Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8645463 | Gene | 2018 | 8 Pages |
Abstract
The epigenetics methylation of cytosine is the most common epigenetic form in DNA sequences. It is highly concentrated in the promoter regions of the genes, leading to an inactivation of tumor suppressors regardless of their initial function. In this work, we aim to identify the highly methylated regions; the cytosine-phosphate-guanine (CpG) island located on the promoters and/or the first exon gene known for their key roles in the cell cycle, hence the need to study gene-gene interactions. The Frommer and hidden Markov model algorithms are used as computational methods to identify CpG islands with specificity and sensitivity up to 76% and 80%, respectively. The results obtained show, on the one hand, that the genes studied are suspected of developing hypermethylation in the promoter region of the gene involved in the case of a cancer. We then showed that the relative richness in CG results from a high level of methylation. On the other hand, we observe that the gene-gene interaction exhibits co-expression between the chosen genes. This let us to conclude that the hidden Markov model algorithm predicts more specific and valuable information about the hypermethylation in gene as a preventive and diagnostics tools for the personalized medicine; as that the tumor-suppresser-genes have relative co-expression and complementary relations which the hypermethylation affect in the samples studied in our work.
Keywords
HMMNBNCpGCGIMGMTACCCDH1CHEK2PALB2BRIP1RAD50BRCA2STK11BARD1RAD51Cp53MCCDNMTsataxia telangiectasia mutatedDNA methyltransferaseDNApositive predictive valuedeoxyribonucleic acidcheckpoint kinase 2CpG islandsCpG islandbase pairSensitivityATMbreast cancer 2breast cancer 1serine/threonine kinase 11Cytosine-phosphate-GuanineCorrelation coefficientphosphatase and tensin homologtrue positivefalse positiveHidden Markov modelfalse negativetrue negativeNibrinSpecificitytumor protein 53Personalized medicineBRCA1Ptencadherin-1
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Authors
Imane Saif, Yassine Kasmi, Karam Allali, Moulay Mustapha Ennaji,