Proteins interaction network and modeling of IGVH mutational status in chronic lymphocytic leukemia
| Autor: | Andrés Fernando González Barrios, Sally Yepes, María Camila Alvarez-Silva, Maria Mercedes Torres |
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| Jazyk: | angličtina |
| Předmět: |
PPI network
Chronic lymphocytic leukemia Systems biology Boolean network Health Informatics Computational biology Biology medicine.disease_cause Bioinformatics Models Biological Modelling and Simulation medicine Humans PTEN Protein Interaction Maps Gene Regulation of gene expression Mutation Mechanism (biology) Research medicine.disease Leukemia Lymphocytic Chronic B-Cell Gene Expression Regulation Neoplastic Modeling and Simulation biology.protein DNA microarray Immunoglobulin Heavy Chains Topological analysis CLL |
| Zdroj: | Theoretical Biology & Medical Modelling |
| ISSN: | 1742-4682 |
| DOI: | 10.1186/s12976-015-0008-z |
| Popis: | Background Chronic lymphocytic leukemia (CLL) is an incurable malignancy of mature B-lymphocytes, characterized as being a heterogeneous disease with variable clinical manifestation and survival. Mutational statuses of rearranged immunoglobulin heavy chain variable (IGVH) genes has been consider one of the most important prognostic factors in CLL, but despite of its proven value to predict the course of the disease, the regulatory programs and biological mechanisms responsible for the differences in clinical behavior are poorly understood. Methods In this study, (i) we performed differential gene expression analysis between the IGVH statuses using multiple and independent CLL cohorts in microarrays platforms, based on this information, (ii) we constructed a simplified protein-protein interaction (PPI) network and (iii) investigated its structure and critical genes. This provided the basis to (iv) develop a Boolean model, (v) infer biological regulatory mechanism and (vi) performed perturbation simulations in order to analyze the network in dynamic state. Results The result of topological analysis and the Boolean model showed that the transcriptional relationships of IGVH mutational status were determined by specific regulatory proteins (PTEN, FOS, EGR1, TNF, TGFBR3, IFGR2 and LPL). The dynamics of the network was controlled by attractors whose genes were involved in multiple and diverse signaling pathways, which may suggest a variety of mechanisms related with progression occurring over time in the disease. The overexpression of FOS and TNF fixed the fate of the system as they can activate important genes implicated in the regulation of process of adhesion, apoptosis, immune response, cell proliferation and other signaling pathways related with cancer. Conclusion The differences in prognosis prediction of the IGVH mutational status are related with several regulatory hubs that determine the dynamic of the system. Electronic supplementary material The online version of this article (doi:10.1186/s12976-015-0008-z) contains supplementary material, which is available to authorized users. |
| Databáze: | OpenAIRE |
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