TY - GEN
T1 - De Novo Discovery of Mutated Driver Pathways in Cancer
AU - Vandin, Fabio
AU - Upfal, Eli
AU - Raphael, Benjamin J.
N1 - Publisher Copyright:
© 2011, Springer-Verlag Berlin Heidelberg.
PY - 2011
Y1 - 2011
N2 - Next-generation DNA sequencing technologies are enabling genome-wide measurements of somatic mutations in large numbers of cancer patients. A major challenge in interpretation of this data is to distinguish functional driver mutations that are important for cancer development from random, passenger mutations. A common approach to identify driver mutations is to find genes that are mutated at significant frequency in a large cohort of cancer genomes. This approach is confounded by the observation that driver mutations target multiple cellular signaling and regulatory pathways. Thus, each cancer patient may exhibit a different combination of mutations that are sufficient to perturb the necessary pathways. However, the current understanding of the somatic mutational process of cancer [3,5,6] places two additional constraints on the expected patterns of somatic mutations in a cancer pathway. First, an important cancer pathway should be perturbed in a large number of patients. Thus we expect that with genome-wide measurements of somatic mutations a driver pathway will exhibit high coverage, where most patients will have a mutation in some gene in the pathway. Second, since driver mutations are relatively rare and typically a single driver mutation is sufficient to perturb a pathway, a reasonable assumption is that most patients have a single driver mutation in a pathway. Thus, the genes in a driver pathway exhibit a pattern of mutually exclusive driver mutations, where driver mutations are observed in exactly one gene in the pathway in each patient. There are numerous examples of sets of mutually exclusive mutations [5,6].
AB - Next-generation DNA sequencing technologies are enabling genome-wide measurements of somatic mutations in large numbers of cancer patients. A major challenge in interpretation of this data is to distinguish functional driver mutations that are important for cancer development from random, passenger mutations. A common approach to identify driver mutations is to find genes that are mutated at significant frequency in a large cohort of cancer genomes. This approach is confounded by the observation that driver mutations target multiple cellular signaling and regulatory pathways. Thus, each cancer patient may exhibit a different combination of mutations that are sufficient to perturb the necessary pathways. However, the current understanding of the somatic mutational process of cancer [3,5,6] places two additional constraints on the expected patterns of somatic mutations in a cancer pathway. First, an important cancer pathway should be perturbed in a large number of patients. Thus we expect that with genome-wide measurements of somatic mutations a driver pathway will exhibit high coverage, where most patients will have a mutation in some gene in the pathway. Second, since driver mutations are relatively rare and typically a single driver mutation is sufficient to perturb a pathway, a reasonable assumption is that most patients have a single driver mutation in a pathway. Thus, the genes in a driver pathway exhibit a pattern of mutually exclusive driver mutations, where driver mutations are observed in exactly one gene in the pathway in each patient. There are numerous examples of sets of mutually exclusive mutations [5,6].
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U2 - 10.1007/978-3-642-20036-6_44
DO - 10.1007/978-3-642-20036-6_44
M3 - Conference contribution
AN - SCOPUS:79953224071
SN - 9783642200359
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 499
EP - 500
BT - Research in Computational Molecular Biology - 15th Annual International Conference, RECOMB 2011, Proceedings
A2 - Bafna, Vineet
A2 - Sahinalp, S. Cenk
PB - Springer Verlag
T2 - 15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011
Y2 - 28 March 2011 through 31 March 2011
ER -