Research Papers:

A prognostic 4-gene expression signature for patients with HER2-negative breast cancer receiving taxane and anthracycline-based chemotherapy

Pu Cheng, Zhen Wang, Guoming Hu, Qi Huang, Mengjiao Han and Jian Huang _

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Oncotarget. 2017; 8:103327-103339. https://doi.org/10.18632/oncotarget.21872

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Pu Cheng1,*, Zhen Wang1,*, Guoming Hu2,*, Qi Huang1, Mengjiao Han3 and Jian Huang1,4

1Department of Surgical Oncology, Second Affiliated Hospital and Cancer Institute (Key Laboratory of Cancer Prevention & Intervention, National Ministry of Education, Provincial Key Laboratory of Molecular Biology in Medical Sciences), Zhejiang University School of Medicine, Hangzhou, China

2Department of General Surgery (Breast and Thyroid Surgery), Shaoxing People’s Hospital, Shaoxing Hospital of Zhejiang University, Zhejiang, China

3Department of Medical Oncology, Key Laboratory of Biotherapy in Zhejiang, Sir Runrun Shaw hospital, Medical School of Zhejiang University, Hangzhou, China

4Gastroenterology Institute, Zhejiang University School of Medicine, Hangzhou, China

*These authors contributed equally to this work

Correspondence to:

Jian Huang, email: [email protected]

Keywords: breast cancer, signature, prognosis, relapse, chemotherapy

Received: September 01, 2017     Accepted: September 29, 2017     Published: October 17, 2017


Breast cancer is a heterogeneous group of diseases with diverse clinicopathological and molecular features. At present, chemo-resistance still poses a major obstacle to successful treatment of HER-2 negative breast cancer. Reliable biomarkers are urgently needed to accurately predict the therapeutic sensitivity and prognosis of such patients. In this study, we identified 3145 distant relapse–free survival (DRFS) associated genes in 310 patients with HER-2 negative breast cancer receiving taxane and anthracycline-based chemotherapy in the GSE25055 dataset using univariate survival analysis. Four genes (SRPK1, PCCA, PRLR and FBP1) were further selected by a robust likelihood-based survival model. A risk score model was then constructed with the regression coefficients of the four signature genes. Patients in the training set were successfully divided into high- and low-risk groups with significant differences in DRFS between the two groups. The predictive value was further validated in GSE25065 dataset and similar results were observed. Moreover, the 4-gene signature was proved to have superior prognostic power compared with several clinical signatures such as tumor size, lymph node invasion, TNM stage and PAM50 signature. Our findings indicated that the 4-gene signature was a robust prognostic marker with a good prospect of clinical application for HER-2 negative breast cancer patients receiving taxane-anthracycline combination therapy.

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