The DOI matches its Crossref record; 289 of the 289 references it cites were found in a registry or an index.
Signaling Pathways in Cancer: Therapeutic Targets, Combinatorial Treatments, and New Developments
Open accessAbstract
Molecular alterations in cancer genes and associated signaling pathways are used to inform new treatments for precision medicine in cancer. Small molecule inhibitors and monoclonal antibodies directed at relevant cancer-related proteins have been instrumental in delivering successful treatments of some blood malignancies (e.g., imatinib with chronic myelogenous leukemia (CML)) and solid tumors (e.g., tamoxifen with ER positive breast cancer and trastuzumab for HER2-positive breast cancer). However, inherent limitations such as drug toxicity, as well as acquisition of de novo or acquired mechanisms of resistance, still cause treatment failure. Here we provide an up-to-date review of the successes and limitations of current targeted therapies for cancer treatment and highlight how recent technological advances have provided a new level of understanding of the molecular complexity underpinning resistance to cancer therapies. We also raise three basic questions concerning cancer drug discovery based on molecular markers and alterations of selected signaling pathways, and further discuss how combination therapies may become the preferable approach over monotherapy for cancer treatments. Finally, we consider novel therapeutic developments that may complement drug delivery and significantly improve clinical response and outcomes of cancer patients.
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Cites
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Cited by
The Curious Case of the HepG2 Cell Line: 40 Years of Expertise
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Metadata
- Authors
- Yip, H. Y. K., & Papa, A.
- Venue
- Cells
- Publisher
- MDPI AG
- Published
- 2021-03-16
- Volume
- 10
- Issue
- 3
- Pages
- 659
- ISSN
- 2073-4409 (ISSN-L)
- OpenAlex
- W3139023757
- Cited by
- 316
- References
- 289
- FWCI
- 25.51
- Type
- journal article
- Language
- en
- Open access
- gold
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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.