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

ABSTRACT:

Purpose

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.

Experimental design

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 clinicopa

SUBMITTER: Lischka A 

PROVIDER: S-EPMC7483822 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature