The DOI matches its Crossref record; 192 of the 192 references it cites were found in a registry or an index.
Metastatic heterogeneity of breast cancer: Molecular mechanism and potential therapeutic targets
Abstract
Breast cancer is one of the most common malignancies among women throughout the world and is the major cause of most cancer-related deaths. Several explanations account for the high rate of mortality of breast cancer, and metastasis to vital organs is identified as the principal cause. Over the past few years, intensive efforts have demonstrated that breast cancer exhibits metastatic heterogeneity with distinct metastatic precedence to various organs, giving rise to differences in prognoses and responses to therapy in breast cancer patients. Bone, lung, liver, and brain are generally accepted as the primary target sites of breast cancer metastasis. However, the underlying molecular mechanism of metastatic heterogeneity of breast cancer remains to be further elucidated. Recently, the advent of novel genomic and pathologic approaches as well as technological breakthroughs in imaging analysis and animal modelling have yielded an unprecedented change in our understanding of the heterogeneity of breast cancer metastasis and provided novel insight for establishing more effective therapeutics. This review summarizes recent molecular mechanisms and emerging concepts on the metastatic heterogeneity of breast cancer and discusses the potential of identifying specific molecules against tumor cells or tumor microenvironments to thwart the development of metastatic disease and improve the prognosis of breast cancer patients.
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Cites
Siegel, R. L., Miller, K. D., & Jemal, A. (2019) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21551 · Cited by 20,160
Comprehensive molecular portraits of human breast tumours
The Cancer Genome Atlas Network (2012) · Nature · doi:10.1038/nature11412 · Cited by 12,129
Epithelial-Mesenchymal Transitions in Development and Disease
Thiery, J. P., Acloque, H., Huang, R. Y. J., & Nieto, M. A. (2009) · Cell · doi:10.1016/j.cell.2009.11.007 · Cited by 9,931
The Epithelial-Mesenchymal Transition Generates Cells with Properties of Stem Cells
Mani, S. A., Guo, W., Liao, M.-J., Eaton, E. N., Ayyanan, A., Zhou, A. Y., Brooks, M., Reinhard, F., Zhang, C. C., Shipitsin, M., et al. (2008) · Cell · doi:10.1016/j.cell.2008.03.027 · Cited by 8,672
Cancer Immunoediting: Integrating Immunity’s Roles in Cancer Suppression and Promotion
Schreiber, R. D., Old, L. J., & Smyth, M. J. (2011) · Science · doi:10.1126/science.1203486 · Cited by 6,474
Allemani, C., Matsuda, T., Di Carlo, V., Harewood, R., Matz, M., Nikšić, M., Bonaventure, A., Valkov, M., Johnson, C. J., Estève, J., et al. (2018) · The Lancet · doi:10.1016/s0140-6736(17)33326-3 · Cited by 6,145
The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups
METABRIC Group, Curtis, C., Shah, S. P., Chin, S.-F., Turashvili, G., Rueda, O. M., Dunning, M. J., Speed, D., Lynch, A. G., Samarajiwa, S., et al. (2012) · Nature · doi:10.1038/nature10983 · Cited by 6,097
Involvement of chemokine receptors in breast cancer metastasis
Müller, A., Homey, B., Soto, H., Ge, N., Catron, D., Buchanan, M. E., McClanahan, T., Murphy, E., Yuan, W., Wagner, S. N., et al. (2001) · Nature · doi:10.1038/35065016 · Cited by 5,340
The distribution of secondary growths in cancer of the breast.
Paget, S. (1889) · The Lancet · doi:10.1016/s0140-6736(00)49915-0 · Cited by 5,277
Matrix Metalloproteinases: Regulators of the Tumor Microenvironment
Kessenbrock, K., Plaks, V., & Werb, Z. (2010) · Cell · doi:10.1016/j.cell.2010.03.015 · Cited by 5,151
Cited by
He, S., Fang, Y., Wu, M., Zhang, P., Gao, F., Hu, H., Sheng, C., & Dong, G. (2023) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.3c01539 · Cited by 42
Ming, H., Li, B., Tian, H., Zhou, L., Jiang, J., Zhang, T., Qiao, L., Wu, P., Nice, E. C., Zhang, W., et al. (2022) · Materials Today Bio · doi:10.1016/j.mtbio.2022.100289 · Cited by 33
Self-citationZeng, J., Wang, L., Cai, Q., Wu, J., & Zhou, C. (2022) · Gland Surgery · doi:10.21037/gs-22-114 · Cited by 22
Metadata
- Authors
- Liang, Y., Zhang, H., Song, X., & Yang, Q.
- Venue
- Seminars in Cancer Biology
- Publisher
- Elsevier BV
- Published
- 2020-02
- Volume
- 60
- Pages
- 14-27
- ISSN
- 1044-579X (ISSN-L)
- OpenAlex
- W2967901922
- Cited by
- 992
- References
- 192
- FWCI
- 25.75
- Type
- journal article
- Language
- en
- Open access
- closed
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- Liang, Y., Zhang, H., Song, X., & Yang, Q. (2020). Metastatic heterogeneity of breast cancer: Molecular mechanism and potential therapeutic targets. Seminars in Cancer Biology. https://doi.org/10.1016/j.semcancer.2019.08.012
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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.