ArticleCPT: pharmacometrics & systems pharmacology2018
Multi-Scale Network Model Supported by Proteomics for Analysis of Combined Gemcitabine and Birinapant Effects in Pancreatic Cancer Cells.
Article in CPT: pharmacometrics & systems pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed, 20 citations in OpenAlex.
- Protein swarm-based cause-effect analysis: effects of microRNAs on cooperation networks linking COVID-19 infections, atherosclerosis, and Alzheimer's disease.Frontiers in cardiovascular medicine · 2025Article
- Effects of vitamin D signaling in cardiovascular disease: centrality of macrophage polarization.Frontiers in cardiovascular medicine · 2024Article
- Systems Pharmacodynamic Model of Combined Gemcitabine and Trabectedin in Pancreatic Cancer Cells. Part I: Effects on Signal Transduction Pathways Related to Tumor GrowthJournal of pharmaceutical sciences · 2024Article
- High-quality and robust protein quantification in large clinical/pharmaceutical cohorts with IonStar proteomics investigation.Nature protocols · 2023Review
- Recent Developments and Applications of Quantitative Proteomics Strategies for High-Throughput Biomolecular Analyses in Cancer Research.RSC chemical biology · 2021Article
- Pharmacodynamic modeling of synergistic birinapant/paclitaxel interactions in pancreatic cancer cells.BMC cancer · 2020Article
- Mechanistic Multiscale Pharmacokinetic Model for the Anticancer Drug 2',2'-difluorodeoxycytidine (Gemcitabine) in Pancreatic Cancer.Clinical and translational science · 2020Article
- SMAC mimetic birinapant inhibits hepatocellular carcinoma growth by activating the cIAP1/TRAF3 signaling pathway.Molecular medicine reports · 2020Article
- Review
- Pharmacodynamic Drug-Drug Interactions.Clinical pharmacology and therapeutics · 2019Review
- Translational Framework Predicting Tumour Response in Gemcitabine-Treated Patients with Advanced Pancreatic and Ovarian Cancer from Xenograft Studies.The AAPS journal · 2019Article
- Physiologically-based pharmacokinetic and pharmacodynamic models for gemcitabine and birinapant in pancreatic cancer xenografts.Journal of pharmacokinetics and pharmacodynamics · 2018Article
- How Do We "Validate" a QSP Model?CPT: pharmacometrics & systems pharmacology · 2018Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Gemcitabine combined with birinapant, an inhibitor of apoptosis protein antagonist, acts synergistically to reduce pancreatic cancer cell proliferation. A large-scale proteomics dataset provided rich time-series data on proteome-level changes that reflect the underlying biological system and mechanisms of action of these drugs. A multiscale network model was developed to link the signaling pathways of cell cycle regulation, DNA damage response, DNA repair, apoptosis, nuclear factor-kappa β (NF-κβ), and mitogen-activated protein kinase (MAPK)-p38 to cell cycle progression, proliferation, and death. After validating the network model under different conditions, the Sobol Sensitivity Analysis was applied to identify promising targets to enhance gemcitabine efficacy. The effects of p53 silencing and combining curcumin with gemcitabine were also tested with the developed model. Merging proteomics analysis with systems modeling facilitates the characterization of quantitative relations among relevant signaling pathways in drug action and resistance, and such multiscale network models could be applied for prediction of combination efficacy and target selection.
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