Single-cell sequencing data reveal widespread recurrence and loss of mutational hits in the life histories of tumors

被引:82
作者
Kuipers, Jack [1 ,2 ]
Jahn, Katharina [1 ,2 ]
Raphael, Benjamin J. [3 ]
Beerenwinkel, Niko [1 ,2 ]
机构
[1] Swiss Fed Inst Technol, Dept Biosyst Sci & Engn, CH-4058 Basel, Switzerland
[2] SIB, CH-4058 Basel, Switzerland
[3] Princeton Univ, Dept Comp Sci, Princeton, NJ 08540 USA
基金
欧洲研究理事会;
关键词
CLONAL EVOLUTION; INTRATUMOR HETEROGENEITY; CANCER-RISK; INFERENCE; SAMPLES; MODEL; LEUKEMIA; NUMBER;
D O I
10.1101/gr.220707.117
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Intra-tumor heterogeneity poses substantial challenges for cancer treatment. A tumor's composition can be deduced by reconstructing its mutational history. Central to current approaches is the infinite sites assumption that every genomic position can only mutate once over the lifetime of a tumor. The validity of this assumption has never been quantitatively assessed. We developed a rigorous statistical framework to test the infinite sites assumption with single-cell sequencing data. Our framework accounts for the high noise and contamination present in such data. We found strong evidence for the same genomic position being mutationally affected multiple times in individual tumors for 11 of 12 single-cell sequencing data sets from a variety of human cancers. Seven cases involved the loss of earlier mutations, five of which occurred at sites unaffected by large-scale genomic deletions. Four cases exhibited a parallel mutation, potentially indicating convergent evolution at the base pair level. Our results refute the general validity of the infinite sites assumption and indicate that more complex models are needed to adequately quantify intra-tumor heterogeneity for more effective cancer treatment.
引用
收藏
页码:1885 / 1894
页数:10
相关论文
共 44 条
  • [11] Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing
    Gerlinger, Marco
    Rowan, Andrew J.
    Horswell, Stuart
    Larkin, James
    Endesfelder, David
    Gronroos, Eva
    Martinez, Pierre
    Matthews, Nicholas
    Stewart, Aengus
    Tarpey, Patrick
    Varela, Ignacio
    Phillimore, Benjamin
    Begum, Sharmin
    McDonald, Neil Q.
    Butler, Adam
    Jones, David
    Raine, Keiran
    Latimer, Calli
    Santos, Claudio R.
    Nohadani, Mahrokh
    Eklund, Aron C.
    Spencer-Dene, Bradley
    Clark, Graham
    Pickering, Lisa
    Stamp, Gordon
    Gore, Martin
    Szallasi, Zoltan
    Downward, Julian
    Futreal, P. Andrew
    Swanton, Charles
    [J]. NEW ENGLAND JOURNAL OF MEDICINE, 2012, 366 (10) : 883 - 892
  • [12] Clonal evolution in cancer
    Greaves, Mel
    Maley, Carlo C.
    [J]. NATURE, 2012, 481 (7381) : 306 - 313
  • [13] Gusfield D., 1997, Algorithms on Strings, Trees, and Sequences-Computer Science and Computational Biology, DOI DOI 10.1017/CBO9780511574931
  • [14] A combinatorial approach for analyzing intra-tumor heterogeneity from high-throughput sequencing data
    Hajirasouliha, Iman
    Mahmoody, Ahmad
    Raphael, Benjamin J.
    [J]. BIOINFORMATICS, 2014, 30 (12) : 78 - 86
  • [15] Single-Cell Exome Sequencing and Monoclonal Evolution of a JAK2-Negative Myeloproliferative Neoplasm
    Hou, Yong
    Song, Luting
    Zhu, Ping
    Zhang, Bo
    Tao, Ye
    Xu, Xun
    Li, Fuqiang
    Wu, Kui
    Liang, Jie
    Shao, Di
    Wu, Hanjie
    Ye, Xiaofei
    Ye, Chen
    Wu, Renhua
    Jian, Min
    Chen, Yan
    Xie, Wei
    Zhang, Ruren
    Chen, Lei
    Liu, Xin
    Yao, Xiaotian
    Zheng, Hancheng
    Yu, Chang
    Li, Qibin
    Gong, Zhuolin
    Mao, Mao
    Yang, Xu
    Yang, Lin
    Li, Jingxiang
    Wang, Wen
    Lu, Zuhong
    Gu, Ning
    Laurie, Goodman
    Bolund, Lars
    Kristiansen, Karsten
    Wang, Jian
    Yang, Huanming
    Li, Yingrui
    Zhang, Xiuqing
    Wang, Jun
    [J]. CELL, 2012, 148 (05) : 873 - 885
  • [16] Tree inference for single-cell data
    Jahn, Katharina
    Kuipers, Jack
    Beerenwinkel, Niko
    [J]. GENOME BIOLOGY, 2016, 17
  • [17] Assessing intratumor heterogeneity and tracking longitudinal and spatial clonal evolutionary history by next-generation sequencing
    Jiang, Yuchao
    Qiu, Yu
    Minn, Andy J.
    Zhang, Nancy R.
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2016, 113 (37) : E5528 - E5537
  • [18] Inferring clonal evolution of tumors from single nucleotide somatic mutations
    Jiao, Wei
    Vembu, Shankar
    Deshwar, Amit G.
    Stein, Lincoln
    Morris, Quaid
    [J]. BMC BIOINFORMATICS, 2014, 15
  • [19] BAYES FACTORS
    KASS, RE
    RAFTERY, AE
    [J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1995, 90 (430) : 773 - 795
  • [20] Using single cell sequencing data to model the evolutionary history of a tumor
    Kim, Kyung In
    Simon, Richard
    [J]. BMC BIOINFORMATICS, 2014, 15