ArticleNucleic acids research2012
Integrative analysis of gene and miRNA expression profiles with transcription factor-miRNA feed-forward loops identifies regulators in human cancers.
Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.
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Who cites it
56 citing papers in PubMed.
- Novel serum small extracellular vesicle miRNAs with multi-target RCA-CRISPR sensor for liver cancer detection.Journal of translational medicine · 2026Article
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- Predicting the Effect of miRNA on Gene Regulation to Foster Translational Multi-Omics Research-A Review on the Role of Super-Enhancers.Non-coding RNA · 2024Review
- A review on methods for predicting miRNA-mRNA regulatory modules.Journal of integrative bioinformatics · 2022Review
- Multiomics Analysis Identifies SOCS1 as Restraining T Cell Activation and Preventing Graft-Versus-Host Disease.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Article
- Metabolic reprogramming by miRNAs in the tumor microenvironment: Focused on immunometabolism.Frontiers in oncology · 2022Review
- Emerging Role of CREB in Epithelial to Mesenchymal Plasticity of Pancreatic Cancer.Frontiers in oncology · 2022Review
- Identification of Unique Key miRNAs, TFs, and mRNAs in Virulent MTB Infection Macrophages by Network Analysis.International journal of molecular sciences · 2021Article
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- TCF21 regulates miR-10a-5p/LIN28B signaling to block the proliferation and invasion of melanoma cells.PloS one · 2021Article
- Non-Coding RNAs and Extracellular Vehicles: Their Role in the Pathogenesis of Gestational Diabetes Mellitus.Frontiers in endocrinology · 2021Review
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- Integrative analysis reveals novel driver genes and molecular subclasses of hepatocellular carcinoma.Aging · 2020Article
- Multi-omics profiling reveals microRNA-mediated insulin signaling networks.BMC bioinformatics · 2020Article
- Genomic instability and cancer: lessons fromOpen biology · 2020Review
- MicroRNA and transcription factor co-regulatory networks and subtype classification of seminoma and non-seminoma in testicular germ cell tumors.Scientific reports · 2020Article
- Article
- Construction of Glycometabolism- and Hormone-Related lncRNA-Mediated Feedforward Loop Networks Reveals Global Patterns of lncRNAs and Drug Repurposing in Gestational Diabetes.Frontiers in endocrinology · 2020Article
- The exploration of disease-specific gene regulatory networks in esophageal carcinoma and stomach adenocarcinoma.BMC bioinformatics · 2019Article
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Authors and funding
10 authors.
Funding
Abstract
We describe here a novel method for integrating gene and miRNA expression profiles in cancer using feed-forward loops (FFLs) consisting of transcription factors (TFs), miRNAs and their common target genes. The dChip-GemiNI (Gene and miRNA Network-based Integration) method statistically ranks computationally predicted FFLs by their explanatory power to account for differential gene and miRNA expression between two biological conditions such as normal and cancer. GemiNI integrates not only gene and miRNA expression data but also computationally derived information about TF-target gene and miRNA-mRNA interactions. Literature validation shows that the integrated modeling of expression data and FFLs better identifies cancer-related TFs and miRNAs compared to existing approaches. We have utilized GemiNI for analyzing six data sets of solid cancers (liver, kidney, prostate, lung and germ cell) and found that top-ranked FFLs account for ∼20% of transcriptome changes between normal and cancer. We have identified common FFL regulators across multiple cancer types, such as known FFLs consisting of MYC and miR-15/miR-17 families, and novel FFLs consisting of ARNT, CREB1 and their miRNA partners. The results and analysis web server are available at http://www.canevolve.org/dChip-GemiNi.
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