Proteoglycans are essential constituents of tissue- and organ microenvironments, modulating both the structural scaffolds that surround cells as well as signaling cues that determine cellular ...phenotype. An important modification of proteoglycans is the sulfation of the monosaccharides that comprise them. Sulfates are added by sulfotransferases and desulfation occurs through the action of sulfatases. In this essay, we examine the biochemistry of a conserved family of desulfating enzymes known as arylsulfatases. A subset of these enzymes mediates the desulfation of proteoglycans. We review the consequences of their aberrant expression in the light of carcinogenesis and carcinomatosis: the dissemination of cancer cells. A closer understanding of their cellular-molecular roles reveals their promise for future strategies for cancer therapy.
The progression of cancer in the breast involves multiple reciprocal interactions between malignantly transformed epithelia, surrounding untransformed but affected stromal cells, and the ...extracellular matrix (ECM) that is remodeled during the process. A quantitative understanding of the relative contribution of such interactions to phenotypes associated with cancer cells can be arrived at through the construction of increasingly complex experimental and computational models. Herein, we introduce a multiscale three-dimensional (3D) organo- and pathotypic experimental assay that approximates, to an unprecedented extent, the histopathological complexity of a tumor disseminating into its surrounding stromal milieu via both bulk and solitary motility dynamics. End point and time-lapse microscopic observations of this assay allow us to study the earliest steps of cancer invasion as well as the dynamical interactions between the epithelial and stromal compartments. We then simulate our experimental observations using the modeling environment Compucell3D that is based on the Glazier-Graner-Hogeweg model. The computational model, which comprises adhesion between cancer cells and the matrices, cell proliferation and apoptosis, and matrix remodeling through reaction-diffusion-based morphogen dynamics, is first trained to phenocopy controls run with the experimental model, wherein one or the other matrices have been removed. The trained computational model successfully predicts phenotypes of the experimental counterparts that are subjected to pharmacological treatments (inhibition of N-linked glycosylation and matrix metalloproteinase activity) and scaffold modulation (alteration of collagen density). Further parametric exploration-based simulations suggest that specific permissive regimes of cell-cell and cell-matrix adhesions, operating in the context of a reaction-diffusion-regulated ECM dynamics, promote multiscale invasion of breast cancer cells and determine the extent to which the latter migrate through their surrounding stroma.
Droplet encapsulations using liquid or solid shells are of significant interest in microreactors, drug delivery, crystallization, and cell growth applications. Despite progress in droplet-related ...technologies, tuning micron-scale shell thickness over a large range of droplet sizes is still a major challenge. In this work, we report capillary force assisted cloaking using hydrophobic colloidal particles and liquid-infused surfaces. The technique produces uniform solid and liquid shell encapsulations over a broad range (5-200 μm shell thickness for droplet volume spanning over four orders of magnitude). Tunable liquid encapsulation is shown to reduce the evaporation rate of droplets by up to 200 times with a wide tunability in lifetime (1.5 h to 12 days). Further, we propose using the technique for single crystals and cell/spheroid culture platforms. Stimuli-responsive solid shells show hermetic encapsulation with tunable strength and dissolution time. Moreover, scalability, and versatility of the technique is demonstrated for on-chip applications.
Asexually reproducing populations of single cells evolve through mutation, natural selection, and genetic drift. Environmental conditions in which the evolution takes place define the emergent ...fitness landscapes. In this work, we used Avida-a digital evolution framework-to uncover a hitherto unexplored interaction between mutation rates, population size, and the relative abundance of metabolizable resources, and its effect on evolutionary outcomes in small populations of digital organisms.
Over each simulation, the population evolved to one of several states, each associated with a single dominant phenotype with its associated fitness and genotype. For a low mutation rate, acquisition of fitness by organisms was accompanied with, and dependent on, an increase in rate of genomic replication. At an increased mutation rate, phenotypes with high fitness values were similarly achieved through enhanced genome replication rates. In addition, we also observed the frequent emergence of suboptimal fitness phenotype, wherein neighboring organisms signaled to each other information relevant to performing metabolic tasks. This metabolic signaling was vital to fitness acquisition and was correlated with greater genotypic and phenotypic heterogeneity in the population. The frequency of appearance of signaling populations increased with population size and with resource abundance.
Our results reveal a minimal set of environment-genotype interactions that lead to the emergence of metabolic signaling within evolving populations.
Circulating tumor cells (CTCs) are putative markers of tumor prognosis and may serve to evaluate patient's response to chemotherapy. CTCs are often detected as single cells but infrequently as ...clusters and are indicative of worse prognosis. In this study, we developed a short-term culture of nucleated blood cells which was applied to blood samples from breast, lung, esophageal and bladder cancer patients. Clusters of different degrees of compactness, classified as very tight, tight and loose were observed across various cancer types. These clusters show variable expression of cytokeratins. Cluster formation from blood samples obtained during the course of chemotherapy was found to be associated with disease progression and shorter overall survival. The short-term cultures offer a robust and highly reliable method for early prediction of treatment response in different cancer types.
This article considers the role played by a core set of "dynamical patterning modules" (DPMs) in the origination, development and evolution of complex organisms. These consist of the products of a ...subset of the genes of what has come to be known as the "developmental-genetic toolkit" in association with physical processes they mobilize. The physical processes are those characteristic of chemically and mechanically excitable mesoscopic systems like cell aggregates: cohesion, viscoelasticity, diffusion, spatiotemporal heterogeneity based on activator-inhibitor interaction, and multistable and oscillatory dynamics. We focus on the emergence of the Metazoa, and show how toolkit gene products and pathways that pre-existed the metazoans acquired novel morphogenetic functions simply by virtue of the change in scale and context inherent to multicellularity. We propose that DPMs, acting singly and in combination with each other, constitute a "pattern language" capable of generating all metazoan body plans and organ forms. This concept implies that the multicellular organisms of the late Precambrian-early Cambrian were phenotypically plastic, fluently exploring morphospace in a fashion decoupled from both function-based selection and genotypic change. The relatively stable developmental trajectories and morphological phenotypes of modern organisms, then, are considered to be products of stabilizing selection. This perspective solves the apparent "molecular homology-analogy paradox," whereby widely divergent modern animal types utilize the same molecular toolkit during development, but it does so by inverting the neo-Darwinian principle that phenotypic disparity was generated over long periods of time in concert with, and in proportion to genotypic change.
Several post-translational protein modifications lie predominantly within regions of disorder: the biased localization has been proposed to expand the binding versatility of disordered regions. ...However, investigating a representative dataset of 500 human N-glycoproteins, we observed the sites of N-linked glycosylations or N-glycosites, to be predominantly present in the regions of predicted order. When compared with disordered stretches, ordered regions were not found to be enriched for asparagines, serines and threonines, residues that constitute the sequon signature for conjugation of N-glycans. We then investigated the basis of mutual exclusivity between disorder and N-glycosites on the basis of amino acid distribution: when compared with control ordered residue stretches without any N-glycosites, residue neighborhoods surrounding N-glycosites showed a depletion of bulky, hydrophobic and disorder-promoting amino acids and an enrichment for flexible and accessible residues that are frequently found in coiled structures. When compared with control disordered residue stretches without any N-glycosites, N-glycosite neighborhoods were depleted of charged, polar, hydrophobic and flexible residues and enriched for aromatic, accessible and order-promoting residues with a tendency to be part of coiled and β structures. N-glycosite neighborhoods also showed greater phylogenetic conservation among amniotes, compared with control ordered regions, which in turn were more conserved than disordered control regions. Our results lead us to propose that unique primary structural compositions and differential propensities for evolvability allowed for the mutual spatial exclusion of N-glycosite neighborhoods and disordered stretches.
The formation of spheroids during epithelial ovarian cancer progression is correlated with peritoneal metastasis, disease recurrence, and poor prognosis. Although metastasis has been demonstrated to ...be driven by metabolic changes in transformed cells, mechanistic associations between metabolism and phenotypic transitions remain ill-explored. We performed quantitative proteomics to identify protein signatures associated with three distinct phenotypic morphologies (2D monolayers and two geometrically distinct three-dimensional spheroidal states) of the high-grade serous ovarian cancer line OVCAR-3. We obtained disease-driving phenotype-specific metabolic reaction modules and elucidated gene knockout strategies to reduce metabolic alterations that could drive phenotypic transitions. Exploring the DrugBank database, we identified and evaluated drugs that could impair such transitions and, hence, cancer progression. Finally, we experimentally validated our predictions by confirming the ability of one of our predicted drugs, the neuraminidase inhibitor oseltamivir, to inhibit spheroidogenesis in three ovarian cancer cell lines without any cytotoxic effects on untransformed stromal mesothelia.
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•Proteomic signatures acquired for distinct morphological OVCAR-3 cell phenotypes•Captured perturbed reaction modules associated with phenotype transition using GSMM•Model predicts oseltamivir to reverse metabolic flux-driven phenotypic transition•Oseltamivir inhibits spheroidogenesis across three ovarian cancer cell lines
Physiology; Mathematical biosciences; Proteomics; Cancer
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