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Therapeutic Implications of Cellular Heterogeneity and Plasticity in Breast Cancer
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Summary Cellular heterogeneity represents one of the greatest challenges in cancer therapeutics. In many malignancies, this heterogeneity is generated during tumor evolution through a combination of genetic alterations and epigenetic events that recapitulate normal developmental processes including stem cell self-renewal and differentiation. Many, if not most, tumors display similar hierarchal organization, at the apex of which are “stem-like cells” that drive tumor growth, mediate metastasis and contribute to treatment resistance. Using breast cancer as a model, we discuss how an improved understanding of tumor cellular heterogeneity and plasticity may lead to development of more effective therapeutic strategies.
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Metadata
- Authors
- Brooks, M. D., Burness, M. L., & Wicha, M. S.
- Venue
- Cell Stem Cell
- Publisher
- Elsevier BV
- Published
- 2015-09
- Volume
- 17
- Issue
- 3
- Pages
- 260-271
- ISSN
- 1875-9777 (ISSN-L)
- 1934-5909
- OpenAlex
- W1833050134
- Cited by
- 374
- References
- 126
- FWCI
- 15.60
- Type
- journal article
- Language
- en
- Open access
- bronze
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.
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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.