A multiple breast cancer stem cell model to predict recurrence of T_1-3, N₀ breast cancer.

ABSTRACT:

Background

Local or distant relapse is the key event for the overall survival of early-stage breast cancer after initial surgery. A small subset of breast cancer cells, which share similar properties with normal stem cells, has been proven to resist to clinical therapy contributing to recurrence.

Methods

In this study, we aimed to develop a prognostic model to predict recurrence based on the prevalence of breast cancer stem cells (BCSCs) in breast cancer. Immunohistochemistry and dual-immunohistochemistry were performed to quantify the stem cells of the breast cancer patients. The performance of Cox proportional hazard regression model was assessed using the holdout methods, where the dataset was randomly split into two exclusive sets (70% training and 30% testing sets). Add

SUBMITTER: Qiu Y 

PROVIDER: S-EPMC6657050 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature