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Exploiting the Therapeutic Potential of MicroRNAs in Viral Diseases: Expectations and Limitations
Abstract
New therapeutic approaches are urgently needed for serious diseases, including cancer, cardiovascular diseases, viral infections, and others. A recent direction in drug development is the utilization of nucleic acidbased therapeutic molecules, such as antisense oligonucleotides, ribozymes, short interfering RNA (siRNA), and microRNA (miRNA). miRNAs are endogenous, short, non-coding RNA molecules. Some viruses encode their own miRNAs, which play pivotal roles in viral replication and immune evasion strategies. Conversely, viruses that do not encode miRNAs may manipulate host cell miRNAs for the benefits of their replication. miRNAs have therefore become attractive tools for the study of viral pathogenesis. Lately, novel therapeutic strategies based on miRNA technology for the treatment of viral diseases have been progressing rapidly. Although this new generation of molecular therapy is promising, there are still several challenges to face, such as targeting delivery to specific tissues, avoiding off-target effects of miRNAs, reducing the toxicity of the drugs, and overcoming mutations and drug resistance. In this article, we review the current knowledge of the role and therapeutic potential of miRNAs in viral diseases, and discuss the limitations of these therapies, as well as strategies to overcome them to provide safe and effective clinical applications of these new therapeutics.
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“On the other hand, it is important to note that each miRNA can target multiple genes simultaneously due to incomplete pairing, which significantly increases the risk of non-specific effects of miRNA-based therapeutic approaches (Hemida et al. 2010).”
From MiR-124 and MiR-155 as Therapeutic Targets in Microglia-Mediated Inflammation in Multiple Sclerosis (2025) · cites this paper as Hemida et al. 2010
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Moelling, K., Matskevich, A. A., Elzaouk, L., Heinrich, J., Jung, J. S., Kwok, T., & Mathur, S. (2006) · Retrovirology · doi:10.1186/1742-4690-3-s1-s57 · Cited by 3
Pawlotsky, J. (2004) · Current Hepatology Reports · doi:10.1007/s11901-004-0007-8 · Cited by 1
Research works printed but not linked: 4
- Brahmachari SK. Host-virus interaction: a new role for microRNAs. Retrovirology 2006; 3(68): 1–9
- Moens U, Van Ghelue M, Johnannessen M. Human polyomaviruses: molecular mechanisms for transformation and their association with cancer. In: Tuneley EI, editor. New research on oncogenic viruses. New York: Nova Science, 2008: 1–63
- Roizman B, Pellet PE. The family Herpesviridae: a brief introduction. In: Knipe DM, Howley PM, editors. Fields virology. 4th ed. Philadelphia (PA): Lippincott Williams & Wilkins, 2001: 2381–97
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Cited by
Involvement of MicroRNA in Microglia-Mediated Immune Response
Guedes, J., Cardoso, A. L. C., & Pedroso de Lima, M. C. (2013) · Clinical and Developmental Immunology · doi:10.1155/2013/186872 · Cited by 65
MiR-124 and MiR-155 as Therapeutic Targets in Microglia-Mediated Inflammation in Multiple Sclerosis
Asl, E. R., Hosseini, S. E., Tahmasebi, F., Bolandi, N., & Barati, S. (2025) · Cellular and Molecular Neurobiology · doi:10.1007/s10571-025-01578-6 · Cited by 19
Metadata
- Authors
- Hemida, M. G., Ye, X., Thair, S., & Yang, D.
- Venue
- Molecular Diagnosis & Therapy
- Published
- 2010-10
- Volume
- 14
- Issue
- 5
- Pages
- 271-282
- ISSN
- 1177-1062
- 1179-2000
- PMC
- PMC7099301
- Cited by
- 32
- References
- 105
- Language
- en
- Licence
- www.springernature.com/gp/researchers/text-and-data-mining (tdm)
- www.springernature.com/gp/researchers/text-and-data-mining (vor)
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.