The REMBRANDT study – a large collection of genomic data from brain cancer patients [SNP]

The Rembrandt brain cancer dataset and includes clinical and biospecimen data from this study for 671 patients collected from 14 contributing institutions in 2005. Such combined datasets would provide researchers with a unique opportunity to conduct integrative analysis of gene expression and copy number changes alongside clinical outcomes this large brain cancer study. In 2015, the NCI retired the REMBRANDT data portal, and all molecular data including microarray gene expression, copy number, and clinical data, was migrated to the Georgetown Database of Cancer (G-DOC). The G-DOC platform can be accessed at: https://gdoc.georgetown.edu. G-DOC is a data integration platform that offers advanced computational tools to handle a variety of biomedical BIG DATA including gene expression arrays, NGS and medical images so that they can be analyzed in the full context of other omics and clinical information. After migration of the REMBRANDT dataset into G-DOC, we applied our novel algorithm for copy number data analysis called Chromosomal Instability Index (CINdex), published as an open source Bioconductor package . This submission includes the copy number data, processed on two Affymetrix 50K copy number arrays and gene expression data processed on the Affymetrix U133 Plus 2 array. It also includes the Chromsome and Cytoband CINdex matrices. Tissue (Approximately 10 μg from each tumor) was used to extract high molecular weight, genomic DNA using QIAamp DNA Micro DNA extraction kit (Qiagen) following the manufacturer's instructions. The quality of DNA was checked by electrophoresis run in a 2% agarose gel. Genomic DNA (250 ng) from samples received were hybridized to Affymetrix 100K single nucleotide polymorphism (SNP) chips, which covers 116,204 single nucleotide polymorphism loci in the human genome with a mean intermarker distance of 23.6 kb. The 100K arrays were a set of 2 chips, 50K each, designed for different restriction enzyme - XbaI and HindIII. These arrays were processed separately and looked for their concordance. It give two simultaneous data type outputs: allelic calls and signal intensity, allowing for the determination of both copy number alterations and regions of allelic imbalances (loss of heterozygosity). Calls were determined by the GTYPE software version 3.0 with 25% level of confidence. The CINdex package uses the segment level data (obtained from the CN4.cnchp files) to calculate the genomic instability in terms of copy number gains and losses separately at the chromosome and cytoband level. The genomic instability across a chromosome offers a global view (referred to asChromosome CIN), and the genomic instability across cytobands regions provides higher resolution (referred to as Cytobands CIN) view of instability. This allows assessing the impacts of copy number alternations on various biological events or clinical outcomes by studying the association of CIN indices with those events. The CINdex algorithm was applied on both the XbaI and HindIII Rembrandt copy number arrays. >>>CEL files are available only for 16 samples due to a corrupted archive. All samples contain processed data as either .CHP or CNCHP files.<<<