Oncotarget

Research Papers:

Identification of long non-coding RNAs biomarkers associated with progression of endometrial carcinoma and patient outcomes

Yanan Sun _, Xiaoyan Zou, Jun He and Yuqin Mao

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Oncotarget. 2017; 8:52604-52613. https://doi.org/10.18632/oncotarget.17537

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Abstract

Yanan Sun1,*, Xiaoyan Zou1,*, Jun He1 and Yuqin Mao1

1Department of Gynecology and Obstetrics, Daqing Oilfield General Hospital, Daqing 163000, China

*These authors contributed equally to this work

Correspondence to:

Yanan Sun, email: ynsundq@163.com

Keywords: biomarkers, endometrial carcinoma, long non-coding RNA

Received: March 13, 2017     Accepted: April 07, 2017     Published: April 30, 2017

ABSTRACT

Endometrial carcinoma is a complex disease characterized by both genetic, epigenetic and environmental factors. Increasing evidence has suggested that long non-coding RNAs (lncRNAs) play important roles in the development and progression of cancers. In this study, we performed a comparison analysis for lncRNA expression between patients with early-stage (stage I/II) and those with advanced-stage (stage III/IV) derived from The Cancer Genome Atlas (TCGA) project and identified 17 differentially expressed lncRNAs using student t-test. Five of the 17 differentially expressed lncRNAs were selected as optimal biomarkers that are significantly associated with progression of UCEC using random forest feature selection procedure. A risk classifier of five lncRNAs was developed to as a molecular signature that identifies patients at high risk for progression using support vector machine. Results of five-lncRNA risk classifier achieved high discriminatory performance in distinguishing advanced stage from early stage with 78% prediction accuracy, 96.6% sensitivity and 76.6% specificity. Functional analysis suggested that these five lncRNA biomarkers may play critical roles in the progression of UCEC by participating in important cancer-related biological processes. Our study will help to improve our understanding of underlying mechanisms in the progression of UCEC and provide novel lncRNAs as candidate predictive biomarkers for the identification of patients with high risk for progression.


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