The DOI matches its Crossref record; 205 of the 205 references it cites were found in a registry or an index.
Epithelial–mesenchymal-transition-inducing transcription factors: new targets for tackling chemoresistance in cancer?
Abstract
Chemoresistance remains a major complication of cancer treatments. Recent data provide strong evidence that chemoresistance is linked to epithelial-mesenchymal transition (EMT), a latent developmental process, which is re-activated during cancer progression. EMT involves transcriptional reprogramming and is driven by specific EMT transcription factors (EMT-TFs). In this review, we provide support for the idea that EMT-TFs contribute to the development of resistance against cancer therapy and discuss how EMT-TFs might be targeted to advance novel therapeutic approaches to the treatment of cancer.
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“EMT also correlates with increased resistance of carcinoma cells to chemotherapies149–152.”
From TGFβ biology in cancer progression and immunotherapy (2021) · cites this paper as [150]
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2 retracted
Items 201–205 of 205
Zhang, K., Zhang, B., Lu, Y., Sun, C., Zhao, W., Jiao, X., Hu, J., Mu, P., Lu, H., & Zhou, C. (2010) · Medical Oncology · doi:10.1007/s12032-010-9759-x · Cited by 21
Fang, S., Wu, L., Li, M., Yi, H., Gao, G., Sheng, Z., Gong, P., Ma, Y., & Cai, L. (2014) · Nanoscale · doi:10.1039/c4nr01518e · Cited by 21
Wang, T., Li, Y., Tuerhanjiang, A., et al. (2014) · Oncology Letters · doi:10.3892/ol.2014.1816 · Cited by 20
The regulation of snail: on the ubiquitin edge
Yu, Q., Zhou, B. P., & Wu, Y. (2017) · Cancer Cell & Microenvironment · doi:10.14800/ccm.1567 · Cited by 19
Johnson, M. A., Sive, R., Riddiough, C., et al. (2015) · Frontiers A Journal of Women Studies · doi:10.5250/fronjwomestud.36.2.0003 · Cited by 10
Research works printed but not linked: 1
- Ban YG, Yang JJ, Chang Y, Wang YL, Liu Y. USP7 promotes tumorigenesis in breast cancer and enhances MRI detection. Int J Clin Exp Med. 2016;9:10018–27.
Cited by
Sorted by citations
TGFβ biology in cancer progression and immunotherapy
Derynck, R., Turley, S. J., & Akhurst, R. J. (2021) · Nature Reviews Clinical Oncology · doi:10.1038/s41571-020-0403-1 · Cited by 944
Endocytosis in the context-dependent regulation of individual and collective cell properties
Sigismund, S., Lanzetti, L., Scita, G., & Di Fiore, P. P. (2021) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-021-00375-5 · Cited by 132
Metadata
- Authors
- van Staalduinen, J., Baker, D., ten Dijke, P., & van Dam, H.
- Affiliations
- Leiden University Medical Center (NL)
- ORCID
- Baker, David
- Venue
- Oncogene
- Published
- 2018-07-12
- Volume
- 37
- Issue
- 48
- Pages
- 6195-6211
- ISSN
- 0950-9232 (ISSN-L)
- 1476-5594
- OpenAlex
- W2870937227
- Cited by
- 158
- References
- 205
- Citations by year
- 2026: 6 · 2025: 9 · 2024: 13 · 2023: 18 · 2022: 30 · 2021: 27 · 2020: 32 · 2019: 22 · 2018: 1
- FWCI
- 2.15
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Oncogene (publishedVersion)
- PubMed (publishedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- Funders
- Cancer Genomics Centre
- Topics
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › TGF-β signaling in diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Mechanisms of cancer metastasis
- Keywords
- epithelial-mesenchymal transition, EMT transcription factors, chemoresistance, cancer therapy resistance, transcriptional reprogramming, targeted cancer therapy, tumor progression
- MeSH terms
- Animals, Humans, Neoplasms, Transcription Factors, Drug Resistance, Neoplasm, Epithelial-Mesenchymal Transition
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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.
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