Ancestral inference in tumors: How much can we know?
被引:6
|
作者:
Zhao, Junsong
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机构:
Univ So Calif, Dept Mol & Computat Biol, Los Angeles, CA 90089 USAUniv So Calif, Dept Mol & Computat Biol, Los Angeles, CA 90089 USA
Zhao, Junsong
[1
]
Siegmund, Kimberly D.
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机构:
Univ So Calif, Keck Sch Med, Dept Prevent Med, Los Angeles, CA 90089 USAUniv So Calif, Dept Mol & Computat Biol, Los Angeles, CA 90089 USA
Siegmund, Kimberly D.
[2
]
Shibata, Darryl
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机构:
Univ So Calif, Keck Sch Med, Dept Pathol, Los Angeles, CA 90089 USAUniv So Calif, Dept Mol & Computat Biol, Los Angeles, CA 90089 USA
Shibata, Darryl
[3
]
Marjoram, Paul
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机构:
Univ So Calif, Dept Mol & Computat Biol, Los Angeles, CA 90089 USA
Univ So Calif, Keck Sch Med, Dept Prevent Med, Los Angeles, CA 90089 USAUniv So Calif, Dept Mol & Computat Biol, Los Angeles, CA 90089 USA
Marjoram, Paul
[1
,2
]
机构:
[1] Univ So Calif, Dept Mol & Computat Biol, Los Angeles, CA 90089 USA
[2] Univ So Calif, Keck Sch Med, Dept Prevent Med, Los Angeles, CA 90089 USA
[3] Univ So Calif, Keck Sch Med, Dept Pathol, Los Angeles, CA 90089 USA
Ancestry;
Approximate Bayesian computation;
Methylation;
Methylation error rate;
Number of cancer stem cells;
APPROXIMATE BAYESIAN COMPUTATION;
STATISTICS;
DYNAMICS;
GROWTH;
MODELS;
D O I:
10.1016/j.jtbi.2014.05.027
中图分类号:
Q [生物科学];
学科分类号:
07 ;
0710 ;
09 ;
摘要:
A tumor is thought to start from a single cell and genome. Yet genomes in the final tumor are typically heterogeneous. The mystery of this intratumoral heterogeneity (ITH) has not yet been uncovered, but much of this ITH may be secondary to replication errors. Methylation of cytosine bases often exhibits ITH and therefore may encode the ancestry of the tumor. In this study, we measure the passenger methylation patterns of a specific CpG region in 9 colorectal tumors by bisulfite sequencing and apply a tumor development model. Based on our model, we are able to retrieve information regarding the ancestry of each tumor using approximate Bayesian computation. With a large simulation study we explore the conditions under which we can estimate the model parameters, and the initial state of the first transformed cell. Finally we apply our analysis to clinical data to gain insight into the dynamics of tumor formation. (C) 2014 Elsevier Ltd. All rights reserved.