Aberrantly methylated-differentially genes and pathways among Iranian patients with colorectal cancer

Cancer Cell International

Marjan Azghandi¹  Mohammad Amin Kerachian²  Mahla Ghorbani³ 

[1] Cancer Genetics Research Unit, Reza Radiotherapy and Oncology Center, Mashhad, Iran;Department of Animal Science, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran;Cancer Genetics Research Unit, Reza Radiotherapy and Oncology Center, Mashhad, Iran;Medical Genetics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran;Department of Medical Genetics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran;Department of Biology, Faculty of Sciences, Mashhad Branch, Islamic Azad University, Mashhad, Iran;Cancer Genetics Research Unit, Reza Radiotherapy and Oncology Center, Mashhad, Iran;

关键词: Diagnostic;    Colon adenocarcinoma;    Epigenetic;    In silico;    Methylation;   

DOI  :  10.1186/s12935-021-02053-0

来源: Springer

【 摘 要 】

BackgroundMethylation plays an important role in colorectal cancer (CRC) pathogenesis. The goal of this study was to identify aberrantly differentially methylated genes (DMGs) and pathways through bioinformatics analysis among Iranian CRC patients using Methylation Next Generation Sequencing.MethodsThis study has integrated results of SureSelectXT Methyl-Seq Target with the potential key candidate genes and pathways in CRC. Six CRC and six samples of normal colon were integrated and deeply analyzed. In addition to this gene methylation profiling, several other gene methylation profiling datasets were obtained from Gene Expression Omnibus (GEO) and TCGA datasets. DMGs were sorted and candidate genes and enrichment pathways were analyzed. DMGs-associated protein–protein interaction network (PPI) was constructed based on the STRING online database.ResultsTotally, 320 genes were detected as common genes between our patients and selected GEO and TCGA datasets from the Agilent SureSelect analysis with selecting criteria of p-value < 0.05 and FC ≥ 1.5. DMGs were identified from hyper-DMGs PPI network complex and 10 KEGG pathways were identified. The most important modules were extracted from MCODE, as most of the corresponding genes were involved in cellular process and protein binding.ConclusionsHub genes including WNT2, SFRP2, ZNF726 and BMP2 were suggested as potentially diagnostic and therapeutic targets for CRC.

【 授权许可】

CC BY