The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Insight into the heterogeneity of breast cancer through next-generation sequencing
Open accessAbstract
Rapid and sophisticated improvements in molecular analysis have allowed us to sequence whole human genomes as well as cancer genomes, and the findings suggest that we may be approaching the ability to individualize the diagnosis and treatment of cancer. This paradigmatic shift in approach will require clinicians and researchers to overcome several challenges including the huge spectrum of tumor types within a given cancer, as well as the cell-to-cell variations observed within tumors. This review discusses how next-generation sequencing of breast cancer genomes already reveals insight into tumor heterogeneity and how it can contribute to future breast cancer classification and management.
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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
Nowell, P. C. (1976) · Science · doi:10.1126/science.959840 · Cited by 6,471
Massive genomic rearrangement acquired in a single catastrophic event during cancer development
Stephens, P. J., Greenman, C. D., Fu, B., Yang, F., Bignell, G. R., Mudie, L. J., Pleasance, E. D., Lau, K. W., Beare, D., Stebbings, L. A., et al. (2011) · Cell · doi:10.1016/j.cell.2010.11.055 · Cited by 2,414
International network of cancer genome projects
The International Cancer Genome Consortium (2010) · Nature · doi:10.1038/nature08987 · Cited by 2,299
kConFab, Lim, E., Vaillant, F., Wu, D., Forrest, N. C., Pal, B., Hart, A. H., Asselin-Labat, M.-L., Gyorki, D. E., Ward, T., et al. (2009) · Nature Medicine · doi:10.1038/nm.2000 · Cited by 1,492
Cited by
Wang, T., Gilkes, D. M., Takano, N., Xiang, L., Luo, W., Bishop, C. J., Chaturvedi, P., Green, J. J., & Semenza, G. L. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1410041111 · Cited by 493
Samanta, D., Gilkes, D. M., Chaturvedi, P., Xiang, L., & Semenza, G. L. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1421438111 · Cited by 460
RetractedSuda, K., Nakaoka, H., Yoshihara, K., Ishiguro, T., Tamura, R., Mori, Y., Yamawaki, K., Adachi, S., Takahashi, T., Kase, H., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.07.037 · Cited by 414
Established breast cancer risk factors and risk of intrinsic tumor subtypes
Barnard, M. E., Boeke, C. E., & Tamimi, R. M. (2015) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/j.bbcan.2015.06.002 · Cited by 278
Omics Technologies Improving Breast Cancer Research and Diagnostics
Orsini, A., Diquigiovanni, C., & Bonora, E. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms241612690 · Cited by 52
Metadata
- Authors
- Russnes, H. G., Navin, N., Hicks, J., & Borresen-Dale, A.-L.
- Venue
- Journal of Clinical Investigation
- Published
- 2011-10-03
- Volume
- 121
- Issue
- 10
- Pages
- 3810-3818
- ISSN
- 0021-9738 (ISSN-L)
- OpenAlex
- W1964302896
- Cited by
- 240
- References
- 5
- FWCI
- 7.85
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Russnes, H. G., Navin, N., Hicks, J., & Borresen-Dale, A.-L. (2011). Insight into the heterogeneity of breast cancer through next-generation sequencing. Journal of Clinical Investigation. https://doi.org/10.1172/jci57088
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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.
