Literature DB >> 22190043

A mathematical model for the glucose-lactate metabolism of in vitro cancer cells.

Berta Mendoza-Juez1, Alicia Martínez-González, Gabriel F Calvo, Víctor M Pérez-García.   

Abstract

We propose a mathematical model of tumor cell nutrient uptake governed by the presence of two key biomolecular fuels: glucose and lactate. The model allows us to describe, in a remarkably simple way, different in vitro scenarios previously reported in experiments of tumor cell metabolism using distinct energy sources. The predictions of our model show good agreement with all the examined tumor cell lines (cervix, colon, and glioma) and provide a first step toward the development of more comprehensive frameworks accounting for in vivo cancer dynamics under complex spatial heterogeneities.

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Year:  2011        PMID: 22190043     DOI: 10.1007/s11538-011-9711-z

Source DB:  PubMed          Journal:  Bull Math Biol        ISSN: 0092-8240            Impact factor:   1.758


  14 in total

1.  Glioma growth modeling based on the effect of vital nutrients and metabolic products.

Authors:  Maria Papadogiorgaki; Panagiotis Koliou; Michalis E Zervakis
Journal:  Med Biol Eng Comput       Date:  2018-03-08       Impact factor: 2.602

2.  Modeling the connection between primary and metastatic tumors.

Authors:  David Diego; Gabriel F Calvo; Víctor M Pérez-García
Journal:  J Math Biol       Date:  2012-07-25       Impact factor: 2.259

3.  Modeling of Tumor Growth with Input from Patient-Specific Metabolomic Data.

Authors:  Hunter A Miller; John Lowengrub; Hermann B Frieboes
Journal:  Ann Biomed Eng       Date:  2022-01-26       Impact factor: 3.934

4.  Evaluation of Lung Cancer Patient Response to First-Line Chemotherapy by Integration of Tumor Core Biopsy Metabolomics with Multiscale Modeling.

Authors:  Hunter A Miller; Donald M Miller; Victor H van Berkel; Hermann B Frieboes
Journal:  Ann Biomed Eng       Date:  2022-10-12       Impact factor: 4.219

Review 5.  Mathematical models of tumor cell proliferation: A review of the literature.

Authors:  Angela M Jarrett; Ernesto A B F Lima; David A Hormuth; Matthew T McKenna; Xinzeng Feng; David A Ekrut; Anna Claudia M Resende; Amy Brock; Thomas E Yankeelov
Journal:  Expert Rev Anticancer Ther       Date:  2018-10-22       Impact factor: 4.512

6.  Tracking the evolution of cancer cell populations through the mathematical lens of phenotype-structured equations.

Authors:  Tommaso Lorenzi; Rebecca H Chisholm; Jean Clairambault
Journal:  Biol Direct       Date:  2016-08-23       Impact factor: 4.540

7.  Mathematical modeling links Wnt signaling to emergent patterns of metabolism in colon cancer.

Authors:  Mary Lee; George T Chen; Eric Puttock; Kehui Wang; Robert A Edwards; Marian L Waterman; John Lowengrub
Journal:  Mol Syst Biol       Date:  2017-02-09       Impact factor: 11.429

8.  Computational Model Predicts the Effects of Targeting Cellular Metabolism in Pancreatic Cancer.

Authors:  Mahua Roy; Stacey D Finley
Journal:  Front Physiol       Date:  2017-04-12       Impact factor: 4.566

9.  Multi-scale computational study of the Warburg effect, reverse Warburg effect and glutamine addiction in solid tumors.

Authors:  Mengrou Shan; David Dai; Arunodai Vudem; Jeffrey D Varner; Abraham D Stroock
Journal:  PLoS Comput Biol       Date:  2018-12-07       Impact factor: 4.475

10.  Lactate does not activate NF-κB in oxidative tumor cells.

Authors:  Vincent F Van Hée; Jhudit Pérez-Escuredo; Andrea Cacace; Tamara Copetti; Pierre Sonveaux
Journal:  Front Pharmacol       Date:  2015-10-13       Impact factor: 5.810

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