Analysis of long non‑coding RNA expression profiles in ovarian cancer

Shen,Liang; Liu,Wei; Cui,Jing; Li,Juan; Li,Changzhong

doi:10.3892/ol.2017.6283

Analysis of long non‑coding RNA expression profiles in ovarian cancer

Authors:
- Liang Shen
- Wei Liu
- Jing Cui
- Juan Li
- Changzhong Li
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Affiliations: Department of Obstetrics and Gynecology, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, Shandong 250021, P.R. China, Department of Oral Surgery, Jinan Stomatology Hospital, Jinan, Shandong 250021, P.R. China
Published online on: May 31, 2017 https://doi.org/10.3892/ol.2017.6283
Pages: 1526-1530
Copyright: © Shen et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

Ovarian cancer is one of the major threats to female health. Identifying cancer cases at an early stage and selecting effective therapeutic drugs for patients is challenging. The number of studies concerning long non‑coding RNAs (lncRNAs) is increasing rapidly; there is a large body of evidence indicating that lncRNAs are crucial in oncogenic and tumor‑suppression mechanisms. Therefore, in the present study, lncRNA expression in ovarian cancer was considered. All of the existing ovarian cancer microarray datasets in the Gene Expression Omnibus database were assessed and two met the criteria for the present study; these were designated the training and validation sets. A re‑annotation pipeline method was established to annotate lncRNAs from existing probe sets. When comparing ovarian cancer with normal ovarian tissues, seven lncRNAs from the RefSeq database, based on their combined ability to classify tissue in the training set, were identified and validated with the validation set. Research into the molecular functions of the seven identified lncRNAs may contribute to the understanding of ovarian cancer oncogenesis; they may also be candidates for novel ovarian cancer biomarkers.

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