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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 in the Markov model.The evolution of the concentration of positive cells after sorting for positive (+) and negative (−) subpopulations as a function of the number of generations N for the Markov model with P11 = 0.4 and two different values of P21.
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f2: Evolution of the concentration of positive cells after sorting in the Markov model.The evolution of the concentration of positive cells after sorting for positive (+) and negative (−) subpopulations as a function of the number of generations N for the Markov model with P11 = 0.4 and two different values of P21.

Mentions: Here, we consider the simple case in which cells are sorted in only two classes: CSCs and CC. Taking advantage of the normalization condition Σiρi = 1, the evolution equation in Eq. 1 can then be written in terms of the density of CSC f1 alone where P11 is the probability per day that a CSC remains a CSC and P21 is the probability that a CC transforms to a CSC. Eq. 3 has explicit solution At long times the fraction of CSCs is given by and the steady-state is reached exponentially with a typical timescale τ = −1/log(P11 − P21) both for positive (f1(0) = 1) and negative sorted subpopulations (f1(0) = 0). An illustration of the behavior of the model is reported in Fig. 2.


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 in the Markov model.The evolution of the concentration of positive cells after sorting for positive (+) and negative (−) subpopulations as a function of the number of generations N for the Markov model with P11 = 0.4 and two different values of P21.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f2: Evolution of the concentration of positive cells after sorting in the Markov model.The evolution of the concentration of positive cells after sorting for positive (+) and negative (−) subpopulations as a function of the number of generations N for the Markov model with P11 = 0.4 and two different values of P21.
Mentions: Here, we consider the simple case in which cells are sorted in only two classes: CSCs and CC. Taking advantage of the normalization condition Σiρi = 1, the evolution equation in Eq. 1 can then be written in terms of the density of CSC f1 alone where P11 is the probability per day that a CSC remains a CSC and P21 is the probability that a CC transforms to a CSC. Eq. 3 has explicit solution At long times the fraction of CSCs is given by and the steady-state is reached exponentially with a typical timescale τ = −1/log(P11 − P21) both for positive (f1(0) = 1) and negative sorted subpopulations (f1(0) = 0). An illustration of the behavior of the model is reported in Fig. 2.

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