CollabRx, Affymetrix To Develop Analytical Tools For Integrated Clinical Cancer Panels
News Apr 16, 2014
CollabRx, Inc. and Affymetrix, Inc. today announced an agreement to optimize the use of CollabRx's Genetic Variant Annotation (GVA) Service™ in connection with Affymetrix' OncoScan™ FFPE Assay Kit and CytoScan® Cytogenetics Suite for analysis of gene copy number variation (CNV) in cancer research.
The overall objective of the partnership is to enable the GVA Service to accept and process gene CNV data directly from OncoScan assays and CytoScan assays to provide scientific knowledge for biomarker CNV profiles in cancer. This powerful informatics solution will pair data from various comprehensive genetic profiling studies, such as somatic mutations from next generation sequencing technologies, with copy number from the OncoScan assay for solid tumors or the CytoScan assay for liquid tumors, and result in a single user friendly report with relevant and dynamically updated knowledge.
"Recent data from The Cancer Genome Atlas (TCGA) has revealed the existence of copy number driven "C" class tumors, such as in breast, ovarian, and squamous cell lung cancers, and established the clinical relevance of several copy number amplifications and deletions. Our partnership with CollabRx will leverage our mutual commitment to provide easily accessible and authoritative informatics solutions to enable researchers to integrate copy number information with somatic mutation information in an automated and standardized way for comprehensive genetic profiling in cancer research," said Andy Last, Chief Operating Officer at Affymetrix. "CollabRx has developed a scalable technology platform that provides a dynamically updated knowledge base that is informed by leading cancer experts and is supported by published medical and scientific data. This capability is essential for clinical research laboratories who wish to fully support cancer research for optimal patient care."
The OncoScan assay and the CytoScan assay are highly sensitive assays for the detection of genome wide copy number changes in tumors. The OncoScan assay uses Molecular Inversion Probe (MIP) technology which interrogates only 40 base pairs of DNA, and is the only assay specifically optimized for the analysis of copy number in FFPE samples, which are the standard sample type for solid tumors. The CytoScan assay can be used to analyze copy number changes in hematological malignancies. Both assays have been widely used and published worldwide.
The GVA Service offered by CollabRx is a widely used, highly scalable, and cloud-based electronic decision support system that provides a turn-key analysis of many types of genetic alterations in cancer. The GVA Service accepts genetic data from any source or platform and pairs it with information contained in a knowledge base that includes the clinical impact of specific genetic profiles. The CollabRx knowledge base is supported by a proprietary technology platform and expert system that leverages a large and growing network of over 75 thought-leaders and clinical practitioners in the United States and Europe who are working together to develop new tools for clinical decision-making in oncology. The GVA Service is offered to customers in a Software as a Service (SaaS) business model.
"We are pleased to partner with Affymetrix, an industry-leading provider of genomic analysis systems that support translational research to advance routine care of cancer patients," said
Thomas Mika, chairman, president & CEO of CollabRx. "Enabling a seamless integration between Affymetrix CNV platforms and the CollabRx GVA Service will provide translational researchers with key insights into the clinical significance of integrated cancer panels. This partnership will both complement our commercial activities and help to advance the science and medicine in cancer research, a shared goal of both companies."
Note: Affymetrix products mentioned in this release are For Research Use Only. Not for use in diagnostic procedures.
Analytical Tool Predicts Disease-Causing GenesNews
Predicting genes that can cause disease due to the production of truncated or altered proteins that take on a new or different function, rather than those that lose their function, is now possible thanks to an international team of researchers that has developed a new analytical tool to effectively and efficiently predict such candidate genes.
Researchers Move Closer to Completely Optical Artificial Neural NetworkNews
Researchers have shown that it is possible to train artificial neural networks directly on an optical chip. The significant breakthrough demonstrates that an optical circuit can perform a critical function of an electronics-based artificial neural network and could lead to less expensive, faster and more energy efficient ways to perform complex tasks such as speech or image recognition.
Single Gene Change in Gut Bacteria Alters Host MetabolismNews
Scientists have found that deleting a single gene in a particular strain of gut bacteria causes changes in metabolism and reduced weight gain in mice. The research provides an important step towards understanding how the microbiome – the bacteria that live in our body – affects metabolism.READ MORE