Impact of tumor heterogeneity on disease-free survival in a series of 368 patients treated for a breast cancer

Abstract

SUMMARY:BACKGROUND:Tumor heterogeneity is an old concept but its impact on cancerogenesis process is poorly understood. Breast cancer is a noteworthy model for its frequency, the diversity of its phenotypes and of its evolution. This study investigates the influence of the heterogeneity of tumor proliferation on disease-free survival of patients with a breast carcinoma. The study involved a series of 368 patients from the Francois Baclesse Cancer Centre (Caen) with a follow-up of more than 15 years.FINDINGS:An immunostaining of mitotic figures was performed on histological section, representative of the tumor, with the anti-phosphohistone-H3 antibody (PHH3). The slides were scanned, then sub-sampled and analyzed by an automatic image processing program developed by the lab. This program detects "Hot Spot" areas and measures 9 features of heterogeneity. A principal component analysis was used to extract the most relevant features for heterogeneity (4 were selected) and combine them (CP2). They were analyzed statistically. In the univariate analysis (DFS), only the Voronoi feature and the combination CP2 have a prognostic value. The multivariate analysis (Cox), combining with classical clinicopathological factors and heterogeneity features, showed three independent prognostic factors: Tumor heterogeneity (CP2), Mitotic index and Lymph node metastasis.CONCLUSIONS:The construction of this model has individualized three groups of patients: "0", "1 or 2" and "3 poor prognostic factors". The tumor heterogeneity measured by image analysis is one of the three major prognostic factors identified in our series. This result encourages confronting the heterogeneity feature CP2 to clinic information, such as recent or late oncologic event.