Aberrantly methylated-differentially expressed genes and pathways in colorectal cancer

Liu, Jingwei; Li, Hao; Sun, Liping; Wang, Zhenning; Xing, Chengzhong; Yuan, Yuan

doi:10.1186/s12935-017-0444-4

Cited by 66 publications

(68 citation statements)

References 40 publications

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“…Liang et al, 2016; J. Liu et al, 2017;Makondi et al, 2018;Wu et al, 2017). Based on these results, aberrantly significant DEGs and pathways in CRC have been identified.…”

Section: Discussionmentioning

confidence: 99%

Identification of differentially expressed genes and biological characteristics of colorectal cancer by integrated bioinformatics analysis

Sun

Peng

et al. 2019

Journal Cellular Physiology

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Colorectal cancer (CRC) ranks as one of the most common malignant tumors worldwide. Its mortality rate has remained high in recent years. Therefore, the aim of this study was to identify significant differentially expressed genes (DEGs) involved in its pathogenesis, which may be used as novel biomarkers or potential therapeutic targets for CRC. The gene expression profiles of GSE21510, GSE32323, GSE89076, and GSE113513 were downloaded from the Gene Expression Omnibus (GEO) database. After screening DEGs in each GEO data set, we further used the robust rank aggregation method to identify 494 significant DEGs including 212 upregulated and 282 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by DAVID and the KOBAS online database, respectively. These DEGs were shown to be significantly enriched in different cancer‐related functions and pathways. Then, the STRING database was used to construct the protein–protein interaction network. The module analysis was performed by the MCODE plug‐in of Cytoscape based on the whole network. We finally filtered out seven hub genes by the cytoHubba plug‐in, including PPBP, CCL28, CXCL12, INSL5, CXCL3, CXCL10, and CXCL11. The expression validation and survival analysis of these hub genes were analyzed based on The Cancer Genome Atlas database. In conclusion, the robust DEGs associated with the carcinogenesis of CRC were screened through the GEO database, and integrated bioinformatics analysis was conducted. Our study provides reliable molecular biomarkers for screening and diagnosis, prognosis as well as novel therapeutic targets for CRC.

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“…Liang et al, 2016; J. Liu et al, 2017;Makondi et al, 2018;Wu et al, 2017). Based on these results, aberrantly significant DEGs and pathways in CRC have been identified.…”

Section: Discussionmentioning

confidence: 99%

Identification of differentially expressed genes and biological characteristics of colorectal cancer by integrated bioinformatics analysis

Sun

Peng

et al. 2019

Journal Cellular Physiology

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“…Interactions with high confidence levels (>0.7) were retained, and the PPI was visualized according to previous methods. 27…”

Section: Ppi Network Construction and Analysismentioning

confidence: 99%

“…A P value < .05 was considered statistically significant. 27 PPIs and iron metabolism-regulated genes and proteins. The STRING database contains known and predicted physical, functional PPIs and identifies interaction partners according to a variety of criteria.…”

Section: Functional and Pathway Enrichment Analysismentioning

confidence: 99%

Iron metabolism gene expression and prognostic features of hepatocellular carcinoma

Shen

Zhao

et al. 2018

J of Cellular Biochemistry

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Iron metabolism is crucial to hepatocellular carcinoma progression and is a key determinant of prognosis. Protein-protein interactions within the iron metabolism gene network were analyzed using the European Molecular Biology Laboratory's Search Tool for Recurring Instances of Neighbouring Genes/Proteins database. We obtained 423 liver hepatocellular carcinoma gene expression profiles from the Cancer Genome Atlas database. The expression and pathway enrichment of representative iron intake genes (TFRC and DMT1), utilization genes (FTH1, FTL, HIF1A, HMOX1, SLC25A37, and SLC25A38), and efflux genes (FLVCR1 and SLC40A1) was investigated in tumor and adjacent tissues. We determined the relationship between iron metabolism and the prognostic features of liver hepatocellular carcinoma. The liver metabolism genes TFRC and FLVCR1 were related to survival, disease status, and prognosis in patients with hepatocellular carcinoma. Our results provide novel insight into liver cancer therapy.

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“…Recently, increasingly combined analysis of DNA methylation status and transcriptional expression in various tumors has been performed. A study made a bioinformatics-based discovery of possible aberrantly methylated-differentially expressed genes and pathways in colorectal cancer so as to unravel the carcinogenesis process [22]. Another study conducted integrated analysis on TCGA data to get a better understanding of molecular mechanisms involved in esophageal squamous cell carcinoma, contributing to a more precise prognosis detection [23].…”

Section: Discussionmentioning

confidence: 99%

Integrated analysis of DNA methylation and mRNA expression profiles to identify key genes in head and neck squamous cell carcinoma

Jin¹,

Qin

2020

Bioscience Reports

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DNA methylation has been demonstrated to play significant roles in the etiology and pathogenesis of head and neck squamous cell carcinoma (HNSCC). In the present study, methylation microarray dataset (GSE87053) and gene expression microarray dataset (GSE23558) were downloaded from GEO database and analyzed through R language. A total of 255 hypermethylated-downregulated genes and 114 hypomethylated-upregulated genes were finally identified. Functional enrichment analyses were performed and a comprehensive protein–protein interaction (PPI) network was constructed. Subsequently, the top ten hub genes selected by Cytoscape software were subjected to further analyses. It was illustrated that the expression level of CSF2, CTLA4, ETS1, PIK3CD, and CFTR was intimately associated with HNSCC. Survival analysis suggested that CTLA4 and FGFR2 could serve as effective independent prognostic biomarkers for HNSCC patients. Overall, our study lay a groundwork for further investigation into the underlying molecular mechanisms in HNSCC carcinogenesis, providing potential biomarkers and therapeutic targets for HNSCC.

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Aberrantly methylated-differentially expressed genes and pathways in colorectal cancer

Cited by 66 publications

References 40 publications

Identification of differentially expressed genes and biological characteristics of colorectal cancer by integrated bioinformatics analysis

Identification of differentially expressed genes and biological characteristics of colorectal cancer by integrated bioinformatics analysis

Iron metabolism gene expression and prognostic features of hepatocellular carcinoma

Integrated analysis of DNA methylation and mRNA expression profiles to identify key genes in head and neck squamous cell carcinoma

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