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An algorithm for molecular dissection of tumor progression

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Abstract.

The volumetric growth of tumor cells as a function of time is most often likely to be a complex trait, controlled by the combined influences of multiple genes and environmental influences. Genetic mapping has proven to be a powerful tool for detecting and identifying specific genes affecting complex traits, i.e., quantitative trait loci (QTL), based on polymorphic markers. In this article, we present a novel statistical model for genetic mapping of QTL governing tumor growth trajectories in humans. In principle, this model is a combination of functional mapping proposed to map function-valued traits and linkage disequilibrium mapping designed to provide high resolution mapping of QTL by making use of recombination events created at a historic time. We implement an EM-simplex hybrid algorithm for parameter estimation, in which a closed-form solution for the EM algorithm is derived to estimate the population genetic parameters of QTL including the allele frequencies and the coefficient of linkage disequilibrium, and the simplex algorithm incorporated to estimate the curve parameters describing the dynamic changes of cancer cells for different QTL genotypes. Extensive simulations are performed to investigate the statistical properties of our model. Through a number of hypothesis tests, our model allows for cutting-edge studies aimed to decipher the genetic mechanisms underlying cancer growth, development and differentiation. The implications of our model in gene therapy for cancer research are discussed.

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Author notes

  1. Rongling Wu

    Present address: Department of Statistics, 533 McCarty Hall C University of Florida, Gainesville, FL, 32611, USA

Authors and Affiliations

  1. Departments of Statistics, University of Florida, Gainesville, FL, 32611, USA

    Tian Liu, Wei Zhao, Lili Tian & Rongling Wu

Authors
  1. Tian Liu
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  2. Wei Zhao
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  3. Lili Tian
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Correspondence to Rongling Wu.

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Liu, T., Zhao, W., Tian, L. et al. An algorithm for molecular dissection of tumor progression. J. Math. Biol. 50, 336–354 (2005). https://doi.org/10.1007/s00285-004-0297-z

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  • DOI: https://doi.org/10.1007/s00285-004-0297-z

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