User profiles for Marc J Williams
Marc J WilliamsMemorial Sloan Kettering Cancer Center Verified email at mskcc.org Cited by 2012 |
Identification of neutral tumor evolution across cancer types
Despite extraordinary efforts to profile cancer genomes, interpreting the vast amount of
genomic data in the light of cancer evolution remains challenging. Here we demonstrate that …
genomic data in the light of cancer evolution remains challenging. Here we demonstrate that …
Quantification of subclonal selection in cancer from bulk sequencing data
Subclonal architectures are prevalent across cancer types. However, the temporal evolutionary
dynamics that produce tumor subclones remain unknown. Here we measure clone …
dynamics that produce tumor subclones remain unknown. Here we measure clone …
Clonal fitness inferred from time-series modelling of single-cell cancer genomes
Progress in defining genomic fitness landscapes in cancer, especially those defined by copy
number alterations (CNAs), has been impeded by lack of time-series single-cell sampling of …
number alterations (CNAs), has been impeded by lack of time-series single-cell sampling of …
Evolutionary dynamics of neoantigens in growing tumors
Cancers accumulate mutations that lead to neoantigens, novel peptides that elicit an
immune response, and consequently undergo evolutionary selection. Here we establish how …
immune response, and consequently undergo evolutionary selection. Here we establish how …
[HTML][HTML] Ovarian cancer mutational processes drive site-specific immune evasion
High-grade serous ovarian cancer (HGSOC) is an archetypal cancer of genomic instability 1
, 2 , 3 – 4 patterned by distinct mutational processes 5 , 6 , tumour heterogeneity 7 , 8 – 9 …
, 2 , 3 – 4 patterned by distinct mutational processes 5 , 6 , tumour heterogeneity 7 , 8 – 9 …
[HTML][HTML] Single-cell genomic variation induced by mutational processes in cancer
How cell-to-cell copy number alterations that underpin genomic instability 1 in human
cancers drive genomic and phenotypic variation, and consequently the evolution of cancer 2 , …
cancers drive genomic and phenotypic variation, and consequently the evolution of cancer 2 , …
Subclonal reconstruction of tumors by using machine learning and population genetics
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 …
cancer subpopulations, as well as normal cells. Subclonal reconstruction methods based on …
Evolutionary history of human colitis-associated colorectal cancer
Objective IBD confers an increased lifetime risk of developing colorectal cancer (CRC), and
colitis-associated CRC (CA-CRC) is molecularly distinct from sporadic CRC (S-CRC). Here …
colitis-associated CRC (CA-CRC) is molecularly distinct from sporadic CRC (S-CRC). Here …
Measuring clonal evolution in cancer with genomics
MJ Williams, A Sottoriva… - Annual review of genomics …, 2019 - annualreviews.org
Cancers originate from somatic cells in the human body that have accumulated genetic
alterations. These mutations modify the phenotype of the cells, allowing them to escape the …
alterations. These mutations modify the phenotype of the cells, allowing them to escape the …
[HTML][HTML] Spatially constrained tumour growth affects the patterns of clonal selection and neutral drift in cancer genomic data
…, T Heide, B Werner, MJ Williams… - PLoS computational …, 2019 - journals.plos.org
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 …
in next-generation sequencing data is largely lacking. Here we use a spatial stochastic …