Identification of Driver Genes and miRNAs in Ovarian Cancer through an Integrated In-Silico Approach.

ABSTRACT: Ovarian cancer is the eighth-most common cancer in women and has the highest rate of death among all gynecological malignancies in the Western world. Increasing evidence shows that miRNAs are connected to the progression of ovarian cancer. In the current study, we focus on the identification of miRNA and its associated genes that are responsible for the early prognosis of patients with ovarian cancer. The microarray dataset GSE119055 used in this study was retrieved via the publicly available GEO database by NCBI for the analysis of DEGs. The miRNA GSE119055 dataset includes six ovarian carcinoma samples along with three healthy/primary samples. In our study, DEM analysis of ovarian carcinoma and healthy subjects was performed using R Software to transform and normalize all transcriptomic

SUBMITTER: Beg A 

PROVIDER: S-EPMC9952540 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature