ArticleJournal of neuro-oncology2012
Combined gene expression and protein interaction analysis of dynamic modularity in glioma prognosis.
Article in Journal of neuro-oncology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 46 citations in OpenAlex.
- miR-137: A Novel Therapeutic Target for Human Glioma.Molecular therapy. Nucleic acids · 2020Review
- Differential network analysis and protein-protein interaction study reveals active protein modules in glucocorticoid resistance for infant acute lymphoblastic leukemia.Molecular medicine (Cambridge, Mass.) · 2019Article
- miR-128-3p inhibits glioma cell proliferation and differentiation by targeting NPTX1 through IRS-1/PI3K/AKT signaling pathway.Experimental and therapeutic medicine · 2019Article
- FOXK1 promotes cell growth through activating wnt/β-catenin pathway and emerges as a novel target of miR-137 in glioma.American journal of translational research · 2018Article
- BAF53a is a potential prognostic biomarker and promotes invasion and epithelial-mesenchymal transition of glioma cells.Oncology reports · 2017Article
- A Computational Method of Defining Potential Biomarkers based on Differential Sub-Networks.Scientific reports · 2017Article
- Identification of potential key genes associated with glioblastoma based on the gene expression profile.Oncology letters · 2017Article
- A New Strategy for Analyzing Time-Series Data Using Dynamic Networks: Identifying Prospective Biomarkers of Hepatocellular Carcinoma.Scientific reports · 2016Article
- Upregulation of miR-183 expression and its clinical significance in human brain glioma.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2016Article
- Fundamentals of protein interaction network mapping.Molecular systems biology · 2015Review
- Decreased expression of microRNA-107 predicts poorer prognosis in glioma.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2015Article
- Clinical and prognostic significance of high-mobility group box-1 in human gliomas.Experimental and therapeutic medicine · 2015Article
- Pathway mapping and development of disease-specific biomarkers: protein-based network biomarkers.Journal of cellular and molecular medicine · 2015Review
- Downregulation of microRNA-124 predicts poor prognosis in glioma patients.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2015Article
- Combined detection of Gab1 and Gab2 expression predicts clinical outcome of patients with glioma.Medical oncology (Northwood, London, England) · 2014Article
- Decreased expression of microRNA-206 correlates with poor clinical outcome in patients with malignant astrocytomas.Pathology oncology research : POR · 2014Article
- Causal inference of gene regulation with subnetwork assembly from genetical genomics data.Nucleic acids research · 2014Article
- Increased expression of microRNA-9 predicts an unfavorable prognosis in human glioma.Molecular and cellular biochemistry · 2013Article
- TCTP overexpression is associated with the development and progression of glioma.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2013Article
- Dynamic protein interaction modules in human hepatocellular carcinoma progression.BMC systems biology · 2013Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Because of the variety of factors affecting glioma prognosis, prediction of patient survival is particularly difficult. Protein-protein interaction (PPI) networks have been considered with regard to how their spatial characteristics relate to glioma. However, the dynamic nature of PPIs in vivo makes them temporally and spatially complex events. Integration of prognosis-specific co-expression information adds further dynamic features to these networks. Although some biomarkers for glioma prognosis have been identified, none is sufficient for accurate prediction of either prognosis or improved survival. We have established co-expressed protein-interaction networks that integrate protein-protein interactions with glioma gene-expression profiles related to different survival times. Biomarkers related to glioma prognosis were identified by comparative analysis of the dynamic features of the glioma prognosis network, particularly subnetworks. Four significantly differently expressed genes (SDEGs) are upregulated and ten SDEGs downregulated as lifetime is extended. In addition, 97 enhanced differently co-expressed protein interactions (DCPIs) and 99 weakened DCPIs were associated with glioma patient lifetime extension. We propose a method for estimating glioma prognosis on the basis of the construction of a dynamic modular network. We have used this method to identify dynamic genes and interactions related to glioma prognosis. Among these, enhanced MYC expression was related to lifetime extension, as were interactions between E2F1 and RB1 and between EGFR and p38. This method is a novel means of studying the molecular mechanisms determining prognosis in glioma.
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