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Do cancer cells undergo phenotypic switching? The case for imperfect cancer stem cell markers.

Zapperi S, La Porta CA - Sci Rep (2012)

Bottom Line: Here we explore an alternative explanation based on the hypothesis that markers are not perfect and are thus unable to identify all cancer stem cells.Our analysis is based on a mathematical model for cancer cell proliferation that takes into account phenotypic switching, imperfect markers and error in the sorting process.Our conclusion is that the observation of reversible expression of surface markers after sorting does not provide sufficient evidence in support of phenotypic switching.

View Article: PubMed Central - PubMed

Affiliation: CNR-IENI, Via R. Cozzi 53, 20125 Milano, Italy. stefano.zapperi@cnr.it

ABSTRACT
The identification of cancer stem cells in vivo and in vitro relies on specific surface markers that should allow to sort cancer cells in phenotypically distinct subpopulations. Experiments report that sorted cancer cell populations after some time tend to express again all the original markers, leading to the hypothesis of phenotypic switching, according to which cancer cells can transform stochastically into cancer stem cells. Here we explore an alternative explanation based on the hypothesis that markers are not perfect and are thus unable to identify all cancer stem cells. Our analysis is based on a mathematical model for cancer cell proliferation that takes into account phenotypic switching, imperfect markers and error in the sorting process. Our conclusion is that the observation of reversible expression of surface markers after sorting does not provide sufficient evidence in support of phenotypic switching.

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Related in: MedlinePlus

Evolution of the concentration of positive cells after sorting for the Imperfect Marker model.(A) The evolution of the concentration of positive cells after sorting for positive (+) and negative (−) subpopulations as a function of the number of generations N in case (i) (q+ = q− = q) for different values of the parameter q, M = 30 and . (B) The same plot as panel A) for case (ii) (q+ = 0, q− = 1) and different values of q.
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f5: Evolution of the concentration of positive cells after sorting for the Imperfect Marker model.(A) The evolution of the concentration of positive cells after sorting for positive (+) and negative (−) subpopulations as a function of the number of generations N in case (i) (q+ = q− = q) for different values of the parameter q, M = 30 and . (B) The same plot as panel A) for case (ii) (q+ = 0, q− = 1) and different values of q.

Mentions: For the imperfect maker model, we have to write two sets of recursion relations for positive and negative cells: and In Fig. 5, we report the evolution of the fraction of positive cells in the sorted population for case (i) and (ii) as a function of q. In both the fraction of positive cells converges to the steady-state value with a timescale set by M while the steady-state value depends on q.


Do cancer cells undergo phenotypic switching? The case for imperfect cancer stem cell markers.

Zapperi S, La Porta CA - Sci Rep (2012)

Evolution of the concentration of positive cells after sorting for the Imperfect Marker model.(A) The evolution of the concentration of positive cells after sorting for positive (+) and negative (−) subpopulations as a function of the number of generations N in case (i) (q+ = q− = q) for different values of the parameter q, M = 30 and . (B) The same plot as panel A) for case (ii) (q+ = 0, q− = 1) and different values of q.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3369193&req=5

f5: Evolution of the concentration of positive cells after sorting for the Imperfect Marker model.(A) The evolution of the concentration of positive cells after sorting for positive (+) and negative (−) subpopulations as a function of the number of generations N in case (i) (q+ = q− = q) for different values of the parameter q, M = 30 and . (B) The same plot as panel A) for case (ii) (q+ = 0, q− = 1) and different values of q.
Mentions: For the imperfect maker model, we have to write two sets of recursion relations for positive and negative cells: and In Fig. 5, we report the evolution of the fraction of positive cells in the sorted population for case (i) and (ii) as a function of q. In both the fraction of positive cells converges to the steady-state value with a timescale set by M while the steady-state value depends on q.

Bottom Line: Here we explore an alternative explanation based on the hypothesis that markers are not perfect and are thus unable to identify all cancer stem cells.Our analysis is based on a mathematical model for cancer cell proliferation that takes into account phenotypic switching, imperfect markers and error in the sorting process.Our conclusion is that the observation of reversible expression of surface markers after sorting does not provide sufficient evidence in support of phenotypic switching.

View Article: PubMed Central - PubMed

Affiliation: CNR-IENI, Via R. Cozzi 53, 20125 Milano, Italy. stefano.zapperi@cnr.it

ABSTRACT
The identification of cancer stem cells in vivo and in vitro relies on specific surface markers that should allow to sort cancer cells in phenotypically distinct subpopulations. Experiments report that sorted cancer cell populations after some time tend to express again all the original markers, leading to the hypothesis of phenotypic switching, according to which cancer cells can transform stochastically into cancer stem cells. Here we explore an alternative explanation based on the hypothesis that markers are not perfect and are thus unable to identify all cancer stem cells. Our analysis is based on a mathematical model for cancer cell proliferation that takes into account phenotypic switching, imperfect markers and error in the sorting process. Our conclusion is that the observation of reversible expression of surface markers after sorting does not provide sufficient evidence in support of phenotypic switching.

Show MeSH
Related in: MedlinePlus