Project description:Cytogenetic profiles of 50 meningiomas using high-density GeneChip Mapping 500K set and Genome-Wide Human SNP 6.0 Array in the tumor tissues and in the peripheral blood of the same patients. A total of two hundred 500k arrays (100 tumor samples and 100 blood samples) and 14 SNP6.0 arrays (7 tumour samples and 7 peripheral blood samples) were studied to explore the most common recurrent chromosomal abnormalities (gains and losses) in meningiomas. Our results confirm that del(22q) (52%) and del(1p) (16%) (common deleted regions: 22q11.21-22q13.3. and 1p31.2-p36.33) are the most frequent abnormalities. Additionally, recurrent monosomy 14 (8%), del(6p) (10%), del(7p) (10%) and del(19p) (6%) were also observed, while copy number variation (CNV) patterns consistent with recurrent chromosome gains, gene amplification was absent or rare. Based on their overall SNP profiles meningiomas could be classified into: i) diploid cases, ii) meningiomas with a single chromosome change (e.g. monosomy 22/del(22q) and iii) tumours with M-bM-^IM-%2 altered chromosomes. 500K SNP mapping set array and Genome-Wide Human SNP 6.0 Array were used to profile 50 meningiomas with matched blood DNA samples. Loss of heterozygosity (LOH) and copy number abnormality (CNA) profiles were derived from each tumour-blood pair. In seven tumors, both types of arrays were assessed.
Project description:Copy number profiling of 36 ovarian tumors on Affymetrix 100K SNP arrays Thirty-six ovarian tumors were profiled for copy-number alterations with the Affymetrix 100K Mapping Array. Copy number profiling of 36 ovarian tumors on Affymetrix 500K SNP arrays Sixteen ovary tumors were profiled for copy-number alterations with the high-resolution Affymetrix 500K Mapping Array.
Project description:Cytogenetic profiles of 50 meningiomas using high-density GeneChip Mapping 500K set and Genome-Wide Human SNP 6.0 Array in the tumor tissues and in the peripheral blood of the same patients. A total of two hundred 500k arrays (100 tumor samples and 100 blood samples) and 14 SNP6.0 arrays (7 tumour samples and 7 peripheral blood samples) were studied to explore the most common recurrent chromosomal abnormalities (gains and losses) in meningiomas. Our results confirm that del(22q) (52%) and del(1p) (16%) (common deleted regions: 22q11.21-22q13.3. and 1p31.2-p36.33) are the most frequent abnormalities. Additionally, recurrent monosomy 14 (8%), del(6p) (10%), del(7p) (10%) and del(19p) (6%) were also observed, while copy number variation (CNV) patterns consistent with recurrent chromosome gains, gene amplification was absent or rare. Based on their overall SNP profiles meningiomas could be classified into: i) diploid cases, ii) meningiomas with a single chromosome change (e.g. monosomy 22/del(22q) and iii) tumours with ≥2 altered chromosomes.
Project description:Development of a clinically relevant animal models of RCC for preclinical investigations. For DNA copy number analysis, the Sty I (250K) SNP array of the 500K Human Mapping Array (Affymetrix) was used. Arrays were scanned by GeneChip Scanner 3000 7G. Probe-level signal intensities were normalized to a baseline array with median intensity using invariant set normalization and SNP-level signal intensities were obtained using a model-based (PM/MM) method. Keywords: SNP array data, renal cell carcinoma
Project description:Chromosomal abnormalities have been identified in some individuals with Autism Spectrum Disorder (ASD), but their full etiologic role is unknown. Submicroscopic copy number variation (CNV) represents a considerable source of genetic variation in the human genome that contributes to phenotypic differences and disease susceptibility. To explore the contribution CNV imbalances in ASD, we genotyped unrelated ASD index cases using the Affymetrix GeneChip® 500K single nucleotide polymorphism (SNP) mapping array. Keywords: Whole Genome Mapping SNP Genotyping Array
Project description:sPNETs are highly malignant embryonal brain tumours of poor prognosis. The underlying biology is poorly understood. To address this we therefore performed high resolution genetic analysis. 36 CNS PNETs and 8 PBs were analysed using the Affymetrix 100K and 500K Mapping Set to identify copy number imbalance at both the chromosome and gene level. Keywords: Affymetrix 100K SNP array, Affymetrix 500K SNP arrays
Project description:Copy number profiling of 36 ovarian tumors on Affymetrix 100K SNP arrays Thirty-six ovarian tumors were profiled for copy-number alterations with the Affymetrix 100K Mapping Array. Copy number profiling of 36 ovarian tumors on Affymetrix 500K SNP arrays Sixteen ovary tumors were profiled for copy-number alterations with the high-resolution Affymetrix 500K Mapping Array. Affymetrix 100K Mapping Array intensity signal CEL files were processed by dChip 2005 (Build date Nov 30, 2005) using the PM/MM difference model and invariant set normalization. Each probe set was mapped to the genome, NCBI assembly version 36, using annotation provided by the Affymetrix web site. The log2 ratios were centered to a median of zero and segmented using the GLAD package for the R statistical environment. Copy number was calculated as power(2,log2ratio + 1). Affymetrix 500K Mapping Array intensity signal CEL files were processed by dChip 2005 (Build date Nov 30, 2005) using the PM/MM difference model and invariant set normalization. Forty-eight normal samples were downloaded from the Affymetrix website (http://www.affymetrix.com/support/technical/byproduct.affx?product=500k) and analyzed at the same time. One CEL file for each set (Sty and Nsp) with the median signal intensity across the set was selected as the reference array. The dChip-normalized signal intensities were converted to log2 ratios and segmented as follows. For each autosomal probe set, the log2 tumor/normal ratio of each tumor sample was calculated using the average intensity for each probe set in the normal set. For Chromosome X, the average of the 20 normal female samples was used. Each probe set was mapped to the genome, NCBI assembly version 36, using annotation provided by the Affymetrix web site. The log2 ratios were centered to a median of zero and segmented using the GLAD package for the R statistical environment. Copy number was calculated as power(2,log2ratio + 1).
Project description:Clinical laboratories are adopting array comparative genomic hybridization (AGH) as a standard clinical test. A number of whole genome AGH systems are available, but little is known about the comparative performance in a clinical context. We prospectively studied 30 children with idiopathic MR and both unaffected parents of each child using Affymetrix 500K GeneChip SNP arrays, Agilent Human Genome 244K oligonucleotide arrays and NimbleGen 385K Whole-Genome oligonucleotide arrays. We determined whether CNVs called on these platforms were detected by Illumina Hap550 beadchips or SMRT 32K BAC whole genome tiling arrays and tested 15 of the 30 trios on Affymetrix 6.0 SNP array. The Affymetrix 500K, Agilent and NimbleGen platforms identified 3061 autosomal and 117 X chromosome CNVs in 30 trios. 147 of these CNVs were de novo, but only 33 (22%) of the de novo CNVs were found on more than one platform. Performing genotype-phenotype correlations, we identified 7 pathogenic and 4 possibly pathogenic CNVs for MR. All 11 of these CNVs were detected by both the Agilent and NimbleGen arrays, 9 by the Affymetrix 500K and Illumina beadchips, and 5 by the SMRT BAC array. Two of the 4 pathogenic or possibly pathogenic CNVs present in the trios tested with the Affymetrix 6.0 array were identified. Our findings demonstrate that different results are obtained with different AGH platforms and illustrate the trade-off that exists between sensitivity and specificity. The large number of apparently false positive CNV calls supports the need for validating clinically important findings with a different methodology.
Project description:Clinical laboratories are adopting array comparative genomic hybridization (AGH) as a standard clinical test. A number of whole genome AGH systems are available, but little is known about the comparative performance in a clinical context. We prospectively studied 30 children with idiopathic MR and both unaffected parents of each child using Affymetrix 500K GeneChip SNP arrays, Agilent Human Genome 244K oligonucleotide arrays and NimbleGen 385K Whole-Genome oligonucleotide arrays. We determined whether CNVs called on these platforms were detected by Illumina Hap550 beadchips or SMRT 32K BAC whole genome tiling arrays and tested 15 of the 30 trios on Affymetrix 6.0 SNP array. The Affymetrix 500K, Agilent and NimbleGen platforms identified 3061 autosomal and 117 X chromosome CNVs in 30 trios. 147 of these CNVs were de novo, but only 33 (22%) of the de novo CNVs were found on more than one platform. Performing genotype-phenotype correlations, we identified 7 pathogenic and 4 possibly pathogenic CNVs for MR. All 11 of these CNVs were detected by both the Agilent and NimbleGen arrays, 9 by the Affymetrix 500K and Illumina beadchips, and 5 by the SMRT BAC array. Two of the 4 pathogenic or possibly pathogenic CNVs present in the trios tested with the Affymetrix 6.0 array were identified. Our findings demonstrate that different results are obtained with different AGH platforms and illustrate the trade-off that exists between sensitivity and specificity. The large number of apparently false positive CNV calls supports the need for validating clinically important findings with a different methodology.