Europe PMC

This website requires cookies, and the limited processing of your personal data in order to function. By using the site you are agreeing to this as outlined in our privacy notice and cookie policy.

Abstract 


One of the major challenges in cancer gene therapy is the identification of functionally relevant tumor-specific genes as the therapeutic targets. MicroRNAs (miRNAs) are a class of small, 22-25 nucleotides, endogenously expressed noncoding RNA. miRNAs are important genetic regulators: one miRNA can possibly target multiple genes and they can function as tumor promoters (oncogenic miRNAs, oncomirs) or tumor suppressors (anti-oncomirs). Therefore, the identification of misregulated miRNAs in cellular signaling pathways related to oncogenesis can have profound implications for cancer therapy. The epithelial-mesenchymal transition (EMT) converts epithelial cells into mesenchymal cells, a normal embryological process that frequently get activated during cancer invasion and metastasis. Recent evidence also supports the presence of a small subset of self-renewing, stem-like cells within the tumor mass that possess the capacity to seed new tumors and they have been termed 'cancer stem cells (CSC)'. Conceivably, these CSCs could provide a resource for cells that cause therapy resistance. Although the cell origin of CSCs remains to be fully elucidated, a growing body of evidence has demonstrated that the biology of EMT and CSCs is tightly linked with the sequences and compositions of miRNA molecules. Therefore, targeting miRNAs involved in EMT and CSCs regulation can provide novel miRNA-based therapeutic strategies in oncology.

References 


Articles referenced by this article (134)


Show 10 more references (10 of 134)

Citations & impact 


Impact metrics

Jump to Citations

Citations of article over time

Alternative metrics

Altmetric item for https://www.altmetric.com/details/947606
Altmetric
Discover the attention surrounding your research
https://www.altmetric.com/details/947606

Smart citations by scite.ai
Smart citations by scite.ai include citation statements extracted from the full text of the citing article. The number of the statements may be higher than the number of citations provided by EuropePMC if one paper cites another multiple times or lower if scite has not yet processed some of the citing articles.
Explore citation contexts and check if this article has been supported or disputed.
https://scite.ai/reports/10.1038/cgt.2012.58

Supporting
Mentioning
Contrasting
3
54
0

Article citations


Go to all (57) article citations