Long Noncoding RNAs in a Risk Score System for Ovarian Cancer
Posted: Tuesday, July 23, 2019
Some long noncoding RNAs seem to be associated with an increased risk of ovarian cancer and may have potential as prognostic biomarkers, according to a bioinformatics study by Qian Zhao, PhD, and Conghong Fan, of the Chengdu Women’s & Children’s Central Hospital, China. Their methodology and findings were published in BMC Medical Genetics.
In this study, RNA-expression data and clinical information from patients with ovarian cancer were obtained from a public database; The Cancer Genome Atlas, GSE32062, and GSE17260 were used as the training and validation data sets, respectively. A weighed gene co-expression network analysis was used to identify long noncoding RNAs in stable modules associated with ovarian cancer, and a validated risk prediction model was used to assign a risk score to each sample. Gene set enrichment analysis was used to examine relevant pathway associations.
The researchers identified 4 highly stable modules associated with ovarian cancer, and 33 long noncoding RNAs implicated in the progression of ovarian cancer. Of them, five long no-coding RNAs—GAS5, HCP5, PART1, SNHG11, and SNHG5—were identified as the optimal prognosis combination for determining a risk score. Pathway enrichment analysis of their target genes showed an association with cell local adhesion, cancer signaling pathways, JAK-STAT signaling, and endogenous cell receptor interaction.
“The risk score system established in this study could provide a novel reliable method to identify individuals at high risk of [ovarian cancer]. In addition, the five prognostic [long noncoding] RNAs identified here are promising potential prognostic biomarkers that could help to elucidate the pathogenesis of [ovarian cancer],” the authors concluded.
Disclosure: The study authors reported no conflicts of interest.