Cargando…
Uncovering potential genes in colorectal cancer based on integrated and DNA methylation analysis in the gene expression omnibus database
BACKGROUND: Colorectal cancer (CRC) is major cancer-related death. The aim of this study was to identify differentially expressed and differentially methylated genes, contributing to explore the molecular mechanism of CRC. METHODS: Firstly, the data of gene transcriptome and genome-wide DNA methylat...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8815138/ https://www.ncbi.nlm.nih.gov/pubmed/35114976 http://dx.doi.org/10.1186/s12885-022-09185-0 |
Sumario: | BACKGROUND: Colorectal cancer (CRC) is major cancer-related death. The aim of this study was to identify differentially expressed and differentially methylated genes, contributing to explore the molecular mechanism of CRC. METHODS: Firstly, the data of gene transcriptome and genome-wide DNA methylation expression were downloaded from the Gene Expression Omnibus database. Secondly, functional analysis of differentially expressed and differentially methylated genes was performed, followed by protein-protein interaction (PPI) analysis. Thirdly, the Cancer Genome Atlas (TCGA) dataset and in vitro experiment was used to validate the expression of selected differentially expressed and differentially methylated genes. Finally, diagnosis and prognosis analysis of selected differentially expressed and differentially methylated genes was performed. RESULTS: Up to 1958 differentially expressed (1025 up-regulated and 993 down-regulated) genes and 858 differentially methylated (800 hypermethylated and 58 hypomethylated) genes were identified. Interestingly, some genes, such as GFRA2 and MDFI, were differentially expressed-methylated genes. Purine metabolism (involved IMPDH1), cell adhesion molecules and PI3K-Akt signaling pathway were significantly enriched signaling pathways. GFRA2, FOXQ1, CDH3, CLDN1, SCGN, BEST4, CXCL12, CA7, SHMT2, TRIP13, MDFI and IMPDH1 had a diagnostic value for CRC. In addition, BEST4, SHMT2 and TRIP13 were significantly associated with patients’ survival. CONCLUSIONS: The identified altered genes may be involved in tumorigenesis of CRC. In addition, BEST4, SHMT2 and TRIP13 may be considered as diagnosis and prognostic biomarkers for CRC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09185-0. |
---|