ACGH of Pancreatic Ductal Adenocarcinoma (PDAC) Cell Line and Xenografts
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Alan Shain
PROVIDER: E-GEOD-19852 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:PDAC tumor DNA hybridized against pooled normal genomic DNA
2011-01-11 | GSE19852 | GEO
Project description:Expression profiling of 70 Pancreatic Ductal Adenocarcinoma (PDAC) samples was performed on Agilent 44K expression arrays for cancer gene discovery. Additionally, matched aCGH on Agilent 244K arrays was performed. These two datasets were integrated in order to identify driver mutations leading to pancreatic cancer. Promising candidates were interrogated further using functional studies. 68 tumor samples (48 xenografts, 20 cell lines). 2 color arrays hybridized against a common reference pool of RNA from 11 cancer cell lines
2011-12-15 | E-GEOD-26088 | biostudies-arrayexpress
Project description:Array Comparative Genomic Hybridization (aCGH) of 70 pancreatic ductal adenocarcinoma (PDAC) samples was performed on Agilent 244K CGH arrays in order to find common genomic aberrations for cancer gene discovery. Additionally, matched expression profiling on Agilent 44K arrays was performed. Common copy number aberrations were identified in order to identify a list of putative cancer genes. Expression profiling data was used to further enrich this list of putative cancer genes for more likely candidates. Last, the most promising candidates were functionally interrogated using RNA interference-mediated knockdown to mimic loss. Well-known PDAC cancer genes were observed as amplified (KRAS and MYC) and deleted (CDKN2A, TGFBR2, SMAD4, and MAP2K4). 70 tumor samples (48 xenografts, 22 cell lines). 2-color arrays hybridized against a common reference pool of genomic DNA from 8 normal individuals. This dataset represents the aCGH component of the study.
2011-12-15 | E-GEOD-25273 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the following subset Series: GSE25273: Array Comparative Genomic Hybridization of Pancreatic Xenografts and Cell Lines GSE26088: Expression Profiling of Pancreatic Xenografts and Cell Lines Refer to individual Series
2011-12-15 | E-GEOD-26089 | biostudies-arrayexpress
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Project description:Pancreatic adenocarcinoma (PDAC) is one of the most lethal human malignancies and a major health problem. Patient-derived xenografts (PDX) are appearing as a prime approach for preclinical studies despite being insufficiently characterized as a model of the human disease and its diversity. We generated subcutaneous PDX from PDAC samples obtained either surgically or using diagnostic biopsies (endoscopic ultrasound guided fine needle aspirate). The extensive multiomics characterization of the xenografts demonstrated that PDX is a suitable model for preclinical studies, representing the diversity of the primary cancers. We generated subcutaneous PDX from PDAC samples obtained either surgically or using diagnostic biopsies (endoscopic ultrasound guided fine needle aspirate). The variable 'MultiOmicsClassification' indicates the resulting sample's group. 'CIMPclass' is the CpG island methylator phenotype as estimated from the methylation arrays analysis. In this dataset, Illumina Infinium HumanCode-24 BeadChips SNP arrays were used to analyze the DNA xenografts samples from pancreatic ductal adenocarcinoma.
2017-12-12 | E-MTAB-5006 | biostudies-arrayexpress
Project description:Pancreatic adenocarcinoma (PDAC) is one of the most lethal human malignancies and a major health problem. Patient-derived xenografts (PDX) are appearing as a prime approach for preclinical studies despite being insufficiently characterized as a model of the human disease and its diversity. We generated subcutaneous PDX from PDAC samples obtained either surgically or using diagnostic biopsies (endoscopic ultrasound guided fine needle aspirate). The extensive multiomics characterization of the xenografts demonstrated that PDX is a suitable model for preclinical studies, representing the diversity of the primary cancers. the variable MultiOmicsClassification indicates the resulting sample's group. Whole-genome DNA methylation was analyzed using the Illumina Infinium HumanMethylation450 Beadchips. Integragen SA (Evry, France) carried out microarray experiments and hybridized to the BeadChip arrays following the manufacturer’s instructions. Illumina GenomeStudio software was used to extract the beta value DNA methylation score for each locus. We removed data from probes that contained SNPs or overlapped with a repetitive element that was not uniquely aligned to the human genome or regions of insertions and deletions in the human genome. The CpG Island Methylator Phenotype (CIMP) index was determined using methylation Illumina Infinium HumanMethylation450 BeadChips based on previous low throughput work (Toyota, 1999). In brief, all island CpG found to be unmethylated (<20% Beta-value) in all 25 normal pancreatic samples from the ICGC consortium (Nones, 2014) were selected. The CIMP index was calculated independently for each sample as the proportion of methylated (>30% Beta-value) CpGs among the selected normally unmethylated island CpG.
2017-12-12 | E-MTAB-5008 | biostudies-arrayexpress
Project description:Background/Aims: Microarray-based comparative genomic hybridisation (CGH) has allowed high-resolution analysis of DNA copy number alterations across the entire cancer genome. Recent advances in bioinformatics tools enable us to perform a robust and highly sensitive analysis of array CGH data and facilitate the discovery of novel cancer-related genes. Methods: We analysed a total of 29 pancreatic ductal adenocarcinoma (PDAC) samples (six cell lines and 23 microdissected tissue specimens) using 1 Mb-spaced CGH arrays. The transcript levels of all genes within the identified regions of genetic alterations were then screened using our Pancreatic Expression Database. Results: In addition to 238 high-level amplifications and 35 homozygous deletions, we identified 315 minimal common regions of “non-random” genetic alterations (115 gains and 200 losses) which were consistently observed across our tumour samples. The small size of these aberrations (median size of 880 kb) contributed to the reduced number of candidate genes included (on average 12 Ensembl-annotated genes). The database has further specified the genes whose expression levels are consistent with their copy number status. Such genes were UQCRB, SQLE, DDEF1, SLA, ERICH1 and DLC1, indicating that these may be potential target candidates within regions of aberrations. Conclusion: This study has revealed multiple novel regions that may indicate the locations of oncogenes or tumour suppressor genes in PDAC. Using the database, we provide a list of novel target genes whose altered DNA copy numbers could lead to significant changes in transcript levels in PDAC. (Harada et al. Pancreatology) Keywords: pancreatic ductal adenocarcinima, tissue microdissection, array CGH, genetic alterations A panel of 23 microdissected PDAC tissues and 6 PDAC-derived cell lines were analysed using Sanger's CGH arrays with 1 Mb resolution. Clinical info of the samples used is provided as a supplementary file.
2008-12-16 | E-GEOD-9672 | biostudies-arrayexpress