ArticleBMC systems biology2008
Construction of a cancer-perturbed protein-protein interaction network for discovery of apoptosis drug targets.
Article in BMC systems biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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38 citing papers in PubMed, 98 citations in OpenAlex.
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- Combining phenome-driven drug-target interaction prediction with patients' electronic health records-based clinical corroboration toward drug discovery.Bioinformatics (Oxford, England) · 2020Article
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- HMNPPID-human malignant neoplasm protein-protein interaction database.Human genomics · 2019Article
- A Drug-Side Effect Context-Sensitive Network approach for drug target prediction.Bioinformatics (Oxford, England) · 2019Article
- Hamiltonian energy as an efficient approach to identify the significant key regulators in biological networks.PloS one · 2019Article
- Uncovering the regeneration strategies of zebrafish organs: a comprehensive systems biology study on heart, cerebellum, fin, and retina regeneration.BMC systems biology · 2018Article
- Interacting partners of FEN1 and its role in the development of anticancer therapeutics.Oncotarget · 2017Review
- Cardioprotection Effects of Sevoflurane by Regulating the Pathway of Neuroactive Ligand-Receptor Interaction in Patients Undergoing Coronary Artery Bypass Graft Surgery.Computational and mathematical methods in medicine · 2017Article
- Identification of Novel Pathways in Plant Lectin-Induced Cancer Cell Apoptosis.International journal of molecular sciences · 2016Article
- Temporal Genetic Modifications after Controlled Cortical Impact--Understanding Traumatic Brain Injury through a Systematic Network Approach.International journal of molecular sciences · 2016Article
- Systematic Tracking of Disrupted Modules Identifies Altered Pathways Associated with Congenital Heart Defects in Down Syndrome.Medical science monitor : international medical journal of experimental and clinical research · 2015Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCancer is caused by genetic abnormalities, such as mutations of oncogenes or tumor suppressor genes, which alter downstream signal transduction pathways and protein-protein interactions. Comparisons of the interactions of proteins in cancerous and normal cells can shed light on the mechanisms of carcinogenesis.
resultsWe constructed initial networks of protein-protein interactions involved in the apoptosis of cancerous and normal cells by use of two human yeast two-hybrid data sets and four online databases. Next, we applied a nonlinear stochastic model, maximum likelihood parameter estimation, and Akaike Information Criteria (AIC) to eliminate false-positive protein-protein interactions in our initial protein interaction networks by use of microarray data. Comparisons of the networks of apoptosis in HeLa (human cervical carcinoma) cells and in normal primary lung fibroblasts provided insight into the mechanism of apoptosis and allowed identification of potential drug targets. The potential targets include BCL2, caspase-3 and TP53. Our comparison of cancerous and normal cells also allowed derivation of several party hubs and date hubs in the human protein-protein interaction networks involved in caspase activation.
conclusionOur method allows identification of cancer-perturbed protein-protein interactions involved in apoptosis and identification of potential molecular targets for development of anti-cancer drugs.
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