ArticlePloS one2013
Reverse engineering of modified genes by Bayesian network analysis defines molecular determinants critical to the development of glioblastoma.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Integrated Bioinformatics, Environmental Epidemiologic and Genomic Approaches to Identify Environmental and Molecular Links between Endometriosis and Breast Cancer.International journal of molecular sciences · 2015Pooled it
- Identification of hsa-miR-144-3p as a novel immunotherapeutic target for glioblastoma based on disulfidptosis-related analysis.Discover oncology · 2026Article
- Intrinsically disordered SERBP1 regulates translation through topology-driven G-quadruplex recognition.bioRxiv : the preprint server for biology · 2026Article
- Effect of MPP2 and its DNA methylation levels on prognosis of colorectal cancer patients.World journal of surgical oncology · 2024Article
- Article
- Epigenetics and Metabolism Reprogramming Interplay into Glioblastoma: Novel Insights on Immunosuppressive Mechanisms.Antioxidants (Basel, Switzerland) · 2023Review
- Transcriptome Changes in Glioma Cells Cultivated under Conditions of Neurosphere Formation.Cells · 2022Article
- Rab31 promotes the invasion and metastasis of cervical cancer cells by inhibiting MAPK6 degradation.International journal of biological sciences · 2022Article
- A novel COL4A1 variant associated with recurrent epistaxis and glioblastoma.Human genome variation · 2021Article
- The Role of Network Science in Glioblastoma.Cancers · 2021Review
- Structural Characterization of the RNA-Binding Protein SERBP1 Reveals Intrinsic Disorder and Atypical RNA Binding Modes.Frontiers in molecular biosciences · 2021Article
- Nuclear Respiratory Factor 1 (NRF1) Transcriptional Activity-Driven Gene Signature Association with Severity of Astrocytoma and Poor Prognosis of Glioblastoma.Molecular neurobiology · 2020Article
- The RNA-binding protein SERBP1 functions as a novel oncogenic factor in glioblastoma by bridging cancer metabolism and epigenetic regulation.Genome biology · 2020Article
- Expression and clinical significance of basic transcription factor 3 in nasopharyngeal carcinoma.Oncology letters · 2019Article
- Cross-species transcriptional analysis reveals conserved and host-specific neoplastic processes in mammalian glioma.Scientific reports · 2018Article
- Molecular mechanisms underlying gliomas and glioblastoma pathogenesis revealed by bioinformatics analysis of microarray data.Medical oncology (Northwood, London, England) · 2017Article
- Predictive models for pressure ulcers from intensive care unit electronic health records using Bayesian networks.BMC medical informatics and decision making · 2017Article
- Modeling the Attractor Landscape of Disease Progression: a Network-Based Approach.Frontiers in genetics · 2017Article
- Estrogenic Endocrine Disrupting Chemicals Influencing NRF1 Regulated Gene Networks in the Development of Complex Human Brain Diseases.International journal of molecular sciences · 2016Review
- The Critical Role of Rab31 in Cell Proliferation and Apoptosis in Cancer Progression.Molecular neurobiology · 2016Article
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Authors and funding
3 authors.
Funding
Abstract
In this study we have identified key genes that are critical in development of astrocytic tumors. Meta-analysis of microarray studies which compared normal tissue to astrocytoma revealed a set of 646 differentially expressed genes in the majority of astrocytoma. Reverse engineering of these 646 genes using Bayesian network analysis produced a gene network for each grade of astrocytoma (Grade I-IV), and 'key genes' within each grade were identified. Genes found to be most influential to development of the highest grade of astrocytoma, Glioblastoma multiforme were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. All of these genes were up-regulated, except MPP2 (down regulated). These 10 genes were able to predict tumor status with 96-100% confidence when using logistic regression, cross validation, and the support vector machine analysis. Markov genes interact with NFkβ, ERK, MAPK, VEGF, growth hormone and collagen to produce a network whose top biological functions are cancer, neurological disease, and cellular movement. Three of the 10 genes - EGFR, COL4A1, and CDK4, in particular, seemed to be potential 'hubs of activity'. Modified expression of these 10 Markov Blanket genes increases lifetime risk of developing glioblastoma compared to the normal population. The glioblastoma risk estimates were dramatically increased with joint effects of 4 or more than 4 Markov Blanket genes. Joint interaction effects of 4, 5, 6, 7, 8, 9 or 10 Markov Blanket genes produced 9, 13, 20.9, 26.7, 52.8, 53.2, 78.1 or 85.9%, respectively, increase in lifetime risk of developing glioblastoma compared to normal population. In summary, it appears that modified expression of several 'key genes' may be required for the development of glioblastoma. Further studies are needed to validate these 'key genes' as useful tools for early detection and novel therapeutic options for these tumors.
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