Project description:This SuperSeries is composed of the following subset Series: GSE17768: An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer: gene expression GSE17769: An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer: DNA methylation GSE21347: An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer: allelic status GSE21540: An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer: CGH Refer to individual Series
Project description:An integrative multi-dimensional genetic and epigenetic strategy to identify aberrant genes and pathways in cancer: gene expression
Project description:Aberrant epigenetic regulation is a hallmark of acute myeloid leukemia (AML). Here, we investigated the molecular consequences of DNMT3B inhibition in KG1A cells, a model of immature AML, using an integrative multi-omics approach combining RNA-seq, Illumina EPIC DNA methylation arrays, ATAC-seq, and TMT-based quantitative proteomics.
Project description:One of the most fertile applications of next generation sequencing will be in the field of cancer genomics. Here, we report a high-throughput multi-dimensional sequencing study of primary non-small cell lung adenocarcinoma tumors and adjacent normal tissues of 6 never-smoker Korean female patients. Our data encompass results from exome-seq, RNA-seq, small RNA-seq, and MeDIP-seq. We identified and validated novel genetic aberrations including 47 somatic mutations and 20 fusion transcripts. We also characterized gene expression profiles which we sought to integrate with genomic aberrations and epigenetic regulations into functional networks. Importantly, among others the gene network module governing G2/M cell check point emerged as the primary source of disturbance in these patients. In addition, our study strongly suggests that microRNAs make key regulatory inputs into this gene network module. Our study offers a paradigm for integrative genomics analysis and proposes potential target pathways for the control of non-small cell lung adenocarcinoma. Study of primary non-small cell lung adenocarcinoma tumors and normal tissues of 6 patients.
Project description:One of the most fertile applications of next generation sequencing will be in the field of cancer genomics. Here, we report a high-throughput multi-dimensional sequencing study of primary non-small cell lung adenocarcinoma tumors and adjacent normal tissues of 6 never-smoker Korean female patients. Our data encompass results from exome-seq, RNA-seq, small RNA-seq, and MeDIP-seq. We identified and validated novel genetic aberrations including 47 somatic mutations and 20 fusion transcripts. We also characterized gene expression profiles which we sought to integrate with genomic aberrations and epigenetic regulations into functional networks. Importantly, among others the gene network module governing G2/M cell check point emerged as the primary source of disturbance in these patients. In addition, our study strongly suggests that microRNAs make key regulatory inputs into this gene network module. Our study offers a paradigm for integrative genomics analysis and proposes potential target pathways for the control of non-small cell lung adenocarcinoma. Study of primary non-small cell lung adenocarcinoma tumors and normal tissues of 6 patients.
Project description:Genome-wide expression and methylation profiling identifies novel targets with aberrant hypermethylation and reduced expression in low-risk myelodysplastic syndromes (MDSs). Gene expression profiling signatures may be used to classify the subtypes of Myelodysplastic syndrome (MDS) patients. However, there are few reports on the global methylation status in MDS. The integration of genome-wide epigenetic regulatory marks with gene expression levels would provide additional information regarding the biological differences between MDS and healthy controls. Gene expression and methylation status were measured using high-density microarrays. A total of 552 differentially methylated CpG loci were identified as being present in low-risk MDS; hypermethylated genes were more frequent than hypomethylated genes. In addition, mRNA expression profiling identified 1005 genes that significantly differed between low-risk MDS and the control group. Integrative analysis of the epigenetic and expression profiles revealed that 66.7% of the hypermethylated genes were underexpressed in low-risk MDS cases. Gene network analysis revealed molecular mechanisms associated with the low-risk MDS group, including altered apoptosis pathways. The two key apoptotic genes BCL2 and ETS1 were identified as silenced genes. In addition, the immune response and micro RNA biogenesis were affected by the hypermethylation and underexpression of IL27RA and DICER1. Our integrative analysis revealed that aberrant epigenetic regulation is a hallmark of low-risk MDS patients and could have a central role in these diseases. Low-risk MDS patients and age-matched controls without haematological malignancies were included in the study. Mononuclear cells were isolated from bone marrow samples of low-risk MDS patients and controls by density gradient (Ficoll). A cohort of 18 patients with low-risk MDS and seven controls were included in a simultaneous integrative study of methylation and expression, while the whole series was used as a control group of expression data.
Project description:<p>Systemic lupus erythematosus (SLE) is a complex autoimmune disease that affects multiple organ systems and varies in severity across different populations. To examine the clinical heterogeneity of SLE, we sought to identify different lupus subtypes within our multi-ethnic cohort using a clustering approach. Additionally, with genome-wide methylation and genotype data generated for our cohort, we applied integrative methods to investigate genetic and epigenetic risk factors. This integrative and computational approach revealed molecular differences associated with phenotypic clusters. </p>