Dataset Information

Functional network analysis of gene-phenotype connectivity associated with temozolomide.

ABSTRACT:

Rationale

Glioma has a poor survival rate in patients even with aggressive treatment. Temozolomide (TMZ) is the standard chemotherapeutic choice for treating glioma, but TMZ treatment consistently leads to high resistance.

Aim

To investigate the underlying mechanisms of TMZ action with new therapeutic regimens in glioma.

Methods and results

The biological effects of TMZ mainly depend on the three following DNA repair systems: methylguanine methyltransferase (MGMT), mismatch repair (MMR) and base excision repair (BER). Based on related genes in these three systems, web-based tools containing data compiled from open-source databases, including DrugBank, STRING, WebGestalt and ClueGO, were queried, and five common genes along with the top fifteen pathways, including the glioma pathway, were identified. A genomic analysis of the six genes identified in the glioma pathway by cBioPortal indicated that TMZ might exert biological effects via interaction with the tumor protein P53(TP53) signaling axis. Finally, a survival analysis with the six genes in glioma cases (low-grade glioma and glioblastoma multiforme) was conducted using OncoLnc, which might provide directions for the future exploration of prognosis in glioma.

Conclusions

This study indicates that a functional network analysis resembles a "BioGPS", with the ability to draw a web-based scientific map that can productively and cost-effectively associate TMZ with its primary and secondary biological targets.

SUBMITTER: Shi J

PROVIDER: S-EPMC5675653 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Publications

Functional network analysis of gene-phenotype connectivity associated with temozolomide.

Shi Jia J Dong Bo B Zhou Peng P Guan Wei W Peng Ya Y

Oncotarget 20170912 50

<h4>Rationale</h4>Glioma has a poor survival rate in patients even with aggressive treatment. Temozolomide (TMZ) is the standard chemotherapeutic choice for treating glioma, but TMZ treatment consistently leads to high resistance.<h4>Aim</h4>To investigate the underlying mechanisms of TMZ action with new therapeutic regimens in glioma.<h4>Methods and results</h4>The biological effects of TMZ mainly depend on the three following DNA repair systems: methylguanine methyltransferase (MGMT), mismatch ...[more]

PMID: 29152101

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Project description:Purpose:Genistein belongs to the group of isoflavones, which include powerful anticancer agents. Its antitumor properties have been intensively described in many cancers, but related studies assessing ovarian cancer are scarce. The aim of this study was to develop a new method of the underlying mechanisms of genistein's effects and broaden the perspective of targeted therapies in ovarian carcinoma. Materials and methods:Genistein targets were searched in the DrugBank database. Prediction of drug interactions with targets (including secondary targets) was performed with STRING database. Interaction pairs with overall score above 0.9 were recorded for protein-protein interaction (PPI) network generation based on the Cytoscape software. Genes with intense interconnections were grouped into a module. Then, PPI network modules with significance were assessed using Molecular Complex Detection (MCODE) analysis tool. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed for the critical genes. Furthermore, disease targets were searched in Comparative Toxicogenomics Database (CTD). The overlapping targets were studied using a Kaplan-Meier analysis to evaluate ovarian carcinoma survival. Results:A total of 13 direct targets and 372 secondary targets were identified for genistein and further analyzed with the MCODE analysis tool to identify critical genes. The top 72 genes were further assessed with KEGG. Then, the term "ovarian cancer" was searched in CTD, and 123 genes associated only with the marker "T" or "M" were recorded. Next, seven overlapping genes (CDKN1B, PTEN, EGFR, MAPK1, MAPK3, PIK3C, and AKT1) resulting from the intersection of three pathways and 123 genes were obtained from CTD. Elevated CDKN1B amounts showed correlation with overall survival (log-rank P=0.021) according to Kaplan-Meier analysis. Conclusion:The current findings indicated that drug-target-disease network analysis represents a useful tool in gene-phenotype connectivity for genistein in ovarian cancer. Our result also showed that CDKN1B is worthy of further research.

Dataset Information

Functional network analysis of gene-phenotype connectivity associated with temozolomide.

Rationale

Aim

Methods and results

Conclusions

Publications

Functional network analysis of gene-phenotype connectivity associated with temozolomide.

Similar Datasets

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