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InDePTH: detection of hub genes for developing gene expression networks under anticancer drug treatment.

ABSTRACT: It has been difficult to elucidate the structure of gene regulatory networks under anticancer drug treatment. Here, we developed an algorithm to highlight the hub genes that play a major role in creating the upstream and downstream relationships within a given set of differentially expressed genes. The directionality of the relationships between genes was defined using information from comprehensive collections of transcriptome profiles after gene knockdown and overexpression. As expected, among the drug-perturbed genes, our algorithm tended to derive plausible hub genes, such as transcription factors. Our validation experiments successfully showed the anticipated activity of certain hub gene in establishing the gene regulatory network that was associated with cell growth inhibition. Notably, giving such top priority to the hub gene was not achieved by ranking fold change in expression and by the conventional gene set enrichment analysis of drug-induced transcriptome data. Thus, our data-driven approach can facilitate to understand drug-induced gene regulatory networks for finding potential functional genes.

SUBMITTER: Koido M

PROVIDER: S-EPMC6044382 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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InDePTH: detection of hub genes for developing gene expression networks under anticancer drug treatment.

Koido Masaru M Tani Yuri Y Tsukahara Satomi S Okamoto Yuka Y Tomida Akihiro A

Oncotarget 20180626 49

It has been difficult to elucidate the structure of gene regulatory networks under anticancer drug treatment. Here, we developed an algorithm to highlight the hub genes that play a major role in creating the upstream and downstream relationships within a given set of differentially expressed genes. The directionality of the relationships between genes was defined using information from comprehensive collections of transcriptome profiles after gene knockdown and overexpression. As expected, among ...[more]

PMID: 30018738

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Project description:Chemotherapy-induced cardiac toxicity is an undesirable yet very common effect that increases the risk of death and reduce the quality of life of individuals undergoing chemotherapy. However, no feasible methods and techniques are available to monitor and detect the degree of cardiotoxicity at an early stage. Therefore, in this project, we aim to develop a fluorescent nanoprobe to image the toxicity within the cardiac tissue induced by an anticancer drug. We have observed that vascular cell adhesion molecule 1 (VCAM1) protein alone with collagen was overly expressed within the heart, when an animal was treated with doxorubicin (DOX), because of inflammation in the epithelial cells. We hypothesize that developing a VCAM1-targeted peptide-based (VHPKQHRGGSKGC) fluorescent nanoprobe can detect and visualize the affected heart. In this regard, we prepared a poly(lactic-co-glycolic acid) (PLGA) nanoparticle linked with VCAM1 peptide and rhodamine B (PLGA-VCAM1-RhB). Selective binding and higher accumulation of the PLGA-VCAM1-RhB nanoprobes were detected in DOX-treated human cardiomyocyte cells (HCMs) compared to the untreated cells. For in vivo studies, DOX (5 mg/kg) was injected via the tail vein once in two weeks for 6 weeks (3 injection total). PLGA-VCAM1-RhB and PLGA-RhB were injected via the tail vein after 1 week of the last dose of DOX, and images were taken 4 h after administration. A higher fluorescent signal of PLGA-RhB-VCAM-1 (48.62% ± 12.79%) was observed in DOX-treated animals compared to the untreated control PLGA-RhB (10.61% ± 4.90) within the heart, indicating the specificity and targeting ability of PLGA-VCAM1-RhB to the inflamed tissues. The quantified fluorescence intensity of the homogenized cardiac tissue of PLGA-RhB-VCAM1 showed 156% higher intensity than the healthy control group. We conclude that PLGA-VCAM1-RhB has the potential to bind inflamed cardiac cells, thereby detecting DOX-induced cardiotoxicity and damaged heart at an early stage.

Dataset Information

InDePTH: detection of hub genes for developing gene expression networks under anticancer drug treatment.

Publications

InDePTH: detection of hub genes for developing gene expression networks under anticancer drug treatment.

Similar Datasets

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