ArticlePloS one2014
Integrative identification of deregulated miRNA/TF-mediated gene regulatory loops and networks in prostate cancer.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
21 citing papers in PubMed, 32 citations in OpenAlex.
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- A microRNA CRISPR screen reveals microRNA-483-3p as an apoptotic regulator in prostate cancer cells.Cell death & disease · 2025Article
- Identification of potential microRNA diagnostic panels and uncovering regulatory mechanisms in breast cancer pathogenesis.Scientific reports · 2022Article
- Upregulated GATA3/miR205-5p Axis Inhibits MFNG Transcription and Reduces the Malignancy of Triple-Negative Breast Cancer.Cancers · 2022Article
- A developmental stage-specific network approach for studying dynamic co-regulation of transcription factors and microRNAs during craniofacial development.Development (Cambridge, England) · 2020Article
- MicroRNA and transcription factor co-regulatory networks and subtype classification of seminoma and non-seminoma in testicular germ cell tumors.Scientific reports · 2020Article
- An in-silico approach for discovery of microRNA-TF regulation of DISC1 interactome mediating neuronal migration.NPJ systems biology and applications · 2019Article
- From Single Level Analysis to Multi-Omics Integrative Approaches: A Powerful Strategy towards the Precision Oncology.High-throughput · 2018Review
- Anabolic Androgenic Steroids: Searching New Molecular Biomarkers.Frontiers in pharmacology · 2018Review
- Construction and analysis of mRNA, miRNA, lncRNA, and TF regulatory networks reveal the key genes associated with prostate cancer.PloS one · 2018Article
- Detecting the Molecular System Signatures of Idiopathic Pulmonary Fibrosis through Integrated Genomic Analysis.Scientific reports · 2017Article
- Systems biology study of transcriptional and post-transcriptional co-regulatory network sheds light on key regulators involved in important biological processes inPhysiology and molecular biology of plants : an international journal of functional plant biology · 2017Article
- miR-143 Induces the Apoptosis of Prostate Cancer LNCap Cells by Suppressing Bcl-2 Expression.Medical science monitor : international medical journal of experimental and clinical research · 2017Article
- Article
- Screening the key microRNAs and transcription factors in prostate cancer based on microRNA functional synergistic relationships.Medicine · 2017Article
- Article
- Elucidating MicroRNA Regulatory Networks Using Transcriptional, Post-transcriptional, and Histone Modification Measurements.Cell reports · 2016Article
- Analysis of miRNA, mRNA, and TF interactions through network-based methods.EURASIP journal on bioinformatics & systems biology · 2015Article
- Article
- MicroRNAs as predictive biomarkers and therapeutic targets in prostate cancer.American journal of clinical and experimental urology · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
MicroRNAs (miRNAs) have attracted a great deal of attention in biology and medicine. It has been hypothesized that miRNAs interact with transcription factors (TFs) in a coordinated fashion to play key roles in regulating signaling and transcriptional pathways and in achieving robust gene regulation. Here, we propose a novel integrative computational method to infer certain types of deregulated miRNA-mediated regulatory circuits at the transcriptional, post-transcriptional and signaling levels. To reliably predict miRNA-target interactions from mRNA/miRNA expression data, our method collectively utilizes sequence-based miRNA-target predictions obtained from several algorithms, known information about mRNA and miRNA targets of TFs available in existing databases, certain molecular structures identified to be statistically over-represented in gene regulatory networks, available molecular subtyping information, and state-of-the-art statistical techniques to appropriately constrain the underlying analysis. In this way, the method exploits almost every aspect of extractable information in the expression data. We apply our procedure on mRNA/miRNA expression data from prostate tumor and normal samples and detect numerous known and novel miRNA-mediated deregulated loops and networks in prostate cancer. We also demonstrate instances of the results in a number of distinct biological settings, which are known to play crucial roles in prostate and other types of cancer. Our findings show that the proposed computational method can be used to effectively achieve notable insights into the poorly understood molecular mechanisms of miRNA-mediated interactions and dissect their functional roles in cancer in an effort to pave the way for miRNA-based therapeutics in clinical settings.
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Registered trials
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.