Functional Analysis of Differentially Expressed Genes Associated with the Conditions of Polycystic Ovary Syndrome and Endometrial Cancer

Abstract

Polycystic ovary syndrome is a metabolic and endocrinal disorder common in women of reproductive age and has led to infertility prevailing across the world. The prevalence of PCOS is 33% worldwide. PCOS can also lead to serious conditions such as anxiety, depression, Insulin resistance, obesity, metabolic disorders (dyslipidemia), cardiovascular complications and endometrial cancer. Linkage of PCOS with endometrial cancer has been proposed by many studies. Beginning in the lining of uterus (endometrium), the most common gynecological malignancy is endometrial cancer. PCOS is a major risk factor associated with endometrial cancer. So, there is a dire need to analyze these diseases at molecular level to propose potential biomarkers and therapeutic targets. Microarray and RNA-Seq data analysis have been performed for analyzing the molecular patterns of the diseases. Different datasets of PCOS and EC have been analyzed in order to compare expression profiles of transcripts. Subsequently, pathway analysis of all datasets provides the evidences for a common pathway which has been affected in both diseases. This pathway is known as “Focal adhesion”. This pathway is further quantitatively modeled by using the expression values of differentially expressed genes. High sensitivity level of ACTG1 and CycD have been observed towards cell mobility and cell proliferation conditions, respectively. Change in expression of these genes can lead towards endometrial cancer and can be used as important therapeutic targets.