Literature DB >> 24907673

Ancestral inference in tumors: how much can we know?

Junsong Zhao1, Kimberly D Siegmund2, Darryl Shibata3, Paul Marjoram4.   

Abstract

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.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Ancestry; Approximate Bayesian computation; Methylation; Methylation error rate; Number of cancer stem cells

Mesh:

Year:  2014        PMID: 24907673      PMCID: PMC4138290          DOI: 10.1016/j.jtbi.2014.05.027

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  20 in total

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Authors:  J K Pritchard; M T Seielstad; A Perez-Lezaun; M W Feldman
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Journal:  Math Med Biol       Date:  2003-12       Impact factor: 1.854

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Review 6.  Modern computational approaches for analysing molecular genetic variation data.

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7.  Inferring coalescence times from DNA sequence data.

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Journal:  Stat Appl Genet Mol Biol       Date:  2011-09-27

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Authors:  Christoph A Klein; Dieter Hölzel
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Journal:  Br J Cancer       Date:  1964-09       Impact factor: 7.640

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  7 in total

1.  Simulation-based Bayesian Analysis of Complex Data.

Authors:  Paul Marjoram; Steven Hamblin; Brad Foley
Journal:  Summer Comput Simul Conf (2015)       Date:  2015-12

2.  Early mutation bursts in colorectal tumors.

Authors:  Junsong Zhao; Matthew P Salomon; Darryl Shibata; Christina Curtis; Kimberly Siegmund; Paul Marjoram
Journal:  PLoS One       Date:  2017-03-03       Impact factor: 3.240

3.  Simulation framework for generating intratumor heterogeneity patterns in a cancer cell population.

Authors:  Watal M Iwasaki; Hideki Innan
Journal:  PLoS One       Date:  2017-09-06       Impact factor: 3.240

4.  Quantitative evidence for early metastatic seeding in colorectal cancer.

Authors:  Zheng Hu; Jie Ding; Zhicheng Ma; Ruping Sun; Jose A Seoane; J Scott Shaffer; Carlos J Suarez; Anna S Berghoff; Chiara Cremolini; Alfredo Falcone; Fotios Loupakis; Peter Birner; Matthias Preusser; Heinz-Josef Lenz; Christina Curtis
Journal:  Nat Genet       Date:  2019-06-17       Impact factor: 38.330

5.  A Genetic Bottleneck of Mitochondrial DNA During Human Lymphocyte Development.

Authors:  Zhongjie Tang; Zhaolian Lu; Baizhen Chen; Weixing Zhang; Howard Y Chang; Zheng Hu; Jin Xu
Journal:  Mol Biol Evol       Date:  2022-05-03       Impact factor: 8.800

6.  Sweepstake evolution revealed by population-genetic analysis of copy-number alterations in single genomes of breast cancer.

Authors:  Mamoru Kato; Daniel A Vasco; Ryuichi Sugino; Daichi Narushima; Alexander Krasnitz
Journal:  R Soc Open Sci       Date:  2017-09-27       Impact factor: 2.963

7.  Cancer Molecular Evolution.

Authors:  David Posada
Journal:  J Mol Evol       Date:  2015-08-20       Impact factor: 2.395

  7 in total

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