Release of new Microarray for Research into Haematological and Solid Cancers

Laboratory products

Release of new Microarray for Research into Haematological and Solid Cancers

13 Jun, 2013

Published over 13 years ago. See the latest and most current information on Laboratory products.

Oxford Gene Technology (OGT) has released a new microarray to improve the accuracy and efficiency of cancer research. The CytoSure™ Cancer +SNP array (4x180k) combines long oligo array comparative genomic hybridisation (aCGH) probes with fully validated single nucleotide polymorphism (SNP) content, providing the superior detection of both copy number variations (CNVs) and loss of heterozygosity (LOH) on a single chip. The array has been optimised in collaboration with Professor Jacqueline Schoumans from the Lausanne University Hospital in Switzerland, an expert in both aCGH and cancer genomics. Unique to the proprietary CytoSure™ Cancer +SNP array, any reference sample can be used for analysis without changes to the standard aCGH protocol and, thanks to novel SNP probe chemistry, no restriction digest is required. The capacity to use matched samples is a particular advantage for research into genetic aberrations in cancer, enabling any constitutional abnormalities to be filtered out.  

Professor Schoumans commented: “The development of a new microarray with the capacity to detect both CNVs and LOH simultaneously was vital for improving the efficiency and quality of our research. By working very closely with the technical experts at OGT, we have constructed a new array that allows users to simultaneously screen a wide genomic background for CNVs and LOH, while also enabling in-depth CNV analysis on 1500 known cancer-associated genes.”

The 60-mer oligonucleotide probes utilised in the array provide a high signal-to-noise ratio and highly sensitive detection; this makes them ideal for research into complex malignant tissues. Thanks to OGT’s CytoSure Interpret Software, data analysis is rapid, reliable and simple to carry out, including updated features, such as the B-allele frequency plot, that have been optimised for the identification of biologically relevant genomic variants in tumour samples.

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