Computational Analysis of Association Pattern Among Patients with Mullerian Mixed Tumor and Serous Ovarian Cancer

Background: Ovarian cancer is the fifth most deadly cancer in women, and is usually diagnosed too late. malignant mixed Mullerian tumour (MMMT) of the uterine is an extremely rare and aggressive malignancy. The majority of these tumors arise in the uterus, they can also occur in ovaries, fallopian tubes, and cervix. These two diseases cause problems in the fertility and often is requires to ovary preservation. The purpose of this study is to finding the common and important genes as a thera-peutic target.Materials and Methods: All genes involve in mullerian mixed tumor and serous ovarian cancer were obtained from Genecard and disease databases. Then Common genes of these two dis-eases were identified by venn diagram. The network was found-ed by string web server and Cytoscape software (version 3.6.1), also main component of the network was analyzed with param-eters including degree, betweenness, and closeness.Results: Output of genecards database shown 312 genes in mullerian mixed tumor and 2048 genes in serous ovarian cancer is differential expressed. 202 genes were common between mullerian mixed tumor and serous ovarian cancer. IGF1, LEP, GHRL, BRCA1, LIF, CGA, GHR, SHBG, GATA6 are genes with high degree among the 202 genes. Nine crucial were ana-lyzed by GO analysis, in which via molecular function among them hormone activity (GO:0005179, adj.P value: 1.26e-6) was disclosed as top category, Also Biological Process (GO:0048639) and Cellular Component (GO:0000931) were identified.Conclusion: The analyses of these common genes showed that there are crucial in cancer progression. Therefore, these genes and pathways involved in it can be considered as an appropriate target for cancer control and treatment. And so will be helpful in controlling infertility.

Keywords:

Mullerian Tumor , Ovarian Cancer , Infertility , Gen-ecards , Cytoscape