ArticleBMC bioinformatics2015
An integrated network of microRNA and gene expression in ovarian cancer.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 31 citations in OpenAlex.
- Elucidation of dynamic microRNA regulations in cancer progression using integrative machine learning.Briefings in bioinformatics · 2021Article
- Gene-based mediation analysis in epigenetic studies.Briefings in bioinformatics · 2021Article
- Transcriptome sequencing identifies genes associated with invasion of ovarian cancer.The Journal of international medical research · 2020Article
- Circulating microRNA trafficking and regulation: computational principles and practice.Briefings in bioinformatics · 2020Review
- miR-1224-5p inhibits the proliferation and invasion of ovarian cancer via targeting SND1.Human cell · 2020Article
- A parallelized strategy for epistasis analysis based on Empirical Bayesian Elastic Net models.Bioinformatics (Oxford, England) · 2020Article
- Exploring drivers of gene expression in the Cancer Genome Atlas.Bioinformatics (Oxford, England) · 2019Article
- Prediction of microRNA and gene target from an integrated network in chronic obstructive pulmonary disease based on canonical correlation analysis.Technology and health care : official journal of the European Society for Engineering and Medicine · 2018Article
- Epistasis analysis of microRNAs on pathological stages in colon cancer based on an Empirical Bayesian Elastic Net method.BMC genomics · 2017Article
- Dissecting the regulation rules of cancer-related miRNAs based on network analysis.Scientific reports · 2016Article
- Cyclin Y regulates the proliferation, migration, and invasion of ovarian cancer cells via Wnt signaling pathway.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2016Article
- Differential Regulatory Analysis Based on Coexpression Network in Cancer Research.BioMed research international · 2016Review
- Genome-wide analysis of microRNA and mRNA expression signatures in cancer.Acta pharmacologica Sinica · 2015Review
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOvarian cancer is a deadly female reproductive cancer. Understanding the biological mechanisms underlying ovarian cancer could help lead to quicker and more accurate diagnosis and more effective treatments. Both changes in microRNA(miRNA) expression and miRNA/mRNA dysregulation have been associated with ovarian cancer. With the availability of whole-genome miRNA and mRNA sequencing we now have new potentials to study these associations. In this study, we performed a comprehensive analysis of miRNA and mRNA expression in ovarian cancer using an integrative network approach combined with association analysis.
resultsWe developed an integrative approach to construct a network that illustrates the complex interplay among miRNA and gene expression from a systems perspective. Our method is composed of expanding networks from eQTL associations, building network associations in eQTL analysis, and then combine the networks into an integrated network. This integrated network takes account of miRNA expression quantitative trait loci (eQTL) associations, miRNAs and their targets, protein-protein interactions, co-expressions among miRNAs and genes respectively. Applied to the ovarian cancer data set from The Cancer Genome Atlas (TCGA), we created an integrated network with 167 nodes containing 108 miRNA-target interactions and 145 from protein-protein interactions, starting from 44 initial eQTLs. This integrated network encompassed 26 genes and 14 miRNAs associated with cancer. In particular, 11 genes and 12 miRNAs in the integrated network are associated with ovarian cancer.
conclusionWe demonstrated an integrated network approach that integrates multiple data sources at a systems level. We applied this approach to the TCGA ovarian cancer dataset, and constructed a network that provided a more inclusive view of miRNA and gene expression in ovarian cancer. This network included four separate types of interactions among miRNAs and genes. Simply analyzing each interaction component in isolation, such as the eQTL associations, the miRNA-target interactions or the protein-protein interactions, would create a much more limited network than the integrated one.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.