Genome-Wide Pattern Found in Tumors from Brain Cancer Patients Predicts Life Expectancy; Proof-of-Principle Study Highlights Mathematical Methods That Are Uniquely Suited for Personalized Medicine

For the past 70 years, the best indicator of life expectancy for a patient with glioblastoma (GBM)--the most common and the most aggressive brain cancer--has simply been age at diagnosis. Now, an international team of scientists has experimentally validated a predictor that is not only more accurate, but also more clinically relevant: a pattern of co-occurring changes in DNA abundance levels, or copy numbers, at hundreds of thousands of sites across the whole tumor genome. Patients with the genome-wide pattern survive for a median of one year. However, patients without it survive three times as long, for a median of three years. The results came from a retrospective clinical trial that was published online on May 15, 2020 in Applied Physics Letters (APL) Bioengineering (https://aip.scitation.org/doi/10.1063/1.5142559). The open-access article is titled “Retrospective Clinical Trial Experimentally Validates Glioblastoma Genome-Wide Pattern of DNA Copy-Number Alterations Predictor of Survival.” Having a predictor of a patient's life expectancy can help inform medical decisions. The GBM pattern can, in principle, be used in this way today. For example, when a patient has magnetic resonance imaging results that are inconclusive, such information can help doctors decide whether to perform an intervention. "The information contained in this pattern, and other patterns that we can discover by using the same mathematical methods, can improve the standard of care of GBM and other diseases," said the team leader Orly Alter (photo), PhD, Utah Science, Technology, and Research (USTAR) Associate Professor of Bioengineering and Human Genetics at the Scientific Computing and Imaging Institute and the Huntsman Cancer Institute at the University of Utah.
Login Or Register To Read Full Story