Effect of hypermethylation in ovarian cancer: Computational approach

Abstract

Ovarian cancer in women represents a mortality rate of >4% worldwide. In cancer, CpG islet hypermethylation of some gene promoters often leads to the inactivation of tumor suppressor genes. Ovarian cancer is characterized by a targeted hypermethylation, hence the need to study this hypermethylation. We have adopted the hypothesis that a very high mutation rate can cause the epimutation phenomenon, causing a 5-fold deamination methyl-cytosine in thymine, consequence of the mutation. To test this, we chose the P53, RASSF1A, WAF1, ARHI, CAV1, DOC-2, BRCA2 and BRCA1genes. The methylation status was first determined by the Chargaff coefficient, which represents a high percentage of about 50% for all the sequences chosen, secondly, the CpGo/e ratio was calculated. ANOVA test has been applied in order to be sure of the correlation between these two calculations andshowed thatthe Chargaff coefficientis significant. Lastly, we adopted Hidden Markov Models (HMM). To indicate exactly the CGI region in the promoters of the studied genes. This model maximizes the mathematical probability of having a hypermethylated region.