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Angiogenesis inhibitors in cancer therapy: mechanistic perspective on classification and treatment rationales
Open accessAbstract
Angiogenesis, a process of new blood vessel formation, is a prerequisite for tumour growth to supply the proliferating tumour with oxygen and nutrients. The angiogenic process may contribute to tumour progression, invasion and metastasis, and is generally accepted as an indicator of tumour prognosis. Therefore, targeting tumour angiogenesis has become of high clinical relevance. The current review aimed to highlight mechanistic details of anti‐angiogenic therapies and how they relate to classification and treatment rationales. Angiogenesis inhibitors are classified into either direct inhibitors that target endothelial cells in the growing vasculature or indirect inhibitors that prevent the expression or block the activity of angiogenesis inducers. The latter class extends to include targeted therapy against oncogenes, conventional chemotherapeutic agents and drugs targeting other cells of the tumour micro‐environment. Angiogenesis inhibitors may be used as either monotherapy or in combination with other anticancer drugs. In this context, many preclinical and clinical studies revealed higher therapeutic effectiveness of the combined treatments compared with individual treatments. The proper understanding of synergistic treatment modalities of angiogenesis inhibitors as well as their wide range of cellular targets could provide effective tools for future therapies of many types of cancer.
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Metadata
- Authors
- El‐Kenawi, A. E., & El‐Remessy, A. B.
- Venue
- British Journal of Pharmacology
- Publisher
- Wiley
- Published
- 2013-10
- Volume
- 170
- Issue
- 4
- Pages
- 712-729
- ISSN
- 0007-1188 (ISSN-L)
- 1476-5381
- OpenAlex
- W1543678657
- Cited by
- 253
- References
- 226
- FWCI
- 4.71
- 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.
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.