Analyzing tumor cell gene expression is essential when it comes to understanding cancer physiopathology. Identifying transcription factor binding sites (TFBSs) that exhibit differential methylation patterns establishes a correlation between RNA polymerization and epigenetic changes at cis-regulatory elements in the genome. In this context, this project aims to combine data generated through ChIP-seq and DNA binding motif analyses available from ENCODE and TRANSFAC databases to evaluate TCGA DNA methylation changes between normal and cancer cells at the level of the individual protein/DNA interaction site. All analytical methods will be implemented by using the open-source R programming language, Bioconductor packages, and HOMER software in order to identify molecular signatures capable of defining the establishment of abnormal DNA methylation profiles at genomic regulatory elements and eases further studies by our group in order to characterize specific transcriptional networks implicated with cancer progression.
News published in Agência FAPESP Newsletter about the scholarship: