Accumulation of driver and passenger mutations during tumor progression

被引:576
作者
Bozic, Ivana [4 ,5 ]
Antal, Tibor [4 ,6 ]
Ohtsuki, Hisashi [7 ]
Carter, Hannah [8 ]
Kim, Dewey [8 ]
Chen, Sining [9 ]
Karchin, Rachel [8 ]
Kinzler, Kenneth W. [1 ,2 ]
Bogelstein, Bert [1 ,2 ]
Nowak, Martin A. [3 ,4 ,5 ]
机构
[1] Johns Hopkins Kimmel Canc Ctr, Ludwig Ctr Canc Genet & Therapeut, Baltimore, MD 21231 USA
[2] Johns Hopkins Kimmel Canc Ctr, Howard Hudges Med Inst, Baltimore, MD 21231 USA
[3] Harvard Univ, Dept Organism & Evolutionary Biol, Cambridge, MA 02138 USA
[4] Harvard Univ, Program Evolutionary Dynam, Cambridge, MA 02138 USA
[5] Harvard Univ, Dept Math, Cambridge, MA 02138 USA
[6] Univ Edinburgh, Sch Math, Edinburgh EH9 3JZ, Midlothian, Scotland
[7] Tokyo Inst Technol, Dept Value & Decis Sci, Tokyo 1528552, Japan
[8] Johns Hopkins Univ, Dept Biomed Engn, Inst Computat Med, Baltimore, MD 21218 USA
[9] Univ Med & Dent New Jersey, Sch Publ Hlth, Dept Biostat, Piscataway, NJ 08854 USA
基金
美国国家科学基金会;
关键词
genetics; mathematical biology; SOMATIC MUTATIONS; WAITING TIME; HUMAN BREAST; CANCER; EVOLUTION; MODEL; RESISTANCE; PATHWAYS; GENES; COLON;
D O I
10.1073/pnas.1010978107
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Major efforts to sequence cancer genomes are now occurring throughout the world. Though the emerging data from these studies are illuminating, their reconciliation with epidemiologic and clinical observations poses a major challenge. In the current study, we provide a mathematical model that begins to address this challenge. We model tumors as a discrete time branching process that starts with a single driver mutation and proceeds as each new driver mutation leads to a slightly increased rate of clonal expansion. Using the model, we observe tremendous variation in the rate of tumor development-providing an understanding of the heterogeneity in tumor sizes and development times that have been observed by epidemiologists and clinicians. Furthermore, the model provides a simple formula for the number of driver mutations as a function of the total number of mutations in the tumor. Finally, when applied to recent experimental data, the model allows us to calculate the actual selective advantage provided by typical somatic mutations in human tumors in situ. This selective advantage is surprisingly small-0.004 +/- 0.0004-and has major implications for experimental cancer research.
引用
收藏
页码:18545 / 18550
页数:6
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