Literature DB >> 27942765

Stochastic phenotypic interconversion in tumors can generate heterogeneity.

Giuseppina Simone1,2.   

Abstract

Phenotype variations define heterogeneity in biological and molecular systems, and play a crucial mechanistic role, and heterogeneity has been demonstrated in tumor cells. In this work, cells from blood of patients affected by colon cancer were analyzed and sorted using a microfluidic assay based on galactose-active moieties and incubated for culturing in severe combined immunodeficiency (SCID) mice. Based on the results of these experiments, a model based on Markov theory is implemented and discussed to explain the equilibrium existing between phenotypes of cell subpopulations sorted using the microfluidic assay. In combination with the experimental results, the model has many implications for tumor heterogeneity; For example, it displays interconversion of phenotypes, confirming the experiments. Such interconversion generates metastatic cells and implies that targeting circulating tumor cells (CTC) will not be an efficient method for prevention of tumor recurrence. Most importantly, understanding the transitions between cell phenotypes in the cell population can improve understanding of tumor generation and growth.

Entities:  

Keywords:  Galectin; Heterogeneity; Phenotype; Stochastic Markov model; Tumor

Mesh:

Substances:

Year:  2016        PMID: 27942765     DOI: 10.1007/s00249-016-1190-6

Source DB:  PubMed          Journal:  Eur Biophys J        ISSN: 0175-7571            Impact factor:   1.733


  16 in total

1.  A facile in situ microfluidic method for creating multivalent surfaces: toward functional glycomics.

Authors:  Giuseppina Simone; Pavel Neuzil; Gerardo Perozziello; Marco Francardi; Natalia Malara; Enzo Di Fabrizio; Andreas Manz
Journal:  Lab Chip       Date:  2012-03-09       Impact factor: 6.799

2.  Molecular communication through stochastic synchronization induced by extracellular fluctuations.

Authors:  Tianshou Zhou; Luonan Chen; Kazuyuki Aihara
Journal:  Phys Rev Lett       Date:  2005-10-19       Impact factor: 9.161

3.  Cell cycle kinetics with supramitotic control, two cell types, and unequal division: a model of transformed embryonic cells.

Authors:  M Kimmel; O Arino
Journal:  Math Biosci       Date:  1991-06       Impact factor: 2.144

4.  In vitro expansion of tumour cells derived from blood and tumour tissue is useful to redefine personalized treatment in non-small cell lung cancer patients.

Authors:  N M Malara; F Givigliano; V Trunzo; L Macrina; C Raso; N Amodio; S Aprigliano; A M Minniti; V Russo; L Roveda; M L Coluccio; M Fini; P Voci; U Prati; E Di Fabrizio; V Mollace
Journal:  J Biol Regul Homeost Agents       Date:  2014 Oct-Dec       Impact factor: 1.711

Review 5.  Tumor heterogeneity.

Authors:  G H Heppner
Journal:  Cancer Res       Date:  1984-06       Impact factor: 12.701

6.  Galectin-3 coats the membrane of breast cells and makes a signature of tumours.

Authors:  Giuseppina Simone; Natalia Malara; Valentina Trunzo; Maria Renne; Gerardo Perozziello; Enzo Di Fabrizio; Andreas Manz
Journal:  Mol Biosyst       Date:  2014-02

Review 7.  Tumor heterogeneity: causes and consequences.

Authors:  Andriy Marusyk; Kornelia Polyak
Journal:  Biochim Biophys Acta       Date:  2009-11-18

8.  Protein-carbohydrate complex reveals circulating metastatic cells in a microfluidic assay.

Authors:  G Simone; N Malara; V Trunzo; G Perozziello; P Neuzil; M Francardi; L Roveda; M Renne; U Prati; V Mollace; A Manz; E Di Fabrizio
Journal:  Small       Date:  2013-02-11       Impact factor: 13.281

9.  Conceptualizing a tool to optimize therapy based on dynamic heterogeneity.

Authors:  David Liao; Luis Estévez-Salmerón; Thea D Tlsty
Journal:  Phys Biol       Date:  2012-11-29       Impact factor: 2.583

Review 10.  Tumour heterogeneity and cancer cell plasticity.

Authors:  Corbin E Meacham; Sean J Morrison
Journal:  Nature       Date:  2013-09-19       Impact factor: 49.962

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