Identification of hub genes as novel biomarkers in Ovarian Cancer using High-Throughput Transcriptome data analysis

Introduction: Ovarian cancer (OC) is a malignancy of the female reproductive system andis the third most common cancer among all cancers in women. Due to the fact patients are diagnosedin advanced stages, it is the fifth cause of cancer death among women [۱, ۲]. The central objective ofthis study is to discover novel biomarkers associated with OC to predict prognosis and developimproved treatment strategies .The GSE۶۶۹۵۷ dataset was obtained from GEO database, consisting of ۵۷ cancer and ۱۲ normalsamples. Principal Component Analysis (PCA) was executed to assess the consistency of the samples.Finally, the statistical analysis was carried out using the LIMMA package. Differentially expressedgenes (DEGs) were identified using the criteria of |𝑙𝑜𝑔۲𝐹𝐶|> ۵ and adj P-value < ۰.۰۵. The Kaplan-Meier plotter was employed to assess the correlation between gene expression and survival outcomes .Microarray analysis was conducted to assess the expression profile of ۶۹ samples. A total of ۳۷ DEGswere identified, of which ۳۳ were up-regulated and ۴ were down-regulated. Among them, two genesCFB, and PPL have been discovered in previous studies to be related to cancers such as Pancreatic andlung. These two genes show a significant increase in expression in this dataset. Based on the informationprovided by the GeneCards and Reactome pathway databases, these genes exert regulatory control overvarious crucial pathways, including complement activation pathways, and innate and adaptive immunesystems. According to Kaplan-Meier plots DEGs are correlated with poor prognosis in OC.Our investigation revealed that the CFB and PPL genes play significant roles in OC and they arecorrelated with poor prognosis in OC.

کلیدواژه ها:

ovarian cancer ، biomarker ، microarray