Integrated analysis of genome-wide DNA methylation and gene expression profiles identifies potential novel biomarkers of rectal cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE75550 | GEO | 2015/12/02
SECONDARY ACCESSION(S): PRJNA304511
REPOSITORIES: GEO
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Project description:DNA methylation was regarded as the promising biomarker for rectal cancer diagnosis. However, the optimal methylation biomarkers with ideal diagnostic performance for rectal cancer are still limited. To identify new molecular markers for rectal cancer, we mapped DNA methylation and transcriptomic profiles in the six rectal cancer and paired normal samples. Further analysis revealed the hypermethylated probes in cancer prone to be located in gene promoter. Meanwhile, transcriptome analysis presented 773 low-expressed and 1,161 over-expressed genes in rectal cancer. Correction analysis identified a panel of 36 genes with an inverse correlation between methylation and gene expression levels, including 10 known colorectal cancer related genes. From the other 26 novel marker genes, GFRA1 and GSTM2 were selected for further analysis on the basis of their biological functions. Further experiment analysis confirmed their methylation and expression status in a larger number (44) of rectal cancer samples, and ROC curves showed higher AUC than SEPT9, which has been used as a biomarker in rectal cancer. Our data suggests that aberrant DNA methylation of contiguous CpG sites in methylation array may be potential diagnostic markers of rectal cancer.
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Project description:DNA methylation was suggested as the promising biomarker for rectal cancer diagnosis. However, it remains a great challenge to search for the optimal methylation biomarkers to obtain ideal diagnostic performance. We aimed to identify new molecular markers for rectal cancer by evaluating their epigenomic and transcriptomic profiles. Genome-wide methylation analysis revealed 18568 probes with significant methylation differences between the six rectal cancer and paired normal samples. Transcriptome profiling presented 773 low-expressed and 1,161 over-expressed genes. After merging the DNA methylation with gene expression data, we identified a panel of 36 genes with an inverse correlation between methylation and gene expression levels. A genome-wide DNA methylation approach merged with array-based gene expression profiles allowed identifying a number of novel, epigenetically regulated candidate tumor-related genes in rectal carcinogenesis, which can be a good strategy to discover optimal DNA methylation diagnostic panels. Genome wide DNA methylation profiling of paired rectal cancers and adjacent normal tissues. The Illumina Human Methylation 450K BeadChip was used to obtain DNA methylation profiles across approximately 485,000 CpGs in all samples. Samples included six pairs of rectal cancers and adjacent normal tissues.
2015-12-02 | GSE75546 | GEO
Project description:DNA methylation was suggested as the promising biomarker for rectal cancer diagnosis. However, it remains a great challenge to search for the optimal methylation biomarkers to obtain ideal diagnostic performance. We aimed to identify new molecular markers for rectal cancer by evaluating their epigenomic and transcriptomic profiles. Genome-wide methylation analysis revealed 18568 probes with significant methylation differences between the six rectal cancer and paired normal samples. Transcriptome profiling presented 773 low-expressed and 1,161 over-expressed genes. After merging the DNA methylation with gene expression data, we identified a panel of 36 genes with an inverse correlation between methylation and gene expression levels. A genome-wide DNA methylation approach merged with array-based gene expression profiles allowed identifying a number of novel, epigenetically regulated candidate tumor-related genes in rectal carcinogenesis, which can be a good strategy to discover optimal DNA methylation diagnostic panels.
2015-12-02 | GSE75548 | GEO
Project description:Integrated analysis of genome-wide DNA methylation and gene expression profiles identifies potential novel biomarkers of rectal cancer
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Project description:As a noninvasive blood testing, the detection of cell-free DNA (cfDNA) methylation in plasma has raised an increasing interest due to diagnostic applications. Although extensively used in cfDNA methylation analysis, bisulfite sequencing is less cost-effective. In this study, we investigated the cfDNA methylation patterns in lung cancer patients by MeDIP-seq. Compared with the healthy individuals, 330 differentially methylated regions (DMRs) at gene promoters were identified in lung cancer patients with 33 hypermethylated and 297 hypomethylated regions, respectively. Moreover, these hypermethylated genes were validated with the publicly available DNA methylation data, yielding a set of ten significant differentially methylated genes in lung cancer, including B3GAT2, BCAR1, HLF, HOPX, HOXD11, MIR1203, MYL9, SLC9A3R2, SYT5, and VTRNA1-3. Our study demonstrated MeDIP-seq could be effectively used for cfDNA methylation profiling and identified a set of potential biomarker genes with clinical application for lung cancer.
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Project description:Aberrant DNA methylation is more prominent in proximal compared with distal colorectal cancers. Although a number of methylation markers were identified for colon cancer, yet few are available for rectal cancer.DNA methylation differences were assessed by a targeted DNA microarray for 360 marker candidates between 22 fresh frozen rectal tumour samples and 8 controls and validated by microfluidic high-throughput and methylation-sensitive qPCR in fresh frozen and formalin-fixed paraffin-embedded (FFPE) samples, respectively. The CpG island methylator phenotype (CIMP) was assessed by MethyLight in FFPE material from 78 patients with pT2 and pT3 rectal adenocarcinoma.We identified and confirmed two novel three-gene signatures in fresh frozen samples that can distinguish tumours from adjacent tissue as well as from blood with a high sensitivity and specificity of up to 1 and an AUC of 1. In addition, methylation of individual CIMP markers was associated with specific clinical parameters such as tumour stage, therapy or patients' age. Methylation of CDKN2A was a negative prognostic factor for overall survival of patients.The newly defined methylation markers will be suitable for early disease detection and monitoring of rectal cancer.
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Project description:Epigenetic changes, including CpG island hypermethylation, occur frequently in bladder cancer (BC) and may be exploited for BC detection and distinction between high-grade (HG) and low-grade (LG) disease. Genome-wide methylation analysis was performed using Agilent Human CpG Island Microarrays to determine epigenetic differences between LG and HG cases. Pathway enrichment analysis and functional annotation determined that the most frequently methylated pathways in HG BC were enriched for anterior/posterior pattern specification, embryonic skeletal system development, neuron fate commitment, DNA binding, and transcription factor activity. We identified 990 probes comprising a 32-gene panel that completely distinguished LG from HG based on methylation. Selected genes from this panel, EOMES, GP5, PAX6, TCF4, and ZSCAN12, were selected for quantitative polymerase chain reaction-based validation by MethyLight in an independent series (n=84) of normal bladder samples and LG and HG cases. GP5 and ZSCAN12, two novel methylated genes in BC, were significantly hypermethylated in HG versus LG BC (P?.03). We validated our data in a second independent cohort of LG and HG BC cases (n=42) from The Cancer Genome Atlas (TCGA). Probes representing our 32-gene panel were significantly differentially methylated in LG versus HG tumors (P?.04). These results indicate the ability to distinguish normal tissue from cancer, as well as LG from HG, based on methylation and reveal important pathways dysregulated in HG BC. Our findings were corroborated using publicly available data sets from TCGA. Ultimately, the creation of a methylation panel, including GP5 and ZSCAN12, able to distinguish between disease phenotypes will improve disease management and patient outcomes.
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Project description:Aberrant methylation of multiple promoter CpG islands could be related to the biology of ovarian tumors and its determination could help to improve treatment strategies. DNA methylation profiling was performed using the Methylation Ligation-dependent Macroarray (MLM), an array-based analysis. Promoter regions of 41 genes were analyzed in 102 ovarian tumors and 17 normal ovarian samples. An average of 29% of hypermethylated promoter genes was observed in normal ovarian tissues. This percentage increased slightly in serous, endometrioid, and mucinous carcinomas (32%, 34%, and 45%, respectively), but decreased in germ cell tumors (20%). Ovarian tumors had methylation profiles that were more heterogeneous than other epithelial cancers. Unsupervised hierarchical clustering identified four groups that are very close to the histological subtypes of ovarian tumors. Aberrant methylation of three genes (BRCA1, MGMT, and MLH1), playing important roles in the different DNA repair mechanisms, were dependent on the tumor subtype and represent powerful biomarkers for precision therapy. Furthermore, a promising relationship between hypermethylation of MGMT, OSMR, ESR1, and FOXL2 and overall survival was observed. Our study of DNA methylation profiling indicates that the different histotypes of ovarian cancer should be treated as separate diseases both clinically and in research for the development of targeted therapies.
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Project description:The aim of the present study was to identify potential biomarkers of hepatocellular carcinoma (HCC). Three gene expression profiles of GSE95698, GSE49515 and GSE76427 and a DNA methylation profile of GSE73003 were downloaded from the Gene Expression Omnibus (GEO) database, each comprising data regarding HCC and control tissue samples. The differentially expressed genes (DEGs) between the HCC group and the control group were identified using the limma software package. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the overlapping DEGs. The PPI network of the overlapping DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins. A total of 41 DEGs were identified in HCC the group compared with control group. The overlapping DEGs were enriched in 11 GO terms and 3 KEGG pathways. A total of 6,349 DMSs were identified, and 6 of the differentially expressed genes were also differentially methylated [Denticleless protein homolog (DTL), Dual specificity phosphatase 1 (DUSP1), Eomesodermin, Endothelial cell specific molecule 1, Nuclear factor ?-light-chain gene enhancer of activated B cells inhibitor, ? (NFKBIA) and suppressor of cytokine signaling 2 (SOCS2)]. The present study suggested that DTL, DUSP1, NFKBIA and SOCS2 may be potential biomarkers of HCC, and the tumor protein 'p53 signaling', 'forkhead box O1' signaling and 'metabolic' pathways may serve roles in the pathogenesis of HCC.
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