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RB-pathway disruption in breast cancer: Differential association with disease subtypes, disease-specific prognosis and therapeutic response
Open accessAbstract
In breast cancer, inactivation of the RB tumor suppressor gene is believed to occur via multiple mechanisms to facilitate tumorigenesis. However, the prognostic and predictive value of RB status in disease-specific clinical outcomes has remained uncertain. We investigated RB pathway deregulation in the context of both ER-positive and ER-negative disease using combined microarray datasets encompassing over 900 breast cancer patient samples. Disease-specific characteristics of RB pathway deregulation were investigated in this dataset by evaluating correlation among pathway genes as well as differential expression across patient tumor populations defined by ER status. Survival analysis among these breast cancer samples demonstrates that the RB-loss signature is associated with poor disease outcome within several independent cohorts. Within the ER-negative subpopulation, the RB-loss signature is associated with improved response to chemotherapy and longer relapse-free survival. Additionally, while individual genes in the RB target signature closely reproduce its prognostic value, they also serve to predict and monitor response to therapeutic compounds, such as the cytostatic agent PD-0332991. These results indicate that the RB-loss signature expression is associated with poor outcome in breast cancer, but predicts improved response to chemotherapy based on data in ER-negative populations. While the RB-loss signature, as a whole, demonstrates prognostic and predictive utility, a small subset of markers could be sufficient to stratify patients based on RB function and inform the selection of appropriate therapeutic regimens.
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Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
Edgar, R. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.207 · Cited by 13,288
DAVID: Database for Annotation, Visualization, and Integrated Discovery
Dennis, G., Sherman, B. T., Hosack, D. A., Yang, J., Gao, W., Lane, H. C., & Lempicki, R. A. (2003) · Genome Biology · doi:10.1186/gb-2003-4-5-p3 · Cited by 9,327
E2F integrates cell cycle progression with DNA repair, replication, and G 2 /M checkpoints
Ren, B., Cam, H., Takahashi, Y., Volkert, T., Terragni, J., Young, R. A., & Dynlacht, B. D. (2002) · Genes & Development · doi:10.1101/gad.949802 · Cited by 1,125
Cellular mechanisms of tumour suppression by the retinoblastoma gene
Burkhart, D. L., & Sage, J. (2008) · Nature Reviews Cancer · doi:10.1038/nrc2399 · Cited by 974
Common markers of proliferation
Whitfield, M. L., George, L. K., Grant, G. D., & Perou, C. M. (2006) · Nature Reviews Cancer · doi:10.1038/nrc1802 · Cited by 650
Pocket proteins and cell cycle control
Cobrinik, D. (2005) · Oncogene · doi:10.1038/sj.onc.1208619 · Cited by 601
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Metadata
- Authors
- Ertel, A., Dean, J. L., Rui, H., Liu, C., Witkiewicz, A., Knudsen, K. E., & Knudsen, E. S.
- Venue
- Cell Cycle
- Publisher
- Informa UK Limited
- Published
- 2010-10-15
- Volume
- 9
- Issue
- 20
- Pages
- 4153-4163
- ISSN
- 1538-4101 (ISSN-L)
- 1551-4005
- OpenAlex
- W2055164947
- Cited by
- 173
- References
- 6
- FWCI
- 4.34
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Ertel, A., Dean, J. L., Rui, H., Liu, C., Witkiewicz, A., Knudsen, K. E., & Knudsen, E. S. (2010). RB-pathway disruption in breast cancer: Differential association with disease subtypes, disease-specific prognosis and therapeutic response. Cell Cycle. https://doi.org/10.4161/cc.9.20.13454
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