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Inferring sequential order of somatic mutations during tumorgenesis based on markov chain model
Kang H.6; Cho K.-H.4; Zhang X.D.5; Zeng T.1; Chen L.6
2015-09-01
Source PublicationIEEE/ACM Transactions on Computational Biology and Bioinformatics
ISSN15455963
Volume12Issue:5Pages:1094-1103
AbstractTumors are developed and worsen with the accumulated mutations on DNA sequences during tumorigenesis. Identifying the temporal order of gene mutations in cancer initiation and development is a challenging topic. It not only provides a new insight into the study of tumorigenesis at the level of genome sequences but also is an effective tool for early diagnosis of tumors and preventive medicine. In this paper, we develop a novel method to accurately estimate the sequential order of gene mutations during tumorigenesis from genome sequencing data based on Markov chain model as TOMC (Temporal Order based on Markov Chain), and also provide a new criterion to further infer the order of samples or patients, which can characterize the severity or stage of the disease. We applied our method to the analysis of tumors based on several high-throughput datasets. Specifically, first, we revealed that tumor suppressor genes (TSG) tend to be mutated ahead of oncogenes, which are considered as important events for key functional loss and gain during tumorigenesis. Second, the comparisons of various methods demonstrated that our approach has clear advantages over the existing methods due to the consideration on the effect of mutation dependence among genes, such as co-mutation. Third and most important, our method is able to deduce the ordinal sequence of patients or samples to quantitatively characterize their severity of tumors. Therefore, our work provides a new way to quantitatively understand the development and progression of tumorigenesis based on high throughput sequencing data.
Keywordfirst hitting time markov chain Mutation order
DOI10.1109/TCBB.2015.2424408
URLView the original
Language英語
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Cited Times [WOS]:3   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionFaculty of Health Sciences
Affiliation1.Institute of Biochemistry and Cell Biology, Shanghai Institute for Biological Sciences Chinese Academy of Sciences
2.Chinese Academy of Sciences
3.University of Tokyo
4.Korea Advanced Institute of Science & Technology
5.Merck Research Laboratories
6.ShanghaiTech University
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Kang H.,Cho K.-H.,Zhang X.D.,et al. Inferring sequential order of somatic mutations during tumorgenesis based on markov chain model[J]. IEEE/ACM Transactions on Computational Biology and Bioinformatics,2015,12(5):1094-1103.
APA Kang H.,Cho K.-H.,Zhang X.D.,Zeng T.,&Chen L..(2015).Inferring sequential order of somatic mutations during tumorgenesis based on markov chain model.IEEE/ACM Transactions on Computational Biology and Bioinformatics,12(5),1094-1103.
MLA Kang H.,et al."Inferring sequential order of somatic mutations during tumorgenesis based on markov chain model".IEEE/ACM Transactions on Computational Biology and Bioinformatics 12.5(2015):1094-1103.
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