Thursday, March 14, 2013
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progression by measuring the evolution of mutational heterogeneity in cancer
Computational analysis of
patient whole-exome sequencing data could be used to measure the evolution of
tumor heterogeneity and help predict disease progression. Whole-exome
sequencing and subsequent computational analysis of 149 samples from patients
with chronic lymphocytic leukemia (CLL) identified more than 3,000 mutations
in total and quantified the prevalence of mutations in each cancer sample. In
12 matched patient samples taken before and after chemotherapy, sequence
analysis identified driver mutations that expanded in prevalence after
treatment and predicted poor survival. Next steps include determining whether
the presence of these driver mutations or the measurement of
chemotherapy-induced tumor evolution can predict patient outcomes in
prospective clinical trials.
Published online March 14, 2013
Patent applications filed;
available for licensing and freely available for academic and not-for-profit
Landau, D.A. et al. Cell;
published online Feb. 14, 2013;
Contact: Catherine J. Wu,
Dana-Farber Cancer Institute, Boston, Mass.
Contact: Gad Getz, Broad Institute of MIT and Harvard, Cambridge,
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