Ontology highlight
ABSTRACT:
REPOSITORIES: ENA
Similar Datasets
Project description:Genome wide DNA methylation profiling of normal kidney (n=36), nephrogenic rest (n=22) and Wilms tumour (n=37) was performed using the Illumina 450k array. Two papers were composed after analysis of this data (1) describes comparative analysis of 22 matched normal kidney-Wilms tumour pairs which identified biomarker differentially methylated regions (DMRs) that could be detected in patient blood; (2) describes comparative analysis of 20 matched trios which identified changes in methylation associated with progression from the precursor lesion towards tumourigenesis.
2014-07-08 | GSE59157 | GEO
Project description:To identify the novel tumor suppressors in hepatocellular carcinoma (HCC), we have employed whole genome microarray expression profiling as a discovery platform in HCC and paired normal liver tissues to identify genes which down-regulated in HCC. Among which, INTS6 and its pseudogene, namely INTS6P1, were found to be dramatically down-regulated in HCC. The down-regulated expression of INTS6 and INTS6P1 in HCC was further confirmed by real-time PCR. RNA was extracted from 3 pairs of HCC and normal liver tissue harvested from patients to undergo microarray study.
2015-01-03 | E-GEOD-64632 | biostudies-arrayexpress
Project description:To identify the novel tumor suppressors in hepatocellular carcinoma (HCC), we have employed whole genome microarray expression profiling as a discovery platform in HCC and paired normal liver tissues to identify genes which down-regulated in HCC. Among which, INTS6 and its pseudogene, namely INTS6P1, were found to be dramatically down-regulated in HCC. The down-regulated expression of INTS6 and INTS6P1 in HCC was further confirmed by real-time PCR. RNA was extracted from 3 pairs of HCC and normal liver tissue harvested from patients to undergo microarray study.
2015-01-03 | E-GEOD-64631 | biostudies-arrayexpress
Project description:Hepatocellular carcinoma (HCC) is the most common malignancy of the liver. Genomic analysis is conducted to identify genetic alterations in driver genes which are all druggable targets for cancer therapy.
Whole genome shotgun sequencing (WGS) and the landscaple of somatic mutations in 88 paired samples from HCC patients including tumors and matched adjacent normal tissues using Illumina HiSeq 2000 platform were performed.
| EGAS00001002218 | EGA
Project description:Chronic infections by hepatitis B virus (HBV) and hepatitis C virus (HCV) appear to be the most significant causes of hepatocellular carcinoma (HCC). Aberrant promoter methylation is known to be deeply involved in cancer, including HCC. In this study, we analyzed aberrant promoter methylation on genome-wide scale in 6 HCCs including 3 HBV-related and 3 HCV-related HCCs, 6 matched noncancerous liver tissues and 3 normal liver tissues by methylated DNA immunoprecipitation-on-chip analysis. Candidate genes with promoter methylation were detected more frequently in HCV-related HCC. Candidate genes methylated preferentially to HBV-related or HCV-related HCCs were detected and selected, and methylation levels of the selected genes were validated using 125 liver tissue samples, including 61 HCCs (28 HBV-related HCCs and 33 HCV-related HCCs) and matched 59 matched noncancerous livers, and 5 normal livers, by quantitative methylation analysis using MALDI-TOF mass spectrometry. Among analyzed genes, preferential methylation in HBV-related HCC was validated in 1 gene only. However, 15 genes were found methylated preferentially in HCV-related HCC, which was independent from age. Hierarchical clustering of HCC using these 15 genes stratified HCV-related HCC as a cluster of frequently methylated samples. The 15 genes included genes inhibitory to cancer-related signaling such as RAS/RAF/ERK and Wnt/b-catenin pathways. It was indicated that genes methylated preferentially in HCV-related HCC exist, and it was suggested that DNA methylation might play an important role in HCV-related HCC by silencing cancer-related pathway inhibitors. we analyzed aberrant promoter methylation in 6 HCC clinical samples (including 3 HBV-related HCCs and 3 HCV-related HCCs) and their matched noncancerous tissues on genome-wide scale by the method. Candidate regions of promoter methylation preferentially to HBV-related HCC and HCV-related HCC were selected, and the methylation levels of these genes were measured quantitatively using MALDI-TOF mass spectrometry. Expression levels of these 6 pairs of HCC and 4 more pairs of HCCs and surrounding noncancerous tissues were analyzed by expression array and are reported in this Series. <br><br>This experiment was reloaded in November 2010 after additional curation. this dataset is part of the TransQST collection.
2010-07-06 | E-GEOD-19665 | biostudies-arrayexpress
Project description:Genome wide DNA methylation profiling of normal kidney (n=36), nephrogenic rest (n=22) and Wilms tumour (n=37) was performed using the Illumina 450k array. Two papers were composed after analysis of this data (1) describes comparative analysis of 22 matched normal kidney-Wilms tumour pairs which identified biomarker differentially methylated regions (DMRs) that could be detected in patient blood; (2) describes comparative analysis of 20 matched trios which identified changes in methylation associated with progression from the precursor lesion towards tumourigenesis. Bisulfte converted DNA from 95 samples of normal kidney, nephrogenic rest and Wilms tumour was hybridised to Illumina HumanMethylation450 bead chips.
2014-07-08 | E-GEOD-59157 | biostudies-arrayexpress
Project description:Whole genome sequencing (WGS) from snap-frozen oesophageal tumour tissue and germline nucleic acids isolated from peripheral blood mononuclear cells (PBMC) was performed as part of the International Cancer Genome Consortium project and OCCAMS consortium (1,2). Filtered read sequences were mapped to the human reference genome (GRCh37) using Burrows-Wheeler Alignment (BWA). In the matched tumour/germline samples, somatic acquired mutation identification was performed using a Bayesian algorithm implemented in the tool Seurat (3). Functional annotation of identified somatic mutations was performed with the tool SnpEff (4). CNV detection was performed with the tool Control-FREEC (5) 1) Weaver, J. M. et al. Ordering of mutations in preinvasive disease stages of esophageal carcinogenesis. Nat.Genet. 46, 837-843 (2014). 2) Weaver, J. M., Ross-Innes, C. S. & Fitzgerald, R. C. The '-omics' revolution and oesophageal adenocarcinoma. Nature reviews. Gastroenterology & hepatology 11, 19-27 (2014) 3) Christoforides, A. et al. Identification of somatic mutations in cancer through Bayesian-based analysis of sequenced genome pairs. BMC.Genomics 14, 302 (2013). 4) Cingolani, P. et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly.(Austin.) 6, 80-92 (2012). 5) Boeva V, Popova T, Bleakley K, Chiche P, Cappo J, Schleiermacher G, Janoueix-Lerosey I, Delattre O, Barillot E. (2011) Control-FREEC: a tool for assessing copy number and allelic content using next generation sequencing data. Bioinformatics. 2011 Dec 6
2016-09-09 | E-MTAB-4600 | biostudies-arrayexpress
Project description:Whole genome sequencing on Illumina X10 machines of up to 100 Adult ALL matched normal-tumour pairs
| EGAS00001002474 | EGA
Project description:Whole genome sequencing for tumour/normal matched pairs from 78 samples
| EGAD00001011343 | EGA