The DOI matches its Crossref record; 351 of the 351 references it cites were found in a registry or an index.
CRISPR/Cas9 therapeutics: progress and prospects
Open accessAbstract
Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) gene-editing technology is the ideal tool of the future for treating diseases by permanently correcting deleterious base mutations or disrupting disease-causing genes with great precision and efficiency. A variety of efficient Cas9 variants and derivatives have been developed to cope with the complex genomic changes that occur during diseases. However, strategies to effectively deliver the CRISPR system to diseased cells in vivo are currently lacking, and nonviral vectors with target recognition functions may be the focus of future research. Pathological and physiological changes resulting from disease onset are expected to serve as identifying factors for targeted delivery or targets for gene editing. Diseases are both varied and complex, and the choice of appropriate gene-editing methods and delivery vectors for different diseases is important. Meanwhile, there are still many potential challenges identified when targeting delivery of CRISPR/Cas9 technology for disease treatment. This paper reviews the current developments in three aspects, namely, gene-editing type, delivery vector, and disease characteristics. Additionally, this paper summarizes successful examples of clinical trials and finally describes possible problems associated with current CRISPR applications.
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Cites
PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer
Hartkopf, A. D., Taran, F.-A., Wallwiener, M., Walter, C. B., Krämer, B., Grischke, E.-M., & Brucker, S. Y. (2016) · Breast Care · doi:10.1159/000453569 · Cited by 30,845
A Programmable Dual-RNA–Guided DNA Endonuclease in Adaptive Bacterial Immunity
Jinek, M., Chylinski, K., Fonfara, I., Hauer, M., Doudna, J. A., & Charpentier, E. (2012) · Science · doi:10.1126/science.1225829 · Cited by 17,116
Multiplex Genome Engineering Using CRISPR/Cas Systems
Cong, L., Ran, F. A., Cox, D., Lin, S., Barretto, R., Habib, N., Hsu, P. D., Wu, X., Jiang, W., Marraffini, L. A., et al. (2013) · Science · doi:10.1126/science.1231143 · Cited by 15,339
Adverse Renal Effects of Immune Checkpoint Inhibitors: A Narrative Review
Wanchoo, R., Karam, S., Uppal, N. N., Barta, V. S., Deray, G., Devoe, C., Launay-Vacher, V., Jhaveri, K. D., & on behalf of Cancer and Kidney International Network Workgroup on Immune Checkpoint Inhibitors (2017) · American Journal of Nephrology · doi:10.1159/000455014 · Cited by 15,256
Genome engineering using the CRISPR-Cas9 system
Ran, F. A., Hsu, P. D., Wright, J., Agarwala, V., Scott, D. A., & Zhang, F. (2013) · Nature Protocols · doi:10.1038/nprot.2013.143 · Cited by 11,133
RNA-Guided Human Genome Engineering via Cas9
Mali, P., Yang, L., Esvelt, K. M., Aach, J., Guell, M., DiCarlo, J. E., Norville, J. E., & Church, G. M. (2013) · Science · doi:10.1126/science.1232033 · Cited by 9,210
Shrestha, S., & Offer, S. M. (2016) · Medical Epigenetics · doi:10.1159/000444713 · Cited by 8,914
Engineering precision nanoparticles for drug delivery
Mitchell, M. J., Billingsley, M. M., Haley, R. M., Wechsler, M. E., Peppas, N. A., & Langer, R. (2021) · Nature Reviews Drug Discovery · doi:10.1038/s41573-020-0090-8 · Cited by 7,933
The new frontier of genome engineering with CRISPR-Cas9
Doudna, J. A., & Charpentier, E. (2014) · Science · doi:10.1126/science.1258096 · Cited by 7,062
CRISPR Provides Acquired Resistance Against Viruses in Prokaryotes
Barrangou, R., Fremaux, C., Deveau, H., Richards, M., Boyaval, P., Moineau, S., Romero, D. A., & Horvath, P. (2007) · Science · doi:10.1126/science.1138140 · Cited by 5,947
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Neutrophils: Linking Inflammation to Thrombosis and Unlocking New Treatment Horizons
Li, H., Shan, W., Zhao, X., & Sun, W. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26051965 · Cited by 32
Metadata
- Authors
- Li, T., Yang, Y., Qi, H., Cui, W., Zhang, L., Fu, X., He, X., Liu, M., Li, P.-F., & Yu, T.
- Venue
- Signal Transduction and Targeted Therapy
- Published
- 2023-01-16
- Volume
- 8
- Issue
- 1
- Pages
- 36-36
- ISSN
- 2059-3635 (ISSN-L)
- OpenAlex
- W4316466738
- Cited by
- 719
- References
- 351
- FWCI
- 53.80
- Type
- journal article
- Language
- en
- Open access
- gold
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- Li, T., Yang, Y., Qi, H., Cui, W., Zhang, L., Fu, X., He, X., Liu, M., Li, P.-F., & Yu, T. (2023). CRISPR/Cas9 therapeutics: progress and prospects. Signal Transduction and Targeted Therapy. https://doi.org/10.1038/s41392-023-01309-7
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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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