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ELIMINATING CANCER STEM CELLS

Background

In normal tissues, the balance between the unlimited self-renewal capacity of stem cells (SCs), and their ability to continuously supply the required number of end cells, is regulated by numerous environmental signals, acting through paracrine or autocrine pathways. This balance is expected to be tightly controlled in order to maintain tissue homeostasis throughout life, also in the face of environmental hazards. Deciphering the cues that enhance SC proliferation under environmental disturbances, and the cues that attenuate accelerated proliferation when normal conditions resume, may shed light on the origin of cancer and may suggest new methods for its control. The power of the mathematical approach to this problem lies in its simplification: the precision, universality and objectivity of the system's analysis are reinforced by the mathematical model's unique ability to overlook less critical system's processes.

Methods and Results

Using increasingly complex mathematical models we studied the mechanism whereby cancer stem cells (SCs) are directed into differentiation. For searching the simplest possible mechanism that allows the tumor tissue to maintain homeostasis, we developed a minimal cellular–automata model that encapsulated proliferation and differentiation properties of individual cells within tissue dynamics. Analysis of this model established that long-term homeostasis is maintained by negative feedback control of cell density (“quorum sensing,” ref. Agur, Daniel, & Ginosar, 2002; Kirnasovsky, Kogan, & Agur, 2008b). In addition, we established that no simpler mechanism could decide the cell fate, i.e, whether they will proliferate or differentiate (Kirnasovsky, et al., 2008b). By the use of the model we predicted that incessant SC proliferation results primarily from poor communication among SCs, i.e, inefficient quorum sensing. We validated this prediction in vitro using MCF-7 BC cells (Agur, Levi, Farnie, Kirnasovsky, & Clarke, 2010). Thereafter we focused on breast cancer SCs (BC–SCs), hypothesizing that modulation of intracellular signaling networks can direct BC–SCs into differentiation, thereby preventing the renewal of cancer and enhancing therapy. To identify the elements critical for the transition into differentiation, we developed a new mathematical modeling type, integrating intracellular and extracellular signal transduction within tissue dynamics. Model analysis indicated that a certain protein known to negatively regulate the Wnt pathway, plays a role in the transition from SC replication to differentiation (Kirnasovsky, Kogan, & Agur, 2008a). By simulating the quantitative effects of this protein, we predicted that it affects BC-SC differentiation in a biphasic manner: low levels of this protein could slightly increase SC numbers, whereas high levels drive SCs into differentiation. This prediction, has been verified in vitro in BC cells taken from primary BC tumor and in the MCF-7 BC cell line.

Conclusions

Upon in vivo confirmation of our predictions, modulation of the Wnt pathway could provide a new option for cancer therapy.

For further reading

Agur, Z., Daniel, Y., & Ginosar, Y. (2002). The universal properties of stem cells as pinpointed by a simple discrete model. J Math Biol, 44(1), 79-86.

Agur, Z., Kirnasovsky, OU.,. Tencer, L., Wasserman, G., Harrison, H., Lamb, R. Clarke, R. B. Experimental validation of mathematically predicted effects of Dickkopf-1 protein on breast cancer stem cell differentiation. In preparation

Agur, Z., Levi, L., Farnie, G., Kirnasovsky, O. U., & Clarke, R. (2010). Disruption of a quorum sensing mechanism may trigger somatic evolution of cancer: a simple discrete model and its preliminary in vitro verification in mammary cancer stem cells. Biology Direct, In Press.

Kirnasovsky, O. U., Kogan, Y., & Agur, Z. (2008a). Analysis of a mathematical model for the molecular mechanism of mammary stem cell fate decision. Mathematical Modelling of Natural Phenomena, 3(7), 78-89.

Kirnasovsky, O. U., Kogan, Y., & Agur, Z. (2008b). Resilience in Stem Cell renewal: Development of the Agur – Daniel – Ginossar Model. Discrete and Continuous Dynamical Systems - Series B, 10(1), 129-148.