The Predictive Link between Matrix and Metastasis

Cancer spread (metastasis) is responsible for 90% of cancer-related fatalities. Informing patient treatment to prevent metastasis, or kill all cancer cells in a patient\u27s body before it becomes metastatic is extremely powerful. However, aggressive treatment for all non-metastatic patients is detrimental, both for quality of life concerns, and the risk of kidney or liver-related toxicity. Knowing when and where a patient has metastatic risk could revolutionize patient treatment and care. In this review, we attempt to summarize the key work of engineers and quantitative biologists in developing strategies and model systems to predict metastasis, with a particular focus on cell interactions with the extracellular matrix (ECM), as a tool to predict metastatic risk and tropism

A cell–ECM screening method to predict breast cancer metastasis

Breast cancer preferentially spreads to the bone, brain, liver, and lung. The clinical patterns of this tissue-specific spread (tropism) cannot be explained by blood flow alone, yet our understanding of what mediates tropism to these physically and chemically diverse tissues is limited. While the micro- environment has been recognized as a critical factor in governing metastatic colonization, the role of the extracellular matrix (ECM) in mediating tropism has not been thoroughly explored. We created a simple biomaterial platform with systematic control over the ECM protein density and composition to determine if integrin binding governs how metastatic cells differentiate between secondary tissue sites. Instead of examining individual behaviors, we compiled large patterns of phenotypes associated with adhesion to and migration on these controlled ECMs. In combining this novel analysis with a simple biomaterial platform, we created an in vitro fingerprint that is predictive of in vivo metastasis. This rapid biomaterial screen also provided information on how b1, a2, and a6 integrins might mediate metastasis in patients, providing insights beyond a purely genetic analysis. We propose that this approach of screening many cell–ECM interactions, across many different heterogeneous cell lines, is predictive of in vivo behavior, and is much simpler, faster, and more economical than complex 3D environments or mouse models. We also propose that when specifically applied toward the question of tissue tropism in breast cancer, it can be used to provide insight into certain integrin subunits as therapeutic targets

Anomalously Diffusing and Persistently Migrating Cells in 2D and 3D Culture Environments

Appropriately chosen descriptive models of cell migration in biomaterials will allow researchers to characterize and ultimately predict the movement of cells in engineered systems for a variety of applications in tissue engineering. The persistent random walk (PRW) model accurately describes cell migration on two-dimensional (2D) substrates. However, this model inherently cannot describe subdiffusive cell movement, i.e. migration paths in which the root mean square displacement increases more slowly than the square root of the time interval. Subdiffusivity is a common characteristic of cells moving in confined environments, such as three-dimensional (3D) porous scaffolds, hydrogel networks, and in vivo tissues. We demonstrate that a generalized anomalous diffusion (AD) model, which uses a simple power law to relate the mean square displacement (MSD) to time, more accurately captures individual cell migration paths across a range of engineered 2D and 3D environments than does the more commonly used PRW model. We used the AD model parameters to distinguish cell movement profiles on substrates with different chemokinetic factors, geometries (2D vs 3D), substrate adhesivities, and compliances. Although the two models performed with equal precision for superdiffusive cells, we suggest a simple AD model, in lieu of PRW, to describe cell trajectories in populations with a significant subdiffusive fraction, such as cells in confined, 3D environments

Integrin α6 and EGFR Signaling Converge at Mechanosensitive Calpain 2

Cells sense and respond to mechanical cues from the extracellular matrix (ECM) via integrins. ECM stiffness is known to enhance integrin clustering and response to epidermal growth factor (EGF), but we lack information on when or if these mechanosensitive growth factor receptors and integrins converge intracellularly. Towards closing this knowledge gap, we combined a biomaterial platform with transcriptomics, molecular biology, and functional assays to link integrin-mediated mechanosensing and epidermal growth factor receptor (EGFR) signaling. We found that high integrin α6 expression controlled breast cancer cell adhesion and motility on soft, laminin-coated substrates, and this mimicked the response of cells to EGF stimulation. The mechanisms that drove both mechanosensitive cell adhesion and motility converged on calpain 2, an intracellular protease important for talin cleavage and focal adhesion turnover. EGF stimulation enhanced adhesion and motility on soft substrates, but required integrin α6 and calpain 2 signaling. In sum, we identified a new role for integrin α6 mechanosensing in breast cancer, wherein cell adhesion to laminin on soft substrates mimicked EGF stimulation. We identified calpain 2, downstream of both integrin α6 engagement and EGFR phosphorylation, as a common intracellular signaling node, and implicate integrin α6 and calpain 2 as potential targets to inhibit the migration of cancer cells in stiff tumor environments

Comparative Study of Multicellular Tumor Spheroid Formation Methods and Implications for Drug Screening

Improved in vitro models are needed to better understand cancer progression and bridge the gap between in vitro proof-of-concept studies, in vivo validation, and clinical application. Multicellular tumor spheroids (MCTS) are a popular method for three-dimensional (3D) cell culture, because they capture some aspects of the dimensionality, cell–cell contact, and cell–matrix interactions seen in vivo. Many approaches exist to create MCTS from cell lines, and they have been used to study tumor cell invasion, growth, and how cells respond to drugs in physiologically relevant 3D microenvironments. However, there are several discrepancies in the observations made of cell behaviors when comparing between MCTS formation methods. To resolve these inconsistencies, we created and compared the behavior of breast, prostate, and ovarian cancer cells across three MCTS formation methods: in polyNIPAAM gels, in microwells, or in suspension culture. These methods formed MCTS via proliferation from single cells or passive aggregation, and therefore showed differential reliance on genes important for cell–cell or cell–matrix interactions. We also found that the MCTS formation method dictated drug sensitivity, where MCTS formed over longer periods of time via clonal growth were more resistant to treatment. Toward clinical application, we compared an ovarian cancer cell line MCTS formed in polyNIPAAM with cells from patient-derived malignant ascites. The method that relied on clonal growth (PolyNIPAAM gel) was more time and cost intensive, but yielded MCTS that were uniformly spherical, and exhibited the most reproducible drug responses. Conversely, MCTS methods that relied on aggregation were faster, but yielded MCTS with grape-like, lobular structures. These three MCTS formation methods differed in culture time requirements and complexity, and had distinct drug response profiles, suggesting the choice of MCTS formation method should be carefully chosen based on the application required

Tumor cell–organized fibronectin maintenance of a dormant breast cancer population

Tumors can undergo long periods of dormancy, with cancer cells entering a largely quiescent, nonproliferative state before reactivation and outgrowth. To understand the role of the extracellular matrix (ECM) in regulating tumor dormancy, we created an in vitro cell culture system with carefully controlled ECM substrates to observe entrance into and exit from dormancy with live imaging. We saw that cell populations capable of surviving entrance into long-term dormancy were heterogeneous, containing quiescent, cell cycle–arrested, and actively proliferating cells. Cell populations capable of entering dormancy formed an organized, fibrillar fibronectin matrix via αvβ3 and α5β1 integrin adhesion, ROCK-generated tension, and TGFβ2 stimulation, and cancer cell outgrowth after dormancy required MMP-2–mediated fibronectin degradation. We propose this approach as a useful, in vitro method to study factors important in regulating dormancy, and we used it here to elucidate a role for fibronectin deposition and MMP activation

Tumor cell-organized fibronectin is required to maintain a dormant breast cancer population [preprint]

Tumors can undergo long periods of dormancy, with cancer cells entering a largely quiescent, non-proliferative state before reactivation and outgrowth. For a patient, these post-remission tumors are often drug resistant and highly aggressive, resulting in poor prognosis. To understand the role of the extracellular matrix (ECM) in regulating tumor dormancy, we created an in vitro cell culture system that combines carefully controlled ECM substrates with nutrient deprivation to observe entrance into and exit from dormancy with live imaging. We saw that cell populations capable of surviving entrance into long-term dormancy were heterogeneous, containing quiescent, cell cycle arrested, and actively proliferating cells. Cell populations that endured extended periods of serum-deprivation-induced dormancy formed an organized, fibrillar fibronectin matrix via αvβ3 and α5β1 integrin adhesion, ROCK-generated tension, and TGFβ2 stimulation. We surmised that the fibronectin matrix was primarily a mediator of cell survival, not proliferation, during the serum-deprivation stress, bacause cancer cell outgrowth after dormancy required MMP-2-mediated fibronectin degradation. Given the difficulty of animal models in observing entrance and exit from dormancy in real-time, we propose this approach as a new, in vitro method to study factors important in regulating dormancy, and we used it here to elucidate a role for fibronectin deposition and MMP activation

Changes in intraocular pressure in study and fellow eyes in the IVAN trial

PURPOSE: To describe changes in intraocular pressure (IOP) in the 'alternative treatments to Inhibit VEGF in Age-related choroidal Neovascularisation (IVAN)' trial (registered as ISRCTN92166560). DESIGN: Randomised controlled clinical trial with factorial design. PARTICIPANTS: Patients (n=610) with treatment naïve neovascular age-related macular degeneration were enrolled and randomly assigned to receive either ranibizumab or bevacizumab and to two regimens, namely monthly (continuous) or as needed (discontinuous) treatment. METHODS: At monthly visits, IOP was measured preinjection in both eyes, and postinjection in the study eye. OUTCOME MEASURES: The effects of 10 prespecified covariates on preinjection IOP, change in IOP (postinjection minus preinjection) and the difference in preinjection IOP between the two eyes were examined. RESULTS: For every month in trial, there was a statistically significant rise in both the preinjection IOP and the change in IOP postinjection during the time in the trial (estimate 0.02 mm Hg, 95% CI 0.01 to 0.03, p<0.001 and 0.03 mm Hg, 95% CI 0.01 to 0.04, p=0.002, respectively). There was also a small but significant increase during the time in trial in the difference in IOP between the two eyes (estimate 0.01 mm Hg, 95% CI 0.005 to 0.02, p<0.001). There were no differences between bevacizumab and ranibizumab for any of the three outcomes (p=0.93, p=0.22 and p=0.87, respectively). CONCLUSIONS: Anti-vascular endothelial growth factor agents induce increases in IOP of small and uncertain clinical significance

Development and validation of HERWIG 7 tunes from CMS underlying-event measurements

This paper presents new sets of parameters (“tunes”) for the underlying-event model of the HERWIG7 event generator. These parameters control the description of multiple-parton interactions (MPI) and colour reconnection in HERWIG7, and are obtained from a fit to minimum-bias data collected by the CMS experiment at s=0.9, 7, and 13Te. The tunes are based on the NNPDF 3.1 next-to-next-to-leading-order parton distribution function (PDF) set for the parton shower, and either a leading-order or next-to-next-to-leading-order PDF set for the simulation of MPI and the beam remnants. Predictions utilizing the tunes are produced for event shape observables in electron-positron collisions, and for minimum-bias, inclusive jet, top quark pair, and Z and W boson events in proton-proton collisions, and are compared with data. Each of the new tunes describes the data at a reasonable level, and the tunes using a leading-order PDF for the simulation of MPI provide the best description of the dat

MUSiC : a model-unspecific search for new physics in proton-proton collisions at root s=13TeV

Results of the Model Unspecific Search in CMS (MUSiC), using proton-proton collision data recorded at the LHC at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb(-1), are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.Peer reviewe