Genome Instability Profiles Predict Disease Outcome in a Cohort of 4,003 Patients with Breast Cancer.

Clinical Cancer Research : an Official Journal of the American Association for Cancer Research
Annette LischkaJens K Habermann

Abstract

The choice of therapy for patients with breast cancer is often based on clinicopathologic parameters, hormone receptor status, and HER2 amplification. To improve individual prognostication and tailored treatment decisions, we combined clinicopathologic prognostic data with genome instabilty profiles established by quantitative measurements of the DNA content. We retrospectively assessed clinical data of 4,003 patients with breast cancer with a minimum postoperative follow-up period of 10 years. For the entire cohort, we established genome instability profiles. We applied statistical methods, including correlation matrices, Kaplan-Meier curves, and multivariable Cox proportional hazard models, to ascertain the potential of standard clinicopathologic data and genome instability profiles as independent predictors of disease-specific survival in distinct subgroups, defined clinically or with respect to treatment. In Cox regression analyses, two parameters of the genome instability profiles, the S-phase fraction and the stemline scatter index, emerged as independent predictors in premenopausal women, outperforming all clinicopathologic parameters. In postmenopausal women, age and hormone receptor status were the predominant prognost...Continue Reading

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