Dataset Information

Identifying novel glioma associated pathways based on systems biology level meta-analysis.

ABSTRACT: BACKGROUND: With recent advances in microarray technology, including genomics, proteomics, and metabolomics, it brings a great challenge for integrating this "-omics" data to analysis complex disease. Glioma is an extremely aggressive and lethal form of brain tumor, and thus the study of the molecule mechanism underlying glioma remains very important. To date, most studies focus on detecting the differentially expressed genes in glioma. However, the meta-analysis for pathway analysis based on multiple microarray datasets has not been systematically pursued. RESULTS: In this study, we therefore developed a systems biology based approach by integrating three types of omics data to identify common pathways in glioma. Firstly, the meta-analysis has been performed to study the overlapping of signatures at different levels based on the microarray gene expression data of glioma. Among these gene expression datasets, 12 pathways were found in GeneGO database that shared by four stages. Then, microRNA expression profiles and ChIP-seq data were integrated for the further pathway enrichment analysis. As a result, we suggest 5 of these pathways could be served as putative pathways in glioma. Among them, the pathway of TGF-beta-dependent induction of EMT via SMAD is of particular importance. CONCLUSIONS: Our results demonstrate that the meta-analysis based on systems biology level provide a more useful approach to study the molecule mechanism of complex disease. The integration of different types of omics data, including gene expression microarrays, microRNA and ChIP-seq data, suggest some common pathways correlated with glioma. These findings will offer useful potential candidates for targeted therapeutic intervention of glioma.

SUBMITTER: Hu Y

PROVIDER: S-EPMC3866263 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Identifying novel glioma associated pathways based on systems biology level meta-analysis.

Hu Yangfan Y Li Jinquan J Yan Wenying W Chen Jiajia J Li Yin Y Hu Guang G Shen Bairong B

BMC systems biology 20131217

<h4>Background</h4>With recent advances in microarray technology, including genomics, proteomics, and metabolomics, it brings a great challenge for integrating this "-omics" data to analysis complex disease. Glioma is an extremely aggressive and lethal form of brain tumor, and thus the study of the molecule mechanism underlying glioma remains very important. To date, most studies focus on detecting the differentially expressed genes in glioma. However, the meta-analysis for pathway analysis base ...[more]

PMID: 24565222

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Project description:Preeclampsia is a disease of the mother, fetus, and placenta, and the gaps in our understanding of the complex interactions among their respective disease pathways preclude successful treatment and prevention. The placenta has a key role in the pathogenesis of the terminal pathway characterized by exaggerated maternal systemic inflammation, generalized endothelial damage, hypertension, and proteinuria. This sine qua non of preeclampsia may be triggered by distinct underlying mechanisms that occur at early stages of pregnancy and induce different phenotypes. To gain insights into these molecular pathways, we employed a systems biology approach and integrated different "omics," clinical, placental, and functional data from patients with distinct phenotypes of preeclampsia. First trimester maternal blood proteomics uncovered an altered abundance of proteins of the renin-angiotensin and immune systems, complement, and coagulation cascades in patients with term or preterm preeclampsia. Moreover, first trimester maternal blood from preterm preeclamptic patients in vitro dysregulated trophoblastic gene expression. Placental transcriptomics of women with preterm preeclampsia identified distinct gene modules associated with maternal or fetal disease. Placental "virtual" liquid biopsy showed that the dysregulation of these disease gene modules originates during the first trimester. In vitro experiments on hub transcription factors of these gene modules demonstrated that DNA hypermethylation in the regulatory region of ZNF554 leads to gene down-regulation and impaired trophoblast invasion, while BCL6 and ARNT2 up-regulation sensitizes the trophoblast to ischemia, hallmarks of preterm preeclampsia. In summary, our data suggest that there are distinct maternal and placental disease pathways, and their interaction influences the clinical presentation of preeclampsia. The activation of maternal disease pathways can be detected in all phenotypes of preeclampsia earlier and upstream of placental dysfunction, not only downstream as described before, and distinct placental disease pathways are superimposed on these maternal pathways. This is a paradigm shift, which, in agreement with epidemiological studies, warrants for the central pathologic role of preexisting maternal diseases or perturbed maternal-fetal-placental immune interactions in preeclampsia. The description of these novel pathways in the "molecular phase" of preeclampsia and the identification of their hub molecules may enable timely molecular characterization of patients with distinct preeclampsia phenotypes.

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Identifying novel glioma associated pathways based on systems biology level meta-analysis.

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Identifying novel glioma associated pathways based on systems biology level meta-analysis.

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