Browsing Clinical Studies by author "Graham, Trevor"
Now showing items 1-4 of 4
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Clinical trial designs for evaluating and exploiting cancer evolution.
Ingles Garces, AH; Porta, N; Graham, TA; Banerji, U (ELSEVIER SCI LTD, 2023-07-01)The evolution of drug-resistant cell subpopulations causes cancer treatment failure. Current preclinical evidence shows that it is possible to model herding of clonal evolution and collateral sensitivity where an initial ... -
Detecting repeated cancer evolution from multi-region tumor sequencing data.
Caravagna, G; Giarratano, Y; Ramazzotti, D; Tomlinson, I; Graham, TA; et al. (NATURE PUBLISHING GROUP, 2018-08-31)Recurrent successions of genomic changes, both within and between patients, reflect repeated evolutionary processes that are valuable for the anticipation of cancer progression. Multi-region sequencing allows the temporal ... -
Spatially constrained tumour growth affects the patterns of clonal selection and neutral drift in cancer genomic data.
Chkhaidze, K; Heide, T; Werner, B; Williams, MJ; Huang, W; et al. (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.
Caravagna, G; Heide, T; Williams, MJ; Zapata, L; Nichol, D; et al. (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 ...