Abstract
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.
Highlights
Colorectal cancer (CRC) is one of the most common malignancies, which estimated more than 1.9 million new cases in developed countries in 2020
Identification of differentially methylated genes (DMGs) A total of 871-shared DMGs (496 hyper and 375 hypo) were obtained in the comparison of the tumor and the normal group, according to the cut-off value selected for the screening
The results indicated that high methylation of Secreted Frizzled Related Protein 2 (SFRP2), ZNF726 and BMP2 lead to lower overall survival (OS) rate than low methylation
Summary
Colorectal cancer (CRC) is one of the most common malignancies, which estimated more than 1.9 million new cases in developed countries in 2020. While numerous studies have shown that several genes in CRC have abnormal DNA hyper- or hypo- methylation, the general profile and pathways of the interaction network are still unknown.[6]. Over the last few years, a number of methodologies have been established that rely on the use of bisulfideconverted DNA. Such techniques have been used to identify changes in gene or allele-DNA methylation but have been modified for genome-DNA methylation analysis and are capable of delivering singleresolution DNA methylation information [7,8,9,10]. The goal of this study was to identify aberrantly differentially methylated genes (DMGs) and pathways through bioinformatics analysis among Iranian CRC patients using Methylation Generation Sequencing
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