| dc.description.abstract | DNA methylation is an important contributor for prostate cancer development and progression. It has been studied experimentally for years, but, lately, high-throughput technologies are able to produce genome-wide DNA methylation data that can be analyzed using various computational approaches. Thus, this study aims to bioinformatically investigate different DNA methylation and gene expression patterns in prostate cancer. DNA methylation data from three datasets (TCGA, Absher and Kirby) was correlated with gene expression data in order to distinguish different regulation patterns. Classically, increased DNA methylation in promoter regions is being associated with gene expression downregulation. Although, results of the present project demonstrate another robust pattern, where DNA hypermethylation in promoter regions of 1,058 common genes is accompanied by upregulated expression.
After analyzing expression and methylation values in the same samples from TCGA dataset, expression overcompensation in a dataset as an explanation for upregulation was excluded. Further reasons behind the pattern were investigated using TCGA DNA methylation data with extended list of probes and includes the presence of methylated positions in CpG islands, distance to transcription start sites and alternative TSSs. As compared with the downregulated genes in the classical pattern, upregulated genes were shown to have more positions in CpG islands and closer to TSSs. Moreover, the presence of alternative TSS in prostate was demonstrated, also disclosing the limitations of methylation detection systems.
In conclusion, indications from a present study suggest a possible DNA methylation role in gene expression upregulation in prostate cancer, which prompts to reconsider the classical believe that DNA methylation always leads to gene suppression. | nb_NO |
