Analysis of the dynamic aberrant landscape of DNA methylation and gene expression during arsenic-induced cell transformation

Abstract Inorganic arsenic is a well-known carcinogen associated with several types of cancer, but the mechanisms involved in arsenic-induced carcinogenesis are not fully understood. Recent evidence points to epigenetic dysregulation as an important mechanism in this process; however, the effects of epigenetic alterations in gene expression have not been explored in depth. Using microarray data and applying a multivariate clustering analysis in a Gaussian mixture model, we describe the alterations in DNA methylation around the promoter region and the impact on gene expression in HaCaT cells during the transformation process caused by chronic exposure to arsenic. Using this clustering approach, the genes were grouped according to their methylation and expression status in the epigenetic landscape, and the changes that occurred during the cellular transformation were identified adequately. Thus, we present a valuable method for identifying epigenomic dysregulation.