To develop anti-amyloidogenic inhibitors for ameliorating the treatment of diabetes, herein, we have synthesized amphiphilic block copolymers with side-chain fatty acid (FA) moieties via reversible addition fragmentation chain-transfer (RAFT) polymerization....

Cellular self-assembly and organization are fundamental steps for the development of biological tissues. In this paper, within the framework of a cellular automata model, we address how an ordered tissue pattern spontaneously emerges from a randomly migrating single cell population without the influence of any external cues. This model is based on the active motility of cells and their ability to reorganize due to cell-cell cohesivity as observed in experiments. Our model successfully emulates the formation of nascent clusters and also predicts the temporal evolution of aggregates that leads to the compact tissue structures. Moreover, the simulations also capture several dynamical properties of growing aggregates, such as, the rate of cell aggregation and non-monotonic growth of the aggregate area which show a good agreement with the existing experimental observations. We further investigate the time evolution of the cohesive strength, and the compactness of aggregates, and also study the ruggedness of the growing structures by evaluating the fractal dimension to get insights into the complexity of tumorous tissue growth which were hitherto unexplored.

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Metastasis is the primary cause of cancer related mortality and morbidity. The circulating tumor cells (CTCs) are shed by epithelial-origin tumors, intravasate assisted by tumor-associated macrophages (TAMs) and travel with blood. A few CTCs extravasate and seed metastasis. However, to reach their destination CTCs have to adapt to hostile for them circulation environment. Previously, we found that the nanomechanical properties of CTCs isolated from prostate cancer patient blood point at CTCs endurance and invasiveness associated with EMT (epithelial-mesenchymal transition). in turn these properties correlated with the patients' sensitivity to androgen deprivation therapy. Here we present evidence that CTCs uniquely co-isolate with macrophage-like cells similar to tumor-associated macrophages (TAMs). We determined with atomic force microscopy (AFM) that pronounced presence of these immune cells was associated with high softness and high adhesion of CTCs. Such survival-promoting phenotypes were related to mechanical fitness and invasiveness in CTCs and could be especially strong in patients starting hormonal therapy. Next, we aimed to recapitulate the tumor cells -macrophages interactions in cell culture using prostate cancer cell lines. Nanomechanical phenotyping and single-cell proteomic analysis showed that the presence of TAM like cells promoted hybrid EMT that increased the mechanical fitness of CTCs. We postulate that to acquire hybrid EMT, certain CTCs are coached by TAMs during their co-migration through the bloodstream. The resulting well-mechanically fit CTCs survive the critical early stage of circulation thanks to softness bestowing resistance to shear stress, and adhesiveness enabling protective cell clustering.

Cellular aggregation is a complex process orchestrated by various kinds of interactions depending on its environments. Different interactions give rise to different pathways of cellular rearrangement and the development of specialized tissues. To distinguish the underlying mechanisms, in this theoretical work, we investigate the spontaneous emergence of tissue patterns from an ensemble of single cells on a substrate following three leading pathways of cell-cell interactions, namely, direct cell adhesion contacts, matrix mediated mechanical interaction, and chemical signalling. Our analysis shows that the growth kinetics of the aggregation process is distinctly different for each pathway and bears the signature of the specific cell-cell interactions. Interestingly, we find that the average domain size and the mass of the clusters exhibit a power law growth in time under certain interaction mechanisms hitherto unexplored. Further, as observed in experiments, the cluster size distribution can be characterized by stretched exponential functions showing distinct cellular organization processes.