ArticleNucleic acids research2018
Integrative analysis reveals disrupted pathways regulated by microRNAs in cancer.
Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Analyzing Co-expression Networks with Network Skeleton Extraction.Research square · 2026Article
- MicroRNA Expression Profile in Endometriosis and Endometriosis-Associated Ovarian Cancer-Systematic Review.Cells · 2026Review
- miRVim: Three-dimensional miRNA Structure Database.MicroRNA (Shariqah, United Arab Emirates) · 2025Article
- Spectral divergence prioritizes key classes, genes, and pathways shared between substance use disorders and cardiovascular disease.Frontiers in neuroscience · 2025Article
- Regulatory QTLs affecting miRNA-mRNA interactions in cancer: mechanisms, methods, and clinical implications.Frontiers in molecular biosciences · 2025Review
- Recent advances in the role of polysaccharides in liver diseases: a review.Frontiers in pharmacology · 2025Review
- Exosomal miRNAs and isomiRs: potential biomarkers for type 2 diabetes mellitus.Precision clinical medicine · 2024Review
- Insights Into Colorectal Carcinoma: A Comprehensive Review of MicroRNA Expression Patterns.Cureus · 2024Review
- PanomiR: a systems biology framework for analysis of multi-pathway targeting by miRNAs.Briefings in bioinformatics · 2023Article
- A summary of the current diagnostic methods for, and exploration of the value of microRNAs as biomarkers in, sepsis-associated encephalopathy.Frontiers in neuroscience · 2023Review
- Article
- A Survey on Computational Methods for Investigation on ncRNA-Disease Association through the Mode of Action Perspective.International journal of molecular sciences · 2022Review
- Extracellular Polysaccharide fromJournal of clinical and translational hepatology · 2022Article
- The promise of microRNA-based therapies in Alzheimer's disease: challenges and perspectives.Molecular neurodegeneration · 2021Review
- Linking genotype to phenotype in multi-omics data of small sample.BMC genomics · 2021Article
- Article
- Integrative analysis of layers of data in hepatocellular carcinoma reveals pathway dependencies.World journal of hepatology · 2021Article
- MicroRNA-32-5p inhibits epithelial-mesenchymal transition and metastasis in lung adenocarcinoma by targeting SMAD family 3.Journal of Cancer · 2021Article
- Downregulated KIF3B Induced by miR-605-3p Inhibits the Progression of Colon Cancer via Inactivating Wnt/Journal of oncology · 2021Article
- Long non‑coding RNA NEAT1 promotes ovarian cancer cell invasion and migration by interacting with miR‑1321 and regulating tight junction protein 3 expression.Molecular medicine reports · 2020Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
MicroRNAs (miRNAs) are small endogenous regulatory molecules that modulate gene expression post-transcriptionally. Although differential expression of miRNAs have been implicated in many diseases (including cancers), the underlying mechanisms of action remain unclear. Because each miRNA can target multiple genes, miRNAs may potentially have functional implications for the overall behavior of entire pathways. Here, we investigate the functional consequences of miRNA dysregulation through an integrative analysis of miRNA and mRNA expression data using a novel approach that incorporates pathway information a priori. By searching for miRNA-pathway associations that differ between healthy and tumor tissue, we identify specific relationships at the systems level which are disrupted in cancer. Our approach is motivated by the hypothesis that if an miRNA and pathway are associated, then the expression of the miRNA and the collective behavior of the genes in a pathway will be correlated. As such, we first obtain an expression-based summary of pathway activity using Isomap, a dimension reduction method which can articulate non-linear structure in high-dimensional data. We then search for miRNAs that exhibit differential correlations with the pathway summary between phenotypes as a means of finding aberrant miRNA-pathway coregulation in tumors. We apply our method to cancer data using gene and miRNA expression datasets from The Cancer Genome Atlas and compare ∼105 miRNA-pathway relationships between healthy and tumor samples from four tissues (breast, prostate, lung and liver). Many of the flagged pairs we identify have a biological basis for disruption in cancer.
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