| Literature DB >> 25849130 |
Hyo-eun C Bhang1, David A Ruddy2, Viveksagar Krishnamurthy Radhakrishna1, Justina X Caushi1, Rui Zhao3, Matthew M Hims1, Angad P Singh1, Iris Kao2, Daniel Rakiec2, Pamela Shaw2, Marissa Balak2, Alina Raza1, Elizabeth Ackley2, Nicholas Keen1, Michael R Schlabach1, Michael Palmer2, Rebecca J Leary1, Derek Y Chiang1, William R Sellers1, Franziska Michor3, Vesselina G Cooke1, Joshua M Korn1, Frank Stegmeier1.
Abstract
Resistance to cancer therapies presents a significant clinical challenge. Recent studies have revealed intratumoral heterogeneity as a source of therapeutic resistance. However, it is unclear whether resistance is driven predominantly by pre-existing or de novo alterations, in part because of the resolution limits of next-generation sequencing. To address this, we developed a high-complexity barcode library, ClonTracer, which enables the high-resolution tracking of more than 1 million cancer cells under drug treatment. In two clinically relevant models, ClonTracer studies showed that the majority of resistant clones were part of small, pre-existing subpopulations that selectively escaped under therapeutic challenge. Moreover, the ClonTracer approach enabled quantitative assessment of the ability of combination treatments to suppress resistant clones. These findings suggest that resistant clones are present before treatment, which would make up-front therapeutic combinations that target non-overlapping resistance a preferred approach. Thus, ClonTracer barcoding may be a valuable tool for optimizing therapeutic regimens with the goal of curative combination therapies for cancer.Entities:
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Year: 2015 PMID: 25849130 DOI: 10.1038/nm.3841
Source DB: PubMed Journal: Nat Med ISSN: 1078-8956 Impact factor: 53.440