Abstract
21009 Background: We sought to validate a previously developed 14-gene prognostic signature and a metastasis score (MS) that predicted distant metastasis in N-, ER+ breast cancer patients in an independent sample set of patients without systemic treatment. The genes consisted primarily of proliferation genes involved in p53 and TNF signaling pathways. Methods: : A cohort of 294 N-, ER+ breast cancer patients from Guy's Hospitals, London, UK without systemic therapy were tested. The cohort had a mean age of 55.5 yrs with 49% > 55 yrs, mean tumor size of 1.93 (max. 3) cm, and a median follow up of 14.3 yrs. The primary endpoint was distant metastasis free survival. RT-PCR was carried out on fixed sections. The MS was calculated. Results: The mean MS (SD) was 0.44 (0.59) with a range of -1.31 to 2.0. Hazard of distant metastasis increased 3.02 fold (95% CI 1.91–4.76, p <0.0001) per unit increase in MS from Cox model. The pre-determined cut point of zero was used to stratify patients into low- and high-risk groups. The 5-yr distant-metastasis-free survival rate (DMFSR) for low- and high-risk groups were 1 and 0.86 (SE 0.024); the 10-yr DMFSR were 0.97 (0.021) and 0.77 (0.030), respectively. Univariate Cox regression analyses indicated that MS (hazard ratio (HR) 5.65, 95% CI 2.05–15.56, p=0.008), tumor size (HR 1.62, p=0.0047) and tumor grade (HR 2.52, p=0.036) were significant but age was not. Multivariate Cox regression indicated that the signature had independent prognostic value with a HR of 4.71 (1.42–15.61, p=0.011) after adjusting for age, tumor size and grade. AUC of MS at 5-and 10-yr were 0.78 (0.71–0.85, p<0.001) and 0.73 (0.66–0.80, p<0.001) with sensitivities of 1 and 0.96 and specificities of 0.31 and 0.31 at zero cut point, respectively. The differential risk between the median MS scores of the lowest and highest deciles was 8-fold. Conclusions: A previously defined RT-PCR prognostic signature for N-, ER+ patients has been confirmed. A metastasis score that quantifies distant metastasis risk, not confounded with treatment effect can complement treatment response predictors. Insight on natural history of tumors is critical for evaluating impact of therapy. No significant financial relationships to disclose.
Published Version
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