The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Molecular Classification and Molecular Forecasting of Breast Cancer: Ready for Clinical Application?
Open accessAbstract
Profiling breast cancer with expression arrays has become common, and it has been suggested that the results from early studies will lead to understanding of the molecular differences between clinical cases and allow individualization of care. We critically review two main applications of expression profiling; studies unraveling novel breast cancer classifications and those that aim to identify novel markers for prediction of clinical outcome. Breast cancer may now be subclassified into luminal, basal, and HER2 subtypes with distinct differences in prognosis and response to therapy. However, profiling studies to identify predictive markers have suffered from methodologic problems that prevent general application of their results. Future work will need to reanalyze existing microarray data sets to identify more representative sets of candidate genes for use as prognostic signatures and will need to take into account the new knowledge of molecular subtypes of breast cancer when assessing predictive effects.
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Cites
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
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
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Ayers, M., Symmans, W. F., Stec, J., Damokosh, A. I., Clark, E., Hess, K., Lecocke, M., Metivier, J., Booser, D., Ibrahim, N., et al. (2004) · Journal of Clinical Oncology · doi:10.1200/jco.2004.05.166 · Cited by 566
Cited by
Haffty, B. G., Yang, Q., Reiss, M., Kearney, T., Higgins, S. A., Weidhaas, J., Harris, L., Hait, W., & Toppmeyer, D. (2006) · Journal of Clinical Oncology · doi:10.1200/jco.2006.06.5664 · Cited by 1,084
Predictive data mining in clinical medicine: Current issues and guidelines
BELLAZZI, R., & ZUPAN, B. (2008) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2006.11.006 · Cited by 823
Pathogenesis of Triple-Negative Breast Cancer
Derakhshan, F., & Reis-Filho, J. S. (2022) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathol-042420-093238 · Cited by 714
Molecular heterogeneity of breast carcinomas and the cancer stem cell hypothesis
Stingl, J., & Caldas, C. (2007) · Nature Reviews Cancer · doi:10.1038/nrc2212 · Cited by 470
Self-citationClassification and prognosis of invasive breast cancer: from morphology to molecular taxonomy
Schnitt, S. J. (2010) · Modern Pathology · doi:10.1038/modpathol.2010.33 · Cited by 419
Metadata
- Authors
- Brenton, J. D., Carey, L. A., Ahmed, A. A., & Caldas, C.
- Venue
- Journal of Clinical Oncology
- Published
- 2005-10-10
- Volume
- 23
- Issue
- 29
- Pages
- 7350-7360
- ISSN
- 0732-183X (ISSN-L)
- 1527-7755
- OpenAlex
- W2143336748
- Cited by
- 953
- References
- 4
- FWCI
- 14.93
- Type
- journal article
- Language
- en
- Open access
- green
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