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.

Allostery is essential for controlled catalysis, signal transmission, receptor trafficking, turning genes on and off, and apoptosis. It governs the organism's response to environmental and metabolic cues, dictating transient partner interactions in the cellular network. Textbooks taught us that allostery is a change of shape at one site on the protein surface brought about by ligand binding to another. For several years, it has been broadly accepted that the change of shape is not induced; rather, it is observed simply because a larger protein population presents it. Current data indicate that while side chains can reorient and rewire, allostery may not even involve a change of (backbone) shape. Assuming that the enthalpy change does not reverse the free-energy change due to the change in entropy, entropy is mainly responsible for binding.

Highlights d Time-dependent stem cell depletion levels off in the old brain via increased quiescence d Age minimally changes the neural stem cell transcriptome d Once-activated neural stem cells perform similar in the old and young brain d The old niche keeps stem cells quiescent via inflammation and Wnt activity regulation

While allostery draws increasing attention, not much is known about allosteric mechanisms. Here we argue that in all proteins, allosteric signals transmit through multiple, pre-existing pathways; which pathways dominate depend on protein topologies, specific binding events, covalent modifications and cellular (environmental) conditions. Further, perturbation events at any site on the protein surface (or in the interior) will not create new pathways but only shift the pre-existing ensemble of pathways. Drugs binding at different sites or mutational events in disease shift the ensemble toward the same conformations; however, the relative populations of the different states will change. Consequently the observed functional, conformational, and dynamic effects will be different. This is the origin of allosteric functional modulation in dynamic proteins: allostery does not necessarily need to invoke conformational rearrangements to control protein activity and pre-existing pathways are always defaulted to during allostery regardless of the stimulant and perturbation site in the protein.

Here, we represent protein structures as residue interacting networks, which are assumed to involve a permanent flow of information between amino acids. By removal of nodes from the protein network, we identify fold centrally conserved residues, which are crucial for sustaining the shortest pathways and thus play key roles in long-range interactions. Analysis of seven protein families (myoglobins, G-protein-coupled receptors, the trypsin class of serine proteases, hemoglobins, oligosaccharide phosphorylases, nuclear receptor ligand-binding domains and retroviral proteases) confirms that experimentally many of these residues are important for allosteric communication.The agreement between the centrally conserved residues, which are key in preserving short path lengths, and residues experimentally suggested to mediate signaling further illustrates that topology plays an important role in network communication. Protein folds have evolved under constraints imposed by function. To maintain function, protein structures need to be robust to mutational events. On the other hand, robustness is accompanied by an extreme sensitivity at some crucial sites. Thus, here we propose that centrally conserved residues, whose removal increases the characteristic path length in protein networks, may relate to the system fragility.

Classification has proven immensely important in science. Using a classification as proposed here should complement text-book descriptions and assist in understanding how function is performed on the single molecule level within the framework of its complex cellular environment.

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Parkinson's disease (PD) is a major neurodegenerative chronic disease, most likely caused by a complex interplay of genetic and environmental factors. Information on various aspects of PD pathogenesis is rapidly increasing and needs to be efficiently organized, so that the resulting data is available for exploration and analysis. Here we introduce a computationally tractable, comprehensive molecular interaction map of PD. This map integrates pathways implicated in PD pathogenesis such as synaptic and mitochondrial dysfunction, impaired protein degradation, alpha-synuclein pathobiology and neuroinflammation. We also present bioinformatics tools for the analysis, enrichment and annotation of the map, allowing the research community to open new avenues in PD research. The PD map is accessible at http://minerva.uni.lu/pd_map.Electronic supplementary materialThe online version of this article (doi:10.1007/s12035-013-8489-4) contains supplementary material, which is available to authorized users.