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Understanding and targeting cancer stem cells: therapeutic implications and challenges
Open accessAbstract
Cancer stem cells (CSCs) have been identified as rare cell populations in many cancers, including leukemia and solid tumors. Accumulating evidence has suggested that CSCs are capable of self-renewal and differentiation into various types of cancer cells. Aberrant regulation of gene expression and some signaling pathways has been observed in CSCs compared to other tumor cells. CSCs are thought to be responsible for cancer initiation, progression, metastasis, recurrence and drug resistance. The CSC hypothesis has recently attracted much attention due to the potential for discovery and development of CSC-related therapies and the identification of key molecules involved in controlling the unique properties of CSC populations. Over the past several years, a tremendous amount of effort has been invested in the development of new drugs, such as nanomedicines, that can take advantage of the "Achilles' heel" of CSCs by targeting cell-surface molecular markers or various signaling pathways. Novel compounds and therapeutic strategies that selectively target CSCs have been identified, some of which have been evaluated in preclinical and clinical studies. In this article, we review new findings related to the investigation of the CSC hypothesis, and discuss the crucial pathways involved in regulating the development of CSC populations and the advances in studies of drug resistance. In addition, we review new CSC-targeted therapeutic strategies aiming to eradicate malignancies.
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Metadata
- Authors
- Chen, K., Huang, Y.-H., & Chen, J.-L.
- Venue
- Acta Pharmacologica Sinica
- Published
- 2013-05-20
- Volume
- 34
- Issue
- 6
- Pages
- 732-740
- ISSN
- 0253-9756 (ISSN-L)
- 1671-4083
- 1745-7254
- OpenAlex
- W2002013266
- Cited by
- 608
- References
- 100
- FWCI
- 29.25
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
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.