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

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

Senescent Cells in Growing Tumors: Population Dynamics and Cancer Stem Cells

Tumors are defined by their intense proliferation, but sometimes cancer cells turn senescent and stop replicating. In the stochastic cancer model in which all cells are tumorigenic, senescence is seen as the result of random mutations, suggesting that it could represent a barrier to tumor growth. In the hierarchical cancer model a subset of the cells, the cancer stem cells, divide indefinitely while other cells eventually turn senescent. Here we formulate cancer growth in mathematical terms and obtain predictions for the evolution of senescence. We perform experiments in human melanoma cells which are compatible with the hierarchical model and show that senescence is a reversible process controlled by survivin. We conclude that enhancing senescence is unlikely to provide a useful therapeutic strategy to fight cancer, unless the cancer stem cells are specifically targeted

Melanoma Chemotherapy Leads to the Selection of ABCB5-Expressing Cells

Metastatic melanoma is the most aggressive skin cancer. Recently, phenotypically distinct subpopulations of tumor cells were identified. Among them, ABCB5-expressing cells were proposed to display an enhanced tumorigenicity with stem cell-like properties. In addition, ABCB5+ cells are thought to participate to chemoresistance through a potential efflux function of ABCB5. Nevertheless, the fate of these cells upon drugs that are used in melanoma chemotherapy remains to be clarified. Here we explored the effect of anti-melanoma treatments on the ABCB5-expressing cells. Using a melanoma xenograft model (WM266-4), we observed in vivo that ABCB5-expressing cells are enriched after a temozolomide treatment that induces a significant tumor regression. These results were further confirmed in a preliminary study conducted on clinical samples from patients that received dacarbazine. In vitro, we showed that ABCB5-expressing cells selectively survive when exposed to dacarbazine, the reference treatment of metastatic melanoma, but also to vemurafenib, a new inhibitor of the mutated kinase V600E BRAF and other various chemotherapeutic drugs. Our results show that anti-melanoma chemotherapy might participate to the chemoresistance acquisition by selecting tumor cell subpopulations expressing ABCB5. This is of particular importance in understanding the relapses observed after anti-melanoma treatments and reinforces the interest of ABCB5 and ABCB5-expressing cells as potential therapeutic targets in melanoma

A Steered Molecular Dynamics Study of Binding and Translocation Processes in the GABA Transporter

The entire substrate translocation pathway in the human GABA transporter (GAT-1) was explored for the endogenous substrate GABA and the anti-convulsive drug tiagabine. Following a steered molecular dynamics (SMD) approach, in which a harmonic restraining potential is applied to the ligand, dissociation and re-association of ligands were simulated revealing events leading to substrate (GABA) translocation and inhibitor (tiagabine) mechanism of action. We succeeded in turning the transporter from the outward facing occluded to the open-to-out conformation, and also to reorient the transporter to the open-to-in conformation. The simulations are validated by literature data and provide a substrate pathway fingerprint in terms of which, how, and in which sequence specific residues are interacted with. They reveal the essential functional roles of specific residues, e.g. the role of charged residues in the extracellular vestibule including two lysines (K76 (TM1) and K448 (TM10)) and a TM6-triad (D281, E283, and D287) in attracting and relocating substrates towards the secondary/interim substrate-binding site (S2). Likewise, E101 is highlighted as essential for the relocation of the substrate from the primary substrate-binding site (S1) towards the cytoplasm

The Cellular Prion Protein Interacts with the Tissue Non-Specific Alkaline Phosphatase in Membrane Microdomains of Bioaminergic Neuronal Cells

BACKGROUND: The cellular prion protein, PrP(C), is GPI anchored and abundant in lipid rafts. The absolute requirement of PrP(C) in neurodegeneration associated to prion diseases is well established. However, the function of this ubiquitous protein is still puzzling. Our previous work using the 1C11 neuronal model, provided evidence that PrP(C) acts as a cell surface receptor. Besides a ubiquitous signaling function of PrP(C), we have described a neuronal specificity pointing to a role of PrP(C) in neuronal homeostasis. 1C11 cells, upon appropriate induction, engage into neuronal differentiation programs, giving rise either to serotonergic (1C11(5-HT)) or noradrenergic (1C11(NE)) derivatives. METHODOLOGY/PRINCIPAL FINDINGS: The neuronal specificity of PrP(C) signaling prompted us to search for PrP(C) partners in 1C11-derived bioaminergic neuronal cells. We show here by immunoprecipitation an association of PrP(C) with an 80 kDa protein identified by mass spectrometry as the tissue non-specific alkaline phosphatase (TNAP). This interaction occurs in lipid rafts and is restricted to 1C11-derived neuronal progenies. Our data indicate that TNAP is implemented during the differentiation programs of 1C11(5-HT) and 1C11(NE) cells and is active at their cell surface. Noteworthy, TNAP may contribute to the regulation of serotonin or catecholamine synthesis in 1C11(5-HT) and 1C11(NE) bioaminergic cells by controlling pyridoxal phosphate levels. Finally, TNAP activity is shown to modulate the phosphorylation status of laminin and thereby its interaction with PrP. CONCLUSION/SIGNIFICANCE: The identification of a novel PrP(C) partner in lipid rafts of neuronal cells favors the idea of a role of PrP in multiple functions. Because PrP(C) and laminin functionally interact to support neuronal differentiation and memory consolidation, our findings introduce TNAP as a functional protagonist in the PrP(C)-laminin interplay. The partnership between TNAP and PrP(C) in neuronal cells may provide new clues as to the neurospecificity of PrP(C) function