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Reply to 'Neutral tumor evolution?'
(2018-12)
Quantification of subclonal selection in cancer from bulk sequencing data.
(NATURE PUBLISHING GROUP, 2018-05-28)
Subclonal architectures are prevalent across cancer types. However, the temporal evolutionary dynamics that produce tumor subclones remain unknown. Here we measure clone dynamics in human cancers by using computational ...
Spatially constrained tumour growth affects the patterns of clonal selection and neutral drift in cancer genomic data.
(PUBLIC LIBRARY SCIENCE, 2019-07-29)
Quantification of the effect of spatial tumour sampling on the patterns of mutations detected in next-generation sequencing data is largely lacking. Here we use a spatial stochastic cellular automaton model of tumour growth ...
Subclonal reconstruction of tumors by using machine learning and population genetics.
(NATURE PUBLISHING GROUP, 2020-09-01)
Most cancer genomic data are generated from bulk samples composed of mixtures of cancer subpopulations, as well as normal cells. Subclonal reconstruction methods based on machine learning aim to separate those subpopulations ...
Mapping the breast cancer metastatic cascade onto ctDNA using genetic and epigenetic clonal tracking.
(NATURE PORTFOLIO, 2020-03-27)
Circulating tumour DNA (ctDNA) allows tracking of the evolution of human cancers at high resolution, overcoming many limitations of tissue biopsies. However, exploiting ctDNA to determine how a patient's cancer is evolving ...
Longitudinal Liquid Biopsy and Mathematical Modeling of Clonal Evolution Forecast Time to Treatment Failure in the PROSPECT-C Phase II Colorectal Cancer Clinical Trial.
(AMER ASSOC CANCER RESEARCH, 2018-08-30)
Sequential profiling of plasma cell-free DNA (cfDNA) holds immense promise for early detection of patient progression. However, how to exploit the predictive power of cfDNA as a liquid biopsy in the clinic remains unclear. ...
Robust RNA-based in situ mutation detection delineates colorectal cancer subclonal evolution.
(NATURE PUBLISHING GROUP, 2017-12-08)
Intra-tumor heterogeneity (ITH) is a major underlying cause of therapy resistance and disease recurrence, and is a read-out of tumor growth. Current genetic ITH analysis methods do not preserve spatial context and may not ...