ReviewInternational journal of molecular sciences2018
Using microRNA Networks to Understand Cancer.
Review in International journal of molecular sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 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.
The trial behind it
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
56 citing papers in PubMed.
- Upregulation of an Epithelial miRNA Is Associated with Immune Evasion in Progressive Bronchial Premalignant Lesions.Cancer immunology research · 2026Article
- Mucinous cystic neoplasms of the pancreas and liver share a similar DNA methylation profile with mucinous ovarian tumors.The Journal of pathology · 2025Article
- Review
- The 2024 Nobel Prize in Physiology or Medicine: microRNA Takes Center Stage.Non-coding RNA · 2024Article
- Longitudinal MicroRNA Signature of Conversion to Psychosis.Schizophrenia bulletin · 2024Article
- Article
- miRNA Expression Profiles in Ovarian Endometriosis and Two Types of Ovarian Cancer-Endometriosis-Associated Ovarian Cancer and High-Grade Ovarian Cancer.International journal of molecular sciences · 2023Article
- Crosstalk between Long Non-Coding RNA and Spliceosomal microRNA as a Novel Biomarker for Cancer.Non-coding RNA · 2023Review
- Editorial: RNA machines.Frontiers in genetics · 2023Article
- MiRNA/mRNA network topology in hepatitis virus B-related liver cirrhosis reveals miR-20a-5p/340-5p as hubs initiating fibrosis.BMC medical genomics · 2022Article
- Suppressing the PI3K/AKT Pathway by miR-30d-5p Mimic Sensitizes Ovarian Cancer Cells to Cell Death Induced by High-Dose Estrogen.Biomedicines · 2022Article
- Identification of the hsa_circ_0039466/miR-96-5p/FOXO1 regulatory network in hepatocellular carcinoma by whole-transcriptome analysis.Annals of translational medicine · 2022Article
- Identification of Two Exosomal miRNAs in Circulating Blood of Cancer Patients by Using Integrative Transcriptome and Network Analysis.Non-coding RNA · 2022Article
- Targeting non-coding RNAs to overcome cancer therapy resistance.Signal transduction and targeted therapy · 2022Review
- Mechanism of miR-760 Reversing Lung Cancer Immune Escape by Downregulating IDO1 and Eliminating Regulatory T Cells Based on Mathematical Biology.Computational and mathematical methods in medicine · 2022Article
- Comparative mRNA/micro-RNA co-expression network drives melanomagenesis by promoting epithelial-mesenchymal transition and vasculogenic mimicry signaling.Translational oncology · 2021Article
- Identification of MicroRNA-mRNA Networks in Melanoma and Their Association with PD-1 Checkpoint Blockade Outcomes.Cancers · 2021Article
- Bioinformatic Tools for the Analysis and Prediction of ncRNA Interactions.International journal of molecular sciences · 2021Review
- The Cohesin Complex and Its Interplay with Non-Coding RNAs.Non-coding RNA · 2021Review
- Upregulation of miR-144-3p expression attenuates glioma cell viability and invasion by targeting BCL6.Experimental and therapeutic medicine · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Human cancers are characterized by deregulated expression of multiple microRNAs (miRNAs), involved in essential pathways that confer the malignant cells their tumorigenic potential. Each miRNA can regulate hundreds of messenger RNAs (mRNAs), while various miRNAs can control the same mRNA. Additionally, many miRNAs regulate and are regulated by other species of non-coding RNAs, such as circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs). For this reason, it is extremely difficult to predict, study, and analyze the precise role of a single miRNA involved in human cancer, considering the complexity of its connections. Focusing on a single miRNA molecule represents a limited approach. Additional information could come from network analysis, which has become a common tool in the biological field to better understand molecular interactions. In this review, we focus on the main types of networks (monopartite, association networks and bipartite) used for analyzing biological data related to miRNA function. We briefly present the important steps to take when generating networks, illustrating the theory with published examples and with future perspectives of how this approach can help to better select miRNAs that can be therapeutically targeted in cancer.
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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.