The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Clinical Applications for microRNAs in Cancer
Abstract
The discovery that noncoding components of the genome, including microRNA (miRNA or miR), can contribute to the pathogenesis of cancer has led investigators to contemplate using these molecules to guide clinical decision making. Currently, miRNA signatures are being applied in human clinical trials and miRNA-directed therapy is under way, with miR-122 targeting in hepatitis C (HCV) being the most developed therapy thus far. miRNA-based targeting in cancer is not far behind, with several private companies developing therapeutics. We are recognizing the potential for miRNA biology to clarify both the molecular pathogenesis of cancer and the inherent complexities in translating its biology to clinics. An increased understanding of fundamental miRNA biology, improved bioinformatics, and directed in vivo targeting while minimizing off-target effects and toxicity will be required for successful translational application. Here, we provide an overview of miRNAs, with a focus on aspects of translating bench-based discoveries to the clinic.
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Lynch, T. J., Bell, D. W., Sordella, R., Gurubhagavatula, S., Okimoto, R. A., Brannigan, B. W., Harris, P. L., Haserlat, S. M., Supko, J. G., Haluska, F. G., et al. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa040938 · Cited by 11,486
Asangani, I. A., Rasheed, S. A. K., Nikolova, D. A., Leupold, J. H., Colburn, N. H., Post, S., & Allgayer, H. (2008) · Oncogene · doi:10.1038/sj.onc.1210856 · Cited by 1,882
LNA-mediated microRNA silencing in non-human primates
Elmén, J., Lindow, M., Schütz, S., Lawrence, M., Petri, A., Obad, S., Lindholm, M., Hedtjärn, M., Hansen, H. F., Berger, U., et al. (2008) · Nature · doi:10.1038/nature06783 · Cited by 1,589
Modulation of K-Ras-Dependent Lung Tumorigenesis by MicroRNA-21
Hatley, M. E., Patrick, D. M., Garcia, M. R., Richardson, J. A., Bassel-Duby, R., van Rooij, E., & Olson, E. N. (2010) · Cancer Cell · doi:10.1016/j.ccr.2010.08.013 · Cited by 626
MiR-21 is an EGFR-regulated anti-apoptotic factor in lung cancer in never-smokers
Seike, M., Goto, A., Okano, T., Bowman, E. D., Schetter, A. J., Horikawa, I., Mathe, E. A., Jen, J., Yang, P., Sugimura, H., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0905234106 · Cited by 500
Self-citationIntact p53-Dependent Responses in miR-34–Deficient Mice
Concepcion, C. P., Han, Y.-C., Mu, P., Bonetti, C., Yao, E., D'Andrea, A., Vidigal, J. A., Maughan, W. P., Ogrodowski, P., & Ventura, A. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002797 · Cited by 197
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Non-viral vectors for gene-based therapy
Yin, H., Kanasty, R. L., Eltoukhy, A. A., Vegas, A. J., Dorkin, J. R., & Anderson, D. G. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3763 · Cited by 3,123
Serum exosomal microRNAs as novel biomarkers for hepatocellular carcinoma
Sohn, W., Kim, J., Kang, S. H., Yang, S. R., Cho, J.-Y., Cho, H. C., Shim, S. G., & Paik, Y.-H. (2015) · Experimental & Molecular Medicine · doi:10.1038/emm.2015.68 · Cited by 426
Humphries, B., & Yang, C. (2015) · Oncotarget · doi:10.18632/oncotarget.3052 · Cited by 346
Azimzadeh, M., Rahaie, M., Nasirizadeh, N., Ashtari, K., & Naderi-Manesh, H. (2016) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2015.09.020 · Cited by 342
Liu, Y., Zeng, X., He, Z., & Zou, Q. (2017) · IEEE/ACM Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2016.2550432 · Cited by 284
Metadata
- Authors
- Nana-Sinkam, S. P., & Croce, C. M.
- Venue
- Clinical Pharmacology & Therapeutics
- Publisher
- Wiley
- Published
- 2012-12-05
- Volume
- 93
- Issue
- 1
- Pages
- 98-104
- ISSN
- 0009-9236 (ISSN-L)
- 1532-6535
- OpenAlex
- W1978025728
- Cited by
- 352
- References
- 6
- FWCI
- 17.44
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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