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A 41-gene signature derived from breast cancer stem cells as a predictor of survival
Authors:Zhi-Qiang Yin  Jian-Jun Liu  Ying-Chun Xu  Jian Yu  Guo-Hui Ding  Feng Yang  Lei Tang  Bao-Hong Liu  Yue Ma  Yu-Wei Xia  Xiao-Lin Lin  Hong-Xia Wang
Institution:1.Shanghai Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200127, China;2.Shanghai Center for Bioinformation Technology, Shanghai 201203, China;3.Department of Oncology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China
Abstract:

Purpose

The aim of this study was to evaluate the ability of a 41-gene signature derived from breast cancer stem cells (BCSCs) to estimate the risk of metastasis and survival in breast cancer patients.

Methods

The centroid expression of the 41-gene signature derived from BCSCs was applied as the threshold to classify patients into two separate groups—patients with high expression (high-EL) of the prognostic signature and patients with low expression (low-EL). The predictive ability of the 41-gene signature was evaluated by Cox regression model and was compared against other popular tests, such as Oncotype and MammaPrint.

Results

Our results showed that the 41-gene prognostic signature was significantly associated with age (P = .0351) and ER status (P = .0095). The analysis indicated that patients in the high-EL group had a worse prognosis than those in the low-EL group in terms of both overall survival (OS: HR, 2.05, P = .009) and distant metastasis-free survival (DMFS: HR, 2.24, P = .002). Additionally, the 41-gene signature was an independent risk factor and separates patients based on estrogen receptor status. While comparable to Oncotype, the analysis demonstrated that the 41-gene signature had a better prognostic value in predicting DMFS and OS than AOL, NPI, St. Gallen, Veridex, and MammaPrint.

Conclusions

This study confirms the utility of the 41-gene signature and adds to the growing evidence that gene expression signatures of BCSCs have clinical potential to predict patient outcome and aid in treatment choice.
Keywords:Prognostic signature  Breast cancer  Stem cell
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