A six-long non-coding RNAs signature as a potential prognostic marker for survival prediction of ER-positive breast cancer patients

Lei Zhong, Ge Lou, Xinglu Zhou, Youyou Qin, Lin Liu, Wenqian Jiang

Oncotarget · 2017 · 26 citations · 39 references

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Abstract

// Lei Zhong 1, * , Ge Lou 2, * , Xinglu Zhou 3 , Youyou Qin 1 , Lin Liu 1 and Wenqian Jiang 1 1 Department of Breast Surgery, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China 2 Department of Pathology, Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China 3 Department of PET/CT, Harbin Medical University Cancer Hospital, Harbin 150040, China * These authors have contributed equally to this work Correspondence to: Lei Zhong, email: leizhonghrbmu@126.com Keywords: breast cancer, estrogen receptor, long non-coding RNAs, prognosis Received: May 18, 2017      Accepted: June 15, 2017      Published: July 01, 2017 ABSTRACT Dysregulated expression of lncRNAs has been observed in various human complex diseases (including cancers) by recent transcriptional profiling studies, highlighting potentials of lncRNAs as biomarkers for cancer diagnosis and prognosis. Despite some efforts have been made to search for novel lncRNA signature in breast cancer, the prognostic value of lncRNAs for ER-positive breast cancer patients still needs to be systematically investigated. In this study, we analyzed lncRNA expression profiles in a large of more than 600 breast cancer patients with ER-positive status from The Cancer Genome Atlas (TCGA) and identified six lncRNAs that are significantly associated with survival. Then a linear risk score model comprising six prognostic lncRNAs, termed six-lncRNA signature, was developed to identify high-risk patients from low-risk cases. The results of Kaplan-Meier analysis and ROC curves demonstrated the good sensitivity and specificity in survival prediction both in the training and testing datasets. Multivariate Cox regression analysis and stratified analysis showed that the six-lncRNA signature is an independent prognostic marker in survival prediction for ER-positive breast cancer patients. The GO enrichment analysis suggested that the six-lncRNA might involve with known breast cancer-related biological processes. With further experimental validation, these identified prognostic lncRNAs might have clinical implications for more personalized risk assessment for ER-positive breast cancer patients.

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