Identification of potentially critical differentially methylated genes in nasopharyngeal carcinoma: A comprehensive analysis of methylation profiling and gene expression profiling

Epigenome-Wide DNA Methylation Profiling in Colorectal Cancer and Normal Adjacent Colon Using Infinium Human Methylation 450K

The aims were to profile the DNA methylation in colorectal cancer (CRC) and to explore cancer-specific methylation biomarkers. Fifty-four pairs of CRCs and the adjacent normal tissues were subjected to Infinium Human Methylation 450K assay and analysed using ChAMP R package. A total of 26,093 differentially methylated probes were identified, which represent 6156 genes; 650 probes were hypermethylated, and 25,443 were hypomethylated. Hypermethylated sites were common in CpG islands, while hypomethylated sites were in open sea. Most of the hypermethylated genes were associated with pathways in cancer, while the hypomethylated genes were involved in the PI3K-AKT signalling pathway. Among the identified differentially methylated probes, we found evidence of four potential probes in CRCs versus adjacent normal; HOXA2 cg06786372, OPLAH cg17301223, cg15638338, and TRIM31 cg02583465 that could serve as a new biomarker in CRC since these probes were aberrantly methylated in CRC as well as involved in the progression of CRC. Furthermore, we revealed the potential of promoter methylation ADHFE1 cg18065361 in differentiating the CRC from normal colonic tissue from the integrated analysis. In conclusion, aberrant DNA methylation is significantly involved in CRC pathogenesis and is associated with gene silencing. This study reports several potential important methylated genes in CRC and, therefore, merit further validation as novel candidate biomarker genes in CRC.

A Four-Gene Signature Model Improves the Prediction of Distant Metastasis in Patients with Nasopharyngeal Carcinoma: A Retrospective, Three-Center Observational Study

Background: Similar to that in other malignant tumors, distant metastasis is one of the most important causes of poor prognosis in nasopharyngeal carcinoma (NPC). However, the genetic hallmarks and networks that regulate the distant metastasis of NPC are not fully understood. Methods: In this study, we performed high-throughput screening of mRNA expression profiles in 92 NPC samples collected from 3hospitals and detected the mRNA expression levels of 31,503 genes in these samples. Gene functional enrichment analyses were performed using gene set enrichment analysis (GSEA). Least absolute shrinkage and selection operator (LASSO) was applied to select prognostic genes and a Cox proportional hazards regression model including these genes was constructed to predict prognosis. The Kaplan-Meier curve and time-dependent receiver operating characteristic (ROC) curve were plotted to assess the performance of this model. Univariate and multivariate analyses were performed using the Cox proportion hazard model to test the independence of prognostic effect of gene model and other clinical features. Results: A total of 1837 differentially expressed genes between patients with and without distant metastasis were identified in the training cohort, including 869 upregulated genes and 968 downregulated genes. Six gene sets, including the Wnt/β catenin signaling pathway, hedgehog (Hh) signaling pathway, Notch signaling pathway, mitotic spindle, apical surface, and estrogen response late, were enriched in patients with distant metastasis. A four-gene signature model was constructed in the training cohort, and according to the time-dependent ROC curve, this model had certain accuracy in predicting distant metastasis-free survival (DMFS) in both the training and validation cohorts. Conclusion: We developed a four-gene signature model that can evaluate the distant metastasis risk of NPC patients and may also provide novel therapeutic targets for NPC treatment in the near future.

Screening and bioinformatical analysis of differentially expressed genes in nasopharyngeal carcinoma

Objective: To identify differentially expressed genes via bioinformatical analysis for nasopharyngeal carcinoma (NPC) and explore potential biomarkers for NPC.

Methods: We downloaded the NPC gene expression datasets (GSE40290, GSE53819) and obtained differentially expressed genes (DEGs) via GEO2R. Functional analysis of DEGs was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. In order to explore the interaction of DEGs and screen the core genes, we established protein-protein interaction (PPI) network. Then the expression level, prognostic and diagnostic analysis of the core genes in NPC were performed to reveal their potential effects on NPC. Furthermore, we obtained the transcription factors (TF) and microRNAs of core genes to construct the coregulatory network.

Results: We obtained 124 up-regulated genes and 190 down-regulated genes in total. These genes were found to be related to signal transduction, extracellular matrix organization and cell adhesion based on GO analysis. KEGG analysis revealed that the NF-kappa B (NF-κB) signaling pathway, pathways in cancer were mainly enriched signaling pathways. 25 core genes were obtained by constructing PPI network. Then the high expression of 10 core genes in NPC were verified via GEPIA, Oncomine databases and laboratory experiments. The TF-microRNA coregulatory network of the 10 core genes was built. Survival and diagnostic analysis indicated that SPP1 had negative influence on the prognosis of NPC patients based on two datasets and nine up-regulated core genes (FN1, MMP1, MMP3, PLAU, PLAUR, SERPINE1, SPP1, COL8A1, COL10A1) might be diagnostic markers for NPC.

Conclusions: Core genes of NPC were screened out by bioinformatical analysis in the present study and these genes may serve as prognostic and diagnostic biomarkers for NPC.

Genome wide methylation profiling of selected matched soft tissue sarcomas identifies methylation changes in metastatic and recurrent disease

In this study we used the Illumina Infinium Methylation array to investigate in a cohort of matched archival human tissue samples (n = 32) from 14 individuals with soft tissue sarcomas if genome-wide methylation changes occur during metastatic and recurrent (Met/Rec) disease. A range of sarcoma types were selected for this study: leiomyosarcoma (LMS), myxofibrosarcoma (MFS), rhabdomyosarcoma (RMS) and synovial sarcoma (SS). We identified differential methylation in all Met/Rec matched samples, demonstrating that epigenomic differences develop during the clonal evolution of sarcomas. Differentially methylated regions and genes were detected, not been previously implicated in sarcoma progression, including at PTPRN2 and DAXX in LMS, WT1-AS and TNXB in SS, VENTX and NTRK3 in pleomorphic RMS and MEST and the C14MC / miR-379/miR-656 in MFS. Our overall findings indicate the presence of objective epigenetic differences across primary and Met/Rec human tissue samples not previously reported.

Genome-Wide Open Chromatin Methylome Profiles in Colorectal Cancer

The methylome of open chromatins was investigated in colorectal cancer (CRC) to explore cancer-specific methylation and potential biomarkers. Epigenome-wide methylome of open chromatins was studied in colorectal cancer tissues using the Infinium DNA MethylationEPIC assay. Differentially methylated regions were identified using the ChAMP Bioconductor. Our stringent analysis led to the discovery of 2187 significant differentially methylated open chromatins in CRCs. More hypomethylated probes were observed and the trend was similar across all chromosomes. The majority of hyper- and hypomethylated probes in open chromatin were in chromosome 1. Our unsupervised hierarchical clustering analysis showed that 40 significant differentially methylated open chromatins were able to segregate CRC from normal colonic tissues. Receiver operating characteristic analyses from the top 40 probes revealed several significant, highly discriminative, specific and sensitive probes such as OPLAH cg26256223, EYA4 cg01328892, and CCNA1 cg11513637, among others. OPLAH cg26256223 hypermethylation is associated with reduced gene expression in the CRC. This study reports many open chromatin loci with novel differential methylation statuses, some of which with the potential as candidate markers for diagnostic purposes.

Genome-Wide DNA Methylome and Transcriptome Analysis of Porcine Intestinal Epithelial Cells upon Deoxynivalenol Exposure

Deoxynivalenol (DON) is a type of mycotoxin that is disruptive to intestinal and immune systems. To better understand the molecular effects of DON exposure, we performed genome-wide comparisons of DNA methylation and gene expression from porcine intestinal epithelial cell IPEC-J2 upon DON exposure using reduced representation bisulfite sequencing and RNA-seq technologies. We characterized the methylation pattern changes and found 3030 differentially methylated regions. Moreover, 3226 genes showing differential expression were enriched in pathways of protein and nucleic acid synthesis and ribosome biogenesis. Integrative analysis identified 29 genes showing inverse correlations between promoter methylation and expression. Altered DNA methylation and expression of various genes suggested their roles and potential functional interactions upon DON exposure. Our data provided new insights into epigenetic and transcriptomic alterations of intestinal epithelial cells upon DON exposure and may advance the identification of biomarkers and drug targets for predicting and controlling the toxic effects of this common mycotoxin.

Up-regulation of the IRX2 gene predicts poor prognosis in nasopharyngeal carcinoma

Aberrant expression of the IRX2 gene contributes to the oncogenesis and progression of various cancers. In this study, we analyzed the clinical significance and the prognostic value of mRNA expression level of the IRX2 gene in nasopharyngeal carcinoma (NPC) patients, with the goal to find a novel prognostic biomarker for NPC. Tissue samples were collected prior to treatment from 71 NPC patients for the detection of mRNA expression level of a total of 31503 genes, with high throughput screening of the mRNA expression profile. The Kaplan-Meier curves and log-rank test were used for univariate analyses to determine if the mRNA expression level of IRX2 and other 31502 genes, as well as clinical characteristics were of prognostic value for overall survival (OS), distant metastasis-free survival (DMFS) and disease-free survival (DFS). Regularized Cox regression was performed to test the contribution of prognostic factors to OS, DMFS, and DFS of NPC patients. The Cox proportional hazard model was used to test the independence of prognostic effect of IRX2 and other clinical features. The receiver operator characteristic curve was drawn and the area under the curve (AUC) was calculated to evaluate the predictive power of IRX2 gene. Univariate analyses showed a higher mRNA expression level of the IRX2 gene correlated with shorter OS (P = 0.001), DMFS (P = 0.003), and DFS (P = 0.007). Regularized Cox regression and Cox proportional hazard model analyses further showed that ahigher mRNA expression level of the IRX2 gene in the primary NPC was an independent prognostic factor for OS (Coxnet beta = 0.03, Cox proportion hazard model P = 0.038), DMFS (Coxnet beta = 0.018, Cox proportion hazard model P = 0.01) and DFS (Coxnet beta = 0.008, Cox proportion hazard model P = 0.029). The AUC showed that the mRNA expression level of the IRX2 gene is a significant predictor for predicting the OS (AUC value = 0.7105) and DMFS (AUC value = 0.7027) of NPC patients. Our results demonstrated that the IRX2 gene may be a novel independent unfavorable prognostic factor for NPC patients.

Integrative analysis of promising molecular biomarkers and pathways for coronary artery disease using WGCNA and MetaDE methods

The present study aimed to examine the molecular mechanisms of coronary artery disease (CAD). A total of four microarray datasets (training dataset no. GSE12288; validation dataset nos. GSE20680, GSE20681 and GSE42148) were downloaded from the Gene Expression Omnibus database, which included CAD and healthy samples. Weighted gene co-expression network analysis was applied to identify highly preserved modules across the four datasets. Differentially expressed genes (DEGs) with significant consistency in the four datasets were selected using the MetaDE method. The overlapping genes amongst the DEGs with significant consistency and in the preserved modules were used to construct a protein-protein interaction (PPI) network, followed by functional enrichment analysis. A total of 11 modules were established in the training dataset, and five of them were highly preserved across all four datasets, including 873 genes. There was a total of 836 DEGs with significant consistency in the four datasets. A total of 177 overlapping genes were selected, with which a PPI network was constructed. The top five genes of the PPI network were identified based on their degrees: LCK proto-oncogene, Src family tyrosine kinase (LCK), euchromatic histone lysine methyltransferase 2 (EHMT2), inosine monophosphate dehydrogenase 2 (IMPDH2), protein phosphatase 4 catalytic subunit (PPP4C) and ζ-chain of T-cell receptor associated protein kinase 70 (ZAP70). Genes in the PPI network were significantly involved in a number of Kyoto Encyclopedia Genes and Genomes pathways, including the ‘natural killer cell mediated cytotoxicity’, ‘primary immunodeficiency’ and ‘Fc gamma R-mediated phagocytosis’ pathways. LCK, EHMT2, IMPDH2, PPP4C and ZAP70 are suggested as promising molecular biomarkers for CAD. The ‘natural killer cell mediated cytotoxicity’, ‘primary immunodeficiency’ and ‘Fc gamma R-mediated phagocytosis’ pathways may serve important roles in CAD.