Choosing the best treatment for a cancer patient is often an inexact science. Drugs that work well for some patients may not help others, and tumors that are initially susceptible to a drug can later become resistant. In a new approach to devising more personalized treatments, researchers at MIT and the Dana-Farber Cancer Institute have developed a novel way to test tumors for drug susceptibility. Using a device that measures the masses of single cells, the scientists can predict whether a particular drug will kill tumor cells, based on how it affects their growth rates. The researchers successfully tested this approach with a very aggressive type of brain cancer called glioblastoma and a type of blood cancer known as acute lymphoblastic leukemia. They reported their results in an article published online on October 10, 2016 in Nature Biotechnology. The article is titled “Drug Sensitivity of Single Cancer Cells Is Predicted by Changes in Mass Accumulation Rate.” “We’ve developed a functional assay that can measure drug response of individual cells while maintaining viability for downstream analysis such as sequencing,” says Scott Manalis, Ph.D., the Andrew (1956) and Erna Viterbi Professor in the MIT Departments of Biological Engineering and Mechanical Engineering and a member of MIT’s Koch Institute for Integrative Cancer Research, who is one of the paper’s senior authors. David Weinstock, Ph.D., and Keith Ligon, Ph.D., of Dana-Farber Cancer Institute are also senior authors of the paper. The lead authors are Mark Stevens, Ph.D., a former MIT graduate student who is now a research scientist at Dana-Farber; MIT graduate student Nigel Chou; and Dana-Farber postdocs Cecile Maire and Mark Murakami.
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