Epigenetic and gene expression studies in carcinoma of human uterine cervix

Abstract

DNA methylation is increasingly recognized as an important epigenetic event playing central role in regulating gene expression and aberrant methylation is shown to play central role in the initiation and progression of cancer in humans. Aberrant methylation in the form of loss (hypomethylation) or gain (hypermethylation) is commonly observed in cancer. Aberrant methylation of key genes is common in various cancers but is less well studied in cervical cancer in India. However, its impact on cervical carcinogenesis is not fully determined, and its potential as a diagnostic biomarker remains to be validated. In the present study, an attempt has been made to understand the epigenetic aspects of cervical cancer (i) by evaluation the DNA methylation at genome wide as well as at gene specific level followed by their validation in a panel of non malignant, pre malignant and malignant cervical samples (ii) to identify the influence of methylation on the expression of corresponding genes and (iii) whether this silencing could be reactivated by demethylation. In the present study we have used nested PCR and direct sequencing approach for Human papilloma virus (HPV) genotyping. The genome wide 5 methyl cytosine content which reflects the global methylation level was estimated using reverse phase HPLC (RP-HPLC). The genome wide methylation changes in CpG islands were identified by methylation sensitive arbitrarily primed PCR (MS-AP-PCR) and differential methylation hybridization based microarray approach (DMH-Microarray).The microarray data was processed through extensive bioinformatic analysis to identify ontological process altered, gene to gene interaction and pathways analysis. The results of the study (differentially methylated regions) were validated in a panel of non malignant and malignant cervical samples by dimethyl sulphoxide polymerase chain reaction (MS-DMSO-PCR), combined bisulfite restriction analysis (COBRA) and bisulfate genomic sequencing.