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Imaging, Diagnosis, Prognosis |
Authors' Affiliations: 1 Cancer Genomics Program, Department of Oncology, Hutchison-Medical Research Council Research Centre, University of Cambridge; 2 Cancer Research UK, Department of Oncology, Strangeways Research Laboratory; 3 Department of Histopathology, Addenbrooke's Hospital, Cambridge, United Kingdom; 4 Department of Pathology, National University of Ireland, Galway, Ireland; 5 Genetic Pathology Evaluation Centre of the Department of Pathology and Prostate Research Centre, Vancouver General Hospital, British Columbia Cancer Agency and University of British Columbia, Vancouver, British Columbia, Canada; 6 Department of Histopathology, Nottingham City Hospital, Nottingham, United Kingdom; and 7 Oncology Health Center, McGill University Health Center, Montreal, Quebec, Canada
Requests for reprints: Carlos Caldas, Department of Oncology, Hutchison-Medical Research Council Research Centre, Level 3, University of Cambridge, Addenbrooke's Hospital, University of Cambridge, Cambridge CB2 2XZ, United Kingdom. Phone: 44-1223-331989; Fax: 44-1223-331753; E-mail: cc234{at}cam.ac.uk.
Purpose: Prognostication of breast cancer using clinicopathologic variables, although useful, remains imperfect. Many reports suggest that gene expression profiling can refine the current approach. Alternatively, it has been shown that panels of proteins assessed by immunohistochemistry might also be useful in this regard. We evaluate the prognostic potential of a panel of markers by immunohistochemistry in a large case series to establish if either a single marker or a panel could improve the prognostic power of the Nottingham Prognostic Index (NPI). We validated the results in an independent series.
Experimental Design and Results: The expression of 13 biomarkers was evaluated in 930 breast cancers on a tissue microarray. Eight markers [estrogen receptor (ER), progesterone receptor (PR), Bcl-2, cyclin E, p53, MIB-1, cytokeratin 5/6, and HER2] showed a significant association with survival at 10 years on univariate analysis. On multivariate analysis that included these eight markers and the NPI, only the NPI [hazard ratio (HR), 1.35; 95% confidence interval (95% CI), 1.16-1.56; P = 0.0005], ER (HR, 0.59; 95% CI, 0.39-0.88; P = 0.011), and Bcl-2 (HR, 0.68; 95% CI, 0.46-0.99; P = 0.055) were significant. In a subsequent multivariate analysis that included the NPI, ER, and Bcl-2, only Bcl-2 (HR, 0.62; 95% CI, 0.44-0.87; P = 0.006) remained independent of NPI (HR, 1.50; 95% CI, 1.16-1.56; P = 0.004). In addition, Bcl-2, used as a single marker, was more powerful than the use of a panel of markers. Based on these results, an independent series was used to validate the prognostic significance of Bcl-2. ER and PR were also evaluated in this validation series. Bcl-2 (HR, 0.83; 95% CI, 0.71-0.96; P = 0.018) retained prognostic significance independent of the NPI (HR, 2.04; 95% CI, 1.67-2.51; P < 0.001) with an effect that was maximal in the first 5 years.
Conclusion: Bcl-2 is an independent predictor of breast cancer outcome and seems to be useful as a prognostic adjunct to the NPI, particularly in the first 5 years after diagnosis.
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