mathematics
Systems Biology
Liver Neoplasms
Hep G2 Cells
Proto-Oncogene Proteins c-met
3. Good health
Computer Science Applications
lcsh:Biology (General)
Drug Resistance
Neoplasm
030220 oncology & carcinogenesis
Modeling and Simulation
Computer modelling
Cancer research
biology.protein
Hepatocyte growth factor
Signal transduction
medicine.drug
Signal Transduction
Zdroj: npj Systems Biology and Applications, Vol 5, Iss 1, Pp 1-14 (2019)
NPJ Systems Biology and Applications
ISSN: 2056-7189
DOI: 10.1038/s41540-019-0107-2
Popis: Hepatocyte growth factor (HGF) signaling through its receptor Met has been implicated in hepatocellular carcinoma tumorigenesis and progression. Met interaction with integrins is shown to modulate the downstream signaling to Akt and ERK (extracellular-regulated kinase). In this study, we developed a mechanistically detailed systems biology model of HGF/Met signaling pathway that incorporated specific interactions with integrins to investigate the efficacy of integrin-binding peptide, AXT050, as monotherapy and in combination with other therapeutics targeting this pathway. Here we report that the modeled dynamics of the response to AXT050 revealed that receptor trafficking is sufficient to explain the effect of Met–integrin interactions on HGF signaling. Furthermore, the model predicted patient-specific synergy and antagonism of efficacy and potency for combination of AXT050 with sorafenib, cabozantinib, and rilotumumab. Overall, the model provides a valuable framework for studying the efficacy of drugs targeting receptor tyrosine kinase interaction with integrins, and identification of synergistic drug combinations for the patients.
Oncology: Scientists predict efficacy of cancer therapies Mathematical modeling can be used to predict the efficacy of drug therapies in liver cancer for individual patients. A team lead by Mohammad Jafarnejad at Johns Hopkins University developed a mathematical model of cellular signaling in liver cells that can predict drug interactions affecting the growth pathways in liver cells found to be responsible for tumor formation in liver cancer. The model was calibrated based on available data and was able to predict the efficacy of common therapies and predicted a synergy for a combination of therapies. Overall, the mathematical modeling allowed us to study the differences in efficacy between different drugs and the efficacy of combining drugs. With the expected increase in the availability of patient-specific data, the methods developed here can be used to benefit individual patients by determining which therapies are most likely to be effective.
Databáze: OpenAIRE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje