![]() ; ; et al in Oncotarget (2018), 9(28), 20018 According to the sequential metastasis model, aggressive mesenchymal (M) metastasis-initiating cells (MICs) are generated by an epithelial-mesenchymal transition (EMT) which eventually is reversed by a ... [more ▼] According to the sequential metastasis model, aggressive mesenchymal (M) metastasis-initiating cells (MICs) are generated by an epithelial-mesenchymal transition (EMT) which eventually is reversed by a mesenchymal-epithelial transition (MET) and outgrowth of life-threatening epithelial (E) macrometastases. Paradoxically, in breast cancer M signatures are linked with more favorable outcomes than E signatures, and M cells are often dispensable for metastasis in mouse models. Here we present evidence at the cellular and patient level for the cooperation metastasis model, according to which E cells are MICs, while M cells merely support E cell persistence through cooperation. We tracked the fates of co-cultured E and M clones and of fluorescent CDH1-promoter-driven cell lines reporting the E state derived from basal breast cancer HMLER cells. Cells were placed in suspension state and allowed to reattach and select an EMT cell fate. Flow cytometry, single cell and bulk gene expression analyses revealed that only pre-existing E cells generated E cells, mixed E/M populations, or stem-like hybrid E/M cells after suspension and that complete EMT manifest in M clones and CDH1-negative reporter cells resulted in loss of cell plasticity, suggesting full transdifferentiation. Mechanistically, E-M coculture experiments supported the persistence of pre-existing E cells where M cells inhibited EMT of E cells in a mutual cooperation via direct cell-cell contact. Consistently, M signatures were associated with more favorable patient outcomes compared to E signatures in breast cancer, specifically in basal breast cancer patients. These findings suggest a potential benefit of complete EMT for basal breast cancer patients. [less ▲] Detailed reference viewed: 110 (3 UL)![]() ; Skupin, Alexander ![]() in PLoS Biology (2016), 14(12), 2000640 Detailed reference viewed: 224 (20 UL)![]() ; ; Fouquier d'Hérouël, Aymeric ![]() in Biosystems (2016), 142 Progress in cell type reprogramming has revived the interest in Waddington’s concept of the epigenetic landscape. Recently researchers developed the quasi-potential theory to represent the Waddington’s ... [more ▼] Progress in cell type reprogramming has revived the interest in Waddington’s concept of the epigenetic landscape. Recently researchers developed the quasi-potential theory to represent the Waddington’s landscape. The Quasi-potential U(x), derived from interactions in the gene regulatory network (GRN) of a cell, quantifies the relative stability of network states, which determine the effort required for state transitions in a multi-stable dynamical system. However, quasi-potential landscapes, originally developed for continuous systems, are not suitable for discrete-valued networks which are important tools to study complex systems. In this paper, we provide a framework to quantify the landscape for discrete Boolean networks (BNs). We apply our framework to study pancreas cell differentiation where an ensemble of BN models is considered based on the structure of a minimal GRN for pancreas development. We impose biologically motivated structural constraints (corresponding to specific type of Boolean functions) and dynamical constraints (corresponding to stable attractor states) to limit the space of BN models for pancreas development. In addition, we enforce a novel functional constraint corresponding to the relative ordering of attractor states in BN models to restrict the space of BN models to the biological relevant class. We find that BNs with canalyzing/sign-compatible Boolean functions best capture the dynamics of pancreas cell differentiation. This framework can also determine the genes' influence on cell state transitions, and thus can facilitate the rational design of cell reprogramming protocols. [less ▲] Detailed reference viewed: 126 (6 UL)![]() ; Fouquier d'Hérouël, Aymeric ![]() E-print/Working paper (2016) The observations of phenotypic plasticity have stimulated the revival of "epigenetics". Over the past 70 years the term has come in many colors and flavors, depending on the biological discipline and time ... [more ▼] The observations of phenotypic plasticity have stimulated the revival of "epigenetics". Over the past 70 years the term has come in many colors and flavors, depending on the biological discipline and time period. The meanings span from Waddington "epigenotype" and "epigenetic landscape" to the molecular biologists "epigenetic marks" embodied by DNA methylation and histone modifications. Here we seek to quell the ambiguity of the name. First we place "epigenetic" in the various historical contexts. Then, by presenting the formal concepts of dynamical systems theory we show that the "epigenetic landscape" is more than a metaphor: it has specific mathematical foundations. The latter explains how gene regulatory networks produce multiple attractor states, the self-stabilizing patterns of gene activation across the genome that account for "epigenetic memory". This network dynamics approach replaces the reductionist correspondence of molecular epigenetic modifications with concept of the epigenetic landscape, by providing a concrete and crisp correspondence. [less ▲] Detailed reference viewed: 291 (6 UL)![]() ; Fouquier d'Hérouël, Aymeric ![]() in PLoS ONE (2015), 10(5), 0126522 Breast cancer stem cells (CSCs) are thought to drive recurrence and metastasis. Their identity has been linked to the epithelial to mesenchymal transition (EMT) but remains highly controversial since ... [more ▼] Breast cancer stem cells (CSCs) are thought to drive recurrence and metastasis. Their identity has been linked to the epithelial to mesenchymal transition (EMT) but remains highly controversial since-depending on the cell-line studied-either epithelial (E) or mesenchymal (M) markers, alone or together have been associated with stemness. Using distinct transcript expression signatures characterizing the three different E, M and hybrid E/M cell-types, our data support a novel model that links a mixed EM signature with stemness in 1) individual cells, 2) luminal and basal cell lines, 3) in vivo xenograft mouse models, and 4) in all breast cancer subtypes. In particular, we found that co-expression of E and M signatures was associated with poorest outcome in luminal and basal breast cancer patients as well as with enrichment for stem-like cells in both E and M breast cell-lines. This link between a mixed EM expression signature and stemness was explained by two findings: first, mixed cultures of E and M cells showed increased cooperation in mammosphere formation (indicative of stemness) compared to the more differentiated E and M cell-types. Second, single-cell qPCR analysis revealed that E and M genes could be co-expressed in the same cell. These hybrid E/M cells were generated by both E or M cells and had a combination of several stem-like traits since they displayed increased plasticity, self-renewal, mammosphere formation, and produced ALDH1+ progenies, while more differentiated M cells showed less plasticity and E cells showed less self-renewal. Thus, the hybrid E/M state reflecting stemness and its promotion by E-M cooperation offers a dual biological rationale for the robust association of the mixed EM signature with poor prognosis, independent of cellular origin. Together, our model explains previous paradoxical findings that breast CSCs appear to be M in luminal cell-lines but E in basal breast cancer cell-lines. Our results suggest that targeting E/M heterogeneity by eliminating hybrid E/M cells and cooperation between E and M cell-types could improve breast cancer patient survival independent of breast cancer-subtype. [less ▲] Detailed reference viewed: 307 (47 UL)![]() ; Fouquier d'Hérouël, Aymeric ![]() in Nucleic Acids Research (2014), 42(16), 126 Digital PCR (dPCR) exploits limiting dilution of a template into an array of PCR reactions. From this array the number of reactions that contain at least one (as opposed to zero) initial template is ... [more ▼] Digital PCR (dPCR) exploits limiting dilution of a template into an array of PCR reactions. From this array the number of reactions that contain at least one (as opposed to zero) initial template is determined, allowing inferring the original template concentration. Here we present a novel protocol to efficiently infer the concentration of a sample and its optimal dilution for dPCR from few targeted qPCR assays. By taking advantage of the real-time amplification feature of qPCR as opposed to relying on endpoint PCR assessment as in standard dPCR prior knowledge of template concentration is not necessary. This eliminates the need for serial dilutions in a separate titration and reduces the number of necessary reactions. We describe the theory underlying our approach and discuss experimental moments that contribute to uncertainty. We present data from a controlled experiment where the initial template concentration is known as proof of principle and apply our method on directly monitoring transcript level change during cell differentiation as well as gauging amplicon numbers in cDNA samples after pre-amplification. [less ▲] Detailed reference viewed: 180 (22 UL)![]() ; ; Fouquier d'Hérouël, Aymeric ![]() in Eils, Roland; Kriete, Andreas (Eds.) Computational Systems Biology (2014) Detailed reference viewed: 335 (8 UL)![]() Heinäniemi, Merja ![]() in Nature Methods (2013) The distinct cell types of multicellular organisms arise due to constraints imposed by gene regulatory networks on the collective change of gene expression across the genome, creating self-stabilizing ... [more ▼] The distinct cell types of multicellular organisms arise due to constraints imposed by gene regulatory networks on the collective change of gene expression across the genome, creating self-stabilizing expression states, or attractors. We compiled a resource of curated human expression data comprising 166 cell types and 2,602 transcription regulating genes and developed a data driven method built around the concept of expression reversal defined at the level of gene pairs, such as those participating in toggle switch circuits. This approach allows us to organize the cell types into their ontogenetic lineage-relationships and to reflect regulatory relationships among genes that explain their ability to function as determinants of cell fate. We show that this method identifies genes belonging to regulatory circuits that control neuronal fate, pluripotency and blood cell differentiation, thus offering a novel large-scale perspective on lineage specification. [less ▲] Detailed reference viewed: 235 (28 UL) |
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