The DOI matches its Crossref record; 134 of the 134 references it cites were found in a registry or an index.
Potential of long non‐coding RNAs in cancer patients: From biomarkers to therapeutic targets
Open accessAbstract
Because of high specificity and easy detection in the tissues, serum, plasma, urine and saliva, interest in exploring the potential of long non‐coding RNAs (lncRNAs) in cancer patients continues to increase. LncRNAs have shown potential as a biomarker in the diagnosis and prognosis of bladder cancer, prostate cancer, gastric cancer, pancreatic cancer, breast cancer and many other cancer types. Some lncRNAs have also been used as adjunct to improve the specificity and sensitivity of existing biomarkers. The molecular tools such as RNA‐seq, RNA‐FISH, ic‐SHAPE and quantitative real‐time PCR have been used for examining the lncRNAs' potential. Some lncRNAs such as PCA3 is now routinely used in the clinic for the diagnosis of prostate cancer. Single nucleotide polymorphisms (SNPs) in lncRNAs can also be used as a predictor of cancer risk. Although ongoing studies continue to unravel the underlying mechanism, some lncRNAs have been used as therapeutic targets for the selective killing of cancer cells in patients. Thus lncRNAs are emerging as convenient and minimally invasive diagnostic/prognostic markers, and also as therapeutic target. Companies such as the Curna Inc., MiNA Therapeutics Ltd. and RaNA Therapeutics Inc. have been taking steps to develop lncRNA based strategies against cancer. In this review, we discuss the potential of lncRNAs as biomarkers and therapeutic targets in cancer patients.
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Jemal, A., Bray, F., Center, M. M., Ferlay, J., Ward, E., & Forman, D. (2011) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.20107 · Cited by 54,679
Long non-coding RNAs: insights into functions
Mercer, T. R., Dinger, M. E., & Mattick, J. S. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2521 · Cited by 5,654
Genome-scale CRISPR-Cas9 knockout screening in human cells
Shalem, O., Sanjana, N. E., Hartenian, E., Shi, X., Scott, D. A., Mikkelsen, T. S., Heckl, D., Ebert, B. L., Root, D. E., Doench, J. G., et al. (2014) · Science · doi:10.1126/science.1247005 · Cited by 5,234
Long non-coding RNA HOTAIR reprograms chromatin state to promote cancer metastasis
Gupta, R. A., Shah, N., Wang, K. C., Kim, J., Horlings, H. M., Wong, D. J., Tsai, M.-C., Hung, T., Argani, P., Rinn, J. L., et al. (2010) · Nature · doi:10.1038/nature08975 · Cited by 5,218
Molecular Mechanisms of Long Noncoding RNAs
Wang, K. C., & Chang, H. Y. (2011) · Molecular Cell · doi:10.1016/j.molcel.2011.08.018 · Cited by 4,396
Hindorff, L. A., Sethupathy, P., Junkins, H. A., Ramos, E. M., Mehta, J. P., Collins, F. S., & Manolio, T. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0903103106 · Cited by 4,013
Wang, H., Yang, H., Shivalila, C. S., Dawlaty, M. M., Cheng, A. W., Zhang, F., & Jaenisch, R. (2013) · Cell · doi:10.1016/j.cell.2013.04.025 · Cited by 3,495
Long Noncoding RNA as Modular Scaffold of Histone Modification Complexes
Tsai, M.-C., Manor, O., Wan, Y., Mosammaparast, N., Wang, J. K., Lan, F., Shi, Y., Segal, E., & Chang, H. Y. (2010) · Science · doi:10.1126/science.1192002 · Cited by 3,290
Khalil, A. M., Guttman, M., Huarte, M., Garber, M., Raj, A., Rivea Morales, D., Thomas, K., Presser, A., Bernstein, B. E., van Oudenaarden, A., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0904715106 · Cited by 2,872
Genetic screens in human cells using the CRISPR-Cas9 system
Wang, T., Wei, J. J., Sabatini, D. M., & Lander, E. S. (2014) · Science · doi:10.1126/science.1246981 · Cited by 2,856
Cited by
Carrasco-Leon, A., Ezponda, T., Meydan, C., Valcárcel, L. V., Ordoñez, R., Kulis, M., Garate, L., Miranda, E., Segura, V., Guruceaga, E., et al. (2021) · Leukemia · doi:10.1038/s41375-021-01147-y · Cited by 50
Potential Therapeutic Targeting of lncRNAs in Cholesterol Homeostasis
Ye, W.-C., Huang, S.-F., Hou, L.-J., Long, H.-J., Yin, K., Hu, C. Y., & Zhao, G.-J. (2021) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2021.688546 · Cited by 19
Metadata
- Authors
- Chandra Gupta, S., & Nandan Tripathi, Y.
- Venue
- International Journal of Cancer
- Publisher
- Wiley
- Published
- 2016-12-30
- Volume
- 140
- Issue
- 9
- Pages
- 1955-1967
- ISSN
- 0020-7136 (ISSN-L)
- 1097-0215
- OpenAlex
- W2783395490
- Cited by
- 527
- References
- 134
- FWCI
- 17.10
- Type
- journal article
- Language
- en
- Open access
- bronze
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