New Technique Improves Breast and Ovarian Cancer Diagnostics
(3BL Media/Justmeans) - Demand for genetic testing to diagnose breast and ovarian cancer has increased as the causal link between mutations in BRCA1 and BRCA2 has been recognized. However, identifying mutations in these large genes by conventional methods can be time-consuming and expensive. A new technique using second-generation sequencing technology that is as sensitive as the standard methodology could improve the efficiency and productivity of genetic testing laboratories. The method is described in the November issue of The Journal of Molecular Diagnostics.
Next-generation sequencing (NGS) refers to technologies that share the ability to parallel sequence millions of DNA templates. The terms second-generation (and third-generation) sequencing are used to describe the evolution of sequencing technology from the first-generation, dideoxy ‘Sanger’ sequencing. These new DNA sequencing technologies are expected to have a significant impact on the detection, management, and treatment of genetic diseases such as ovarian and breast cancer.
“In our laboratory, approximately 25% of high risk patients who undergo BRCA1 or BRCA2 testing will generate a result with a real or ambiguous relationship to hereditary cancer risk, and so testing for these mutations is an important tool to identify individuals who would benefit from preventative surgery or increased breast cancer surveillance,” says lead investigator Aly Karsan, MD, of the Genome Sciences Centre and Department of Pathology of the BC Cancer Agency.
Dr. Karsan says he expects demand to rise (currently his institution currently receives over 500 requests annually) as public awareness broadens, especially following the recently publicized medical case of high-profile patient Angelina Jolie. Fueling the demand will be the identification of additional suspect genes and discovery of genetic factors predictive of response to new therapies. As a result, there is a need for faster and low-cost testing with additional analytic capabilities.
Image credit: Elsevier