Chromatin organization is a major influence on regional mutation rates in human cancer cells
By Benjamin Schuster-Böckler, Ben Lehner. Nature, 2012
646 citations recorded by the source corpus.
Subfields: Cancer Research, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/3e79cf7526d894e6c19d04ceb674d30655b8c597
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cancer Research
- Gad Getz
- Bert Vogelstein
- Eric S. Lander
- Matthew Meyerson
- Kenneth W. Kinzler
- Kristian Cibulskis
- M. Lawrence
- A. Bardelli
In Molecular Biology
- Eric S. Lander
- Gad Getz
- Matthew Meyerson
- Bert Vogelstein
- Kenneth W. Kinzler
- Levi A. Garraway
- Stacey Gabriel
- William Pao
Citations in the corpus
- Whole Genome Sequencing in Autism Identifies Hotspots for De Novo Germline Mutation (2012, positive): “, 2012) and cancer (Schuster-Böckler and Lehner, 2012) is also influenced by aspects of chromatin structure, consistent with partially overlappingmutational mechanisms acting in germ cells and somatic cells.”
- Evaluating the evaluation of cancer driver genes (2016, background): “perhaps by a variety of factors that have yet to be discovered (4, 18, 19).”
- Mapping and elucidating the function of modified bases in DNA (2017, background): “16 that occur, such that the mutation rate variation is linked to the epigenomic features of the cell of origin.(95,96,97)”
- Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing (2012, result): “This observation is consistent with reports of regional mutation rates correlated with density of H3K9 chromatin marks across cancers (Schuster-Böckler and Lehner, 2012) and with gene expression in multiple myeloma (Chapman et al.”
- Tissue-specific mutation accumulation in human adult stem cells during life (2016, neutral): “3a), similar to patterns previously observed in cancer 15 .”
- Universal Patterns of Selection in Cancer and Somatic Tissues (2018, neutral): “…a statistical model ( dNdScv ) that combines the local observed synonymous mutation rate with a regression model using covariates that predict the variable mutation rate across the genome (Lawrence et al., 2013; Polak et al., 2015; Schuster-Bockler and Lehner, 2012) (Supplementary Methods S1.”