Project description:Renal tumors with complex morphology require extensive workup for accurate classification. Chromosomal aberrations that define subtypes of renal epithelial neoplasms have been reported. We explored if whole-genome chromosome copy number and loss-of-heterozygosity analysis with single nucleotide polymorphism (SNP) arrays can be used to identify these aberrations. Experiment Overall Design: We analyzed 20 paraffin-embedded tissues representing conventional renal cell carcinoma (RCC), papillary RCC, chromophobe RCC, and oncocytoma with Affymetrix GeneChip 10K 2.0 Mapping arrays.
Project description:We applied Illumina’s 317K high-density SNP-arrays to profile chromosomal aberrations in clear cell renal cell carcinoma (ccRCC) from 80 patients and analyzed the association of LOH/amplification events with clinicopathological characteristics
Project description:Renal tumors with complex morphology require extensive workup for accurate classification. Chromosomal aberrations that define subtypes of renal epithelial neoplasms have been reported. We explored if whole-genome chromosome copy number and loss-of-heterozygosity analysis with single nucleotide polymorphism (SNP) arrays can be used to identify these aberrations. Keywords: Chromosome copy number and LOH analysis with SNP Genotyping Arrays
Project description:Renal tumors with complex morphology require extensive workup for accurate classification. Chromosomal aberrations that define subtypes of renal epithelial neoplasms have been reported. We explored if whole-genome chromosome copy number and loss-of-heterozygosity analysis with single nucleotide polymorphism (SNP) arrays can be used to identify these aberrations in cases where morphology was unable to definitively classify these tumors. Experiment Overall Design: We analyzed 50 paraffin-embedded tissues representing tumors with classic morphology from clear cell renal cell carcinoma (RCC), papillary RCC, chromophobe RCC, and oncocytoma with Affymetrix GeneChip 10K 2.0 Mapping arrays. We then analyzed 25 tumors that could not be classified by morphology and classified them based on the presence of defining chromosomal anomalies identified in the "classic" cohort.
Project description:Renal tumors with complex morphology require extensive workup for accurate classification. Chromosomal aberrations that define subtypes of renal epithelial neoplasms have been reported. We explored if whole-genome chromosome copy number and loss-of-heterozygosity analysis with single nucleotide polymorphism (SNP) arrays can be used to identify these aberrations in cases where morphology was unable to definitively classify these tumors. Keywords: Chromosome copy number and LOH analysis (virtual karyotyping) with SNP Genotyping Arrays Keywords: Genome variation profiling by SNP array
Project description:To identify genetic alterations involved in the pathogenesis of PETs, we have analysed a total of 32 PET samples (29 tissue specimens and 3 cell lines) using high-resolution single nucleotide polymorphism (SNP) arrays. Keywords: comparative genomic hybridisation
Project description:Sex chromosomal abnormalities areare associated with multiple defects. In this study, we retrospectively analyzed the single nucleotide polymorphism (SNP) arrays of 186 early embryos with sex chromosomal abnormalities. using single nucleotide polymorphism (SNP) array. Among them, 52 cases of Turner syndrome, 21 cases of triple X syndrome, 35 cases of Klinefelter syndrome and 14 cases of XYY syndrome were detected. Moreover, 27 cases of mosaic sex chromosomal abnormalities were determined. Sex chromosomal deletions and duplications were found in 37 cases. Overall, our results presented a detailed manifestation of sex chromosomal abnormalities.
Project description:84 NSCLC cell lines were collected from various sources (Supplemental Table 1) and formed the basis for all subsequent experiments. Cell lines were derived from tumors representing all major subtypes of NSCLC tumors, including adenocarcinoma, squamous-cell carcinoma and large-cell carcinoma. The genomic landscape of these cell lines was characterized by analyzing gene copy number alterations using high-resolution single-nucleotide polymorphism (SNP) arrays (250K Sty1). We used the statistical algorithm Genomic Identification of Significant Targets in Cancer (GISTIC) to distinguish biologically relevant lesions from background noise. The application of GISTIC revealed 16 regions of recurrent, high-level copy number gain (inferred copy number > 2.14) and 20 regions of recurrent copy number loss (inferred copy number < 1.86)
