Analysis of the interplay between methylation and expression reveals its potential role in cancer aetiology.


Ozer B., Sezerman U.

Functional & integrative genomics, cilt.17, sa.1, ss.53-68, 2017 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 17 Sayı: 1
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1007/s10142-016-0533-9
  • Dergi Adı: Functional & integrative genomics
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.53-68
  • Anahtar Kelimeler: Bioinformatics, Methylation, Expression, Data integration, Integrative analysis, Functional enrichment analysis, Cancer biology, HUMAN PROSTATE-CANCER, FOCAL ADHESION KINASE, PROTEIN-COUPLED RECEPTORS, GENOME-WIDE ASSOCIATION, DNA-METHYLATION, GENE-EXPRESSION, COLORECTAL-CANCER, BREAST-CANCER, SIGNALING PATHWAYS, THYROID-CANCER
  • Acıbadem Mehmet Ali Aydınlar Üniversitesi Adresli: Hayır

Özet

With ongoing developments in technology, changes in DNA methylation levels have become prevalent to study cancer biology. Previous studies report that DNA methylation affects gene expression in a direct manner, most probably by blocking gene regulatory regions. In this study, we have studied the interplay between methylation and expression to improve our knowledge of cancer aetiology. For this purpose, we have investigated which genomic regions are of higher importance; hence, first exon, 5'UTR and 200 bp near the transcription start sites are proposed as being more crucial compared to other genomic regions. Furthermore, we have searched for a valid methylation level change threshold, and as a result, 25 % methylation change in previously determined genomic regions showed the highest inverse correlation with expression data. As a final step, we have examined the commonly affected genes and pathways by integrating methylation and expression information. Remarkably, the GPR115 gene and ErbB signalling pathway were found to be significantly altered for all cancer types in our analysis. Overall, combining methylation and expression information and identifying commonly affected genes and pathways in a variety of cancer types revealed new insights of cancer disease mechanisms. Moreover, compared to previous methylation-based studies, we have identified more important genomic regions and have defined a methylation change threshold level in order to obtain more reliable results. In addition to the novel analysis framework that involves the analysis of four different cancer types, our study exposes essential information regarding the contribution of methylation changes and its impact on cancer disease biology, which may facilitate the identification of new drug targets.