科研之友
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摘要
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.
