The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Host microenvironment in breast cancer development: Epithelial–mesenchymal transition in breast cancer development
Open accessAbstract
The epithelial-mesenchymal transition (EMT) is a developmental mechanism of crucial importance in establishing the body plan in many multicellular organisms. Several transduction pathways controlling the various steps of the morphological transition have been identified by molecular analyses of this process in cell lines and in vivo. The newly formed mesenchymal cells can exhibit locomotory and invasive phenotypes, suggesting that EMTs contribute to the progression of carcinoma. Diverse evidence indicates that EMT subprograms are involved in the appearance of different breast carcinoma types. Several normal and malignant breast cell lines are currently being analyzed to define key steps in EMT and to identify candidate genes. DNA profiling technology is also being applied to uncover pathways that lead to a metastatic phenotype.
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Cites
Gene expression profiling predicts clinical outcome of breast cancer
van 't Veer, L. J., Dai, H., van de Vijver, M. J., He, Y. D., Hart, A. A. M., Mao, M., Peterse, H. L., van der Kooy, K., Marton, M. J., Witteveen, A. T., et al. (2002) · Nature · doi:10.1038/415530a · Cited by 9,536
New functions for the matrix metalloproteinases in cancer progression
Egeblad, M., & Werb, Z. (2002) · Nature Reviews Cancer · doi:10.1038/nrc745 · Cited by 6,108
The snail superfamily of zinc-finger transcription factors
Nieto, M. A. (2002) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm757 · Cited by 1,719
Building epithelial architecture: insights from three-dimensional culture models
O'Brien, L. E., Zegers, M. M. P., & Mostov, K. E. (2002) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm859 · Cited by 596
Cited by
Chen, J., Imanaka, N., Chen, J., & Griffin, J. D. (2010) · British Journal of Cancer · doi:10.1038/sj.bjc.6605486 · Cited by 346
SALMON: survival analysis learning with multi-omics neural networks on breast cancer
Huang, Z., Zhan, X., Xiang, S., Johnson, T. S., Helm, B., Yu, C. Y., Zhang, J., Salama, P., Rizkalla, M., Han, Z., et al. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.00166 · Cited by 262
Turley, E. A., Veiseh, M., Radisky, D. C., & Bissell, M. J. (2008) · Nature Clinical Practice Oncology · doi:10.1038/ncponc1089 · Cited by 253
YI, B.-R., CHOI, K. J., KIM, S. U., & CHOI, K.-C. (2012) · International Journal of Oncology · doi:10.3892/ijo.2012.1523 · Cited by 32
Metadata
- Authors
- Vincent-Salomon, A., & Thiery, J. P.
- Venue
- Breast Cancer Research
- Published
- 2003-04
- Volume
- 5
- Issue
- 2
- Pages
- 101-6
- ISSN
- 1465-5411 (ISSN-L)
- 1465-542X
- OpenAlex
- W1843154721
- Cited by
- 223
- References
- 4
- FWCI
- 4.15
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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