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Cited by 285

The DOI matches its Crossref record; 85 of the 85 references it cites were found in a registry or an index.

The MicroRNA-17-92 Family of MicroRNA Clusters in Development and Disease

Open access
Concepcion, Carla P., Bonetti, Ciro, Ventura, Andrea·2012·The Cancer Journal

Abstract

Overwhelming experimental evidence accumulated over the past decade indicates that microRNAs (miRNAs) are key regulators of gene expression in animals and plants and play important roles in development, homeostasis, and disease. The miR-17-92 family of miRNA clusters is composed of 3 related, highly conserved, polycistronic miRNA genes that collectively encode for a total of 15 miRNAs. We discuss recent studies demonstrating that these miRNAs are essential for vertebrate development and homeostasis. We also show how their mutation or deregulation contributes to the pathogenesis of a variety of human diseases, including cancer and congenital developmental defects. Finally, we discuss the current evidence suggesting how the different miRNAs encoded by these 3 clusters can functionally cooperate to fine-tune signaling and developmental pathways.

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Crossref · 10.1097/ppo.0b013e318258b60a

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Citations

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Metadata

Authors
Concepcion, C. P., Bonetti, C., & Ventura, A.
Venue
The Cancer Journal
Published
2012-05
Volume
18
Issue
3
Pages
262-267
ISSN
1528-9117 (ISSN-L)
OpenAlex
W2316081269
Cited by
285
References
85
FWCI
4.62
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: The MicroRNA-17-92 Family of MicroRNA Clusters in Development and Disease. https://app.cochat.ai/papers/10.1097/ppo.0b013e318258b60a
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Concepcion, C. P., Bonetti, C., & Ventura, A. (2012). The MicroRNA-17-92 Family of MicroRNA Clusters in Development and Disease. The Cancer Journal. https://doi.org/10.1097/ppo.0b013e318258b60a

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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.