Author/Authors :
Wang Jing نويسنده , Qu Lu-yun نويسنده Department of Gynecology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University Medical College, Yantai, Shandong Province, China , Jiang Hai-yang نويسنده Department of Gynecology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University Medical College, Yantai, Shandong Province, China , Li Zeng-hui نويسنده Department of Gynecology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University Medical College, Yantai, Shandong Province, China , Li Xiao-hong نويسنده Department of Gynecology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University Medical College, Yantai, Shandong Province, China , Hou Jian-qing نويسنده Department of Gynecology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University Medical College, Yantai, Shandong Province, China
Abstract :
[Background]Ovarian Cancer is one of the most fatal female neoplasms associated with high mortality. Finding of the new mechanisms involved in the development of ovarian cancer will help us to better diagnosis and effective treatment.[Objectives]The current bioinformatics study aimed at investigating the relationship between messenger RNA (mRNA) and long non-coding RNA (lncRNA) in ovarian cancer through the LncRNAs2Pathways method.[Methods]The genome-wide lncRNA and mRNA data obtained from 185 ovarian cancer and healthy control samples originated from Michigan Medical School were downloaded and pretreated from European bioinformatics institute (EMBL-EBI) database. The interactions between miRNA and mRNA, and the intersections between lncRNA and miRNA were identified with starBase version 2.0. A long non-coding RNA-mediated ceRNA network (LMCN) was constructed by integrating lncRNA-mRNA and lncRNA-mRNA intersections. Then, the lncRNAs were mapped to the network, and these lncRNAs were regarded as source nodes, and the random walk with restart (RWR) algorithm was also applied to evaluate the effect of source nodes on protein-coding genes. Finally, the Kolmogorov-Smirnov-like statistics weighted by the propagation score was used to evaluate the enrichment value of each functional pathway.[Results]After preliminary screening, the gene expression profile including 12,437 genes was obtained. The LMCN network including 11 lncRNA and 367 mRNA were identified. A total of 11 differentially expressed lncRNAs between the normal and ovarian cancer samples by the LCMN network were identified. The LncRNAs2Pathways screened six functional pathways (P < 0.05) coregulated by lncRNAs related to ovarian cancer.[Conclusions]A total of six functional pathways related to lncRNA and mRNA interactions in ovarian cancer were identified. This finding is beneficial for effective diagnosis of patients with ovarian cancer, and also provides a new insight into the treatment of this disease.
