Using lean methodology to decrease wasted RN time in seeking supplies in emergency departments.

BACKGROUND: Timely stocking of essential supplies in an emergency department (ED) is crucial to efficient and effective patient care. OBJECTIVE: The objective of this study was to decrease wasted nursing time in obtaining needed supplies in an ED through the use of Lean process controls. METHODS: As part of a Lean project, the team conducted a "before and after" prospective observation study of ED nurses seeking supplies. Nurses were observed for an entire shift for the time spent outside the patient room obtaining supplies at baseline and after implementation of a point-of-use storage system. RESULTS: Before implementation, nurses were leaving patient rooms a median of 11 times per 8-hour shift (interquartile range [IQR], 8 times per 8-hour shift) and 10 times per 12-hour shift (IQR, 23 times per 12-hour shift). After implementation of the new system, the numbers decreased to 2.5 per 8-hour shift (IQR, 2 per 8-hour shift) and 1 per 12-hour shift (IQR, 1 per 12-hour shift). CONCLUSION: A redesigned process including a standardized stocking system significantly decreases the number of searches by nurses for supplies.

Divergent transcriptomic signatures from putative mesenchymal stimuli in glioblastoma cells.

In glioblastoma, a mesenchymal phenotype is associated with especially poor patient outcomes. Various glioblastoma microenvironmental factors and therapeutic interventions are purported drivers of the mesenchymal transition, but the degree to which these cues promote the same mesenchymal transitions and the uniformity of those transitions, as defined by molecular subtyping systems, is unknown. Here, we investigate this question by analyzing publicly available patient data, surveying commonly measured transcripts for mesenchymal transitions in glioma-initiating cells (GIC), and performing next-generation RNA sequencing of GICs. Analysis of patient tumor data reveals that TGFß, TNFα, and hypoxia signaling correlate with the mesenchymal subtype more than the proneural subtype. In cultured GICs, the microenvironment-relevant growth factors TGFß and TNFα and the chemotherapeutic temozolomide promote expression of commonly measured mesenchymal transcripts. However, next-generation RNA sequencing reveals that growth factors and temozolomide broadly promote expression of both mesenchymal and proneural transcripts, in some cases with equal frequency. These results suggest that glioblastoma mesenchymal transitions do not occur as distinctly as in epithelial-derived cancers, at least as determined using common subtyping ontologies and measuring response to growth factors or chemotherapeutics. Further understanding of these issues may identify improved methods for pharmacologically targeting the mesenchymal phenotype in glioblastoma.

A Histone Methylation-MAPK Signaling Axis Drives Durable Epithelial-Mesenchymal Transition in Hypoxic Pancreatic Cancer.

The tumor microenvironment in pancreatic ductal adenocarcinoma (PDAC) plays a key role in tumor progression and response to therapy. The dense PDAC stroma causes hypovascularity, which leads to hypoxia. Here, we showed that hypoxia drives long-lasting epithelial-mesenchymal transition (EMT) in PDAC primarily through a positive-feedback histone methylation-MAPK signaling axis. Transformed cells preferentially underwent EMT in hypoxic tumor regions in multiple model systems. Hypoxia drove a cell autonomous EMT in PDAC cells, which, unlike EMT in response to growth factors, could last for weeks. Furthermore, hypoxia reduced histone demethylase KDM2A activity, suppressed PP2 family phosphatase expression, and activated MAPKs to post-translationally stabilize histone methyltransferase NSD2, leading to an H3K36me2-dependent EMT in which hypoxia-inducible factors played only a supporting role. Hypoxia-driven EMT could be antagonized in vivo by combinations of MAPK inhibitors. Collectively, these results suggest that hypoxia promotes durable EMT in PDAC by inducing a histone methylation-MAPK axis that can be effectively targeted with multidrug therapies, providing a potential strategy for overcoming chemoresistance. SIGNIFICANCE: Integrated regulation of histone methylation and MAPK signaling by the low-oxygen environment of pancreatic cancer drives long-lasting EMT that promotes chemoresistance and shortens patient survival and that can be pharmacologically inhibited. See related commentary by Wirth and Schneider, p. 1739.

An integrated mechanistic and data-driven computational model predicts cell responses to high- and low-affinity EGFR ligands.

The biophysical properties of ligand binding heavily influence the ability of receptors to specify cell fates. Understanding the rules by which ligand binding kinetics impact cell phenotype is challenging, however, because of the coupled information transfers that occur from receptors to downstream signaling effectors and from effectors to phenotypes. Here, we address that issue by developing an integrated mechanistic and data-driven computational modeling platform to predict cell responses to different ligands for the epidermal growth factor receptor (EGFR). Experimental data for model training and validation were generated using MCF7 human breast cancer cells treated with the high- and low-affinity ligands epidermal growth factor (EGF) and epiregulin (EREG), respectively. The integrated model captures the unintuitive, concentration-dependent abilities of EGF and EREG to drive signals and phenotypes differently, even at similar levels of receptor occupancy. For example, the model correctly predicts the dominance of EREG over EGF in driving a cell differentiation phenotype through AKT signaling at intermediate and saturating ligand concentrations and the ability of EGF and EREG to drive a broadly concentration-sensitive migration phenotype through cooperative ERK and AKT signaling. Parameter sensitivity analysis identifies EGFR endocytosis, which is differentially regulated by EGF and EREG, as one of the most important determinants of the alternative phenotypes driven by different ligands. The integrated model provides a new platform to predict how phenotypes are controlled by the earliest biophysical rate processes in signal transduction and may eventually be leveraged to understand receptor signaling system performance depends on cell context. One-sentence summary: Integrated kinetic and data-driven EGFR signaling model identifies the specific signaling mechanisms that dictate cell responses to EGFR activation by different ligands.

MECHANISTIC AND DATA-DRIVEN MODELS OF CELL SIGNALING: TOOLS FOR FUNDAMENTAL DISCOVERY AND RATIONAL DESIGN OF THERAPY.

A full understanding of cell signaling processes requires knowledge of protein structure/function relationships, protein-protein interactions, and the abilities of pathways to control phenotypes. Computational models offer a valuable framework for integrating that knowledge to predict the effects of system perturbations and interventions in health and disease. Whereas mechanistic models are well suited for understanding the biophysical basis for signal transduction and principles of therapeutic design, data-driven models are particularly suited to distill complex signaling relationships among samples and between multivariate signaling changes and phenotypes. Both approaches have limitations and provide incomplete representations of signaling biology, but their careful implementation and integration can provide new understanding for how manipulating system variables impacts cellular decisions.

Breast Cancer Antiestrogen Resistance 3 (BCAR3) promotes tumor growth and progression in triple-negative breast cancer.

Triple-Negative Breast Cancers (TNBCs) constitute roughly 10-20% of breast cancers and are associated with poor clinical outcomes. Previous work from our laboratory and others has determined that the cytoplasmic adaptor protein Breast Cancer Antiestrogen Resistance 3 (BCAR3) is an important promoter of cell motility and invasion of breast cancer cells. In this study, we use both in vivo and in vitro approaches to extend our understanding of BCAR3 function in TNBC. We show that BCAR3 is upregulated in ductal carcinoma in situ (DCIS) and invasive carcinomas compared to normal mammary tissue, and that survival of TNBC patients whose tumors contained elevated BCAR3 mRNA is reduced relative to individuals whose tumors had less BCAR3 mRNA. Using mouse orthotopic tumor models, we further show that BCAR3 is required for efficient TNBC tumor growth. Analysis of publicly available RNA expression databases revealed that MET receptor signaling is strongly correlated with BCAR3 mRNA expression. A functional role for BCAR3-MET coupling is supported by data showing that both proteins participate in a single pathway to control proliferation and migration of TNBC cells. Interestingly, the mechanism through which this functional interaction operates appears to differ in different genetic backgrounds of TNBC, stemming in one case from potential differences in the strength of downstream signaling by the MET receptor and in another from BCAR3-dependent activation of an autocrine loop involving the production of HGF mRNA. Together, these data open the possibility for new approaches to personalized therapy for individuals with TNBCs.

Mathematical Model Predicts that Acceleration of Diabetic Wound Healing is Dependent on Spatial Distribution of VEGF-A mRNA (AZD8601).

INTRODUCTION: Pharmacologic approaches for promoting angiogenesis have been utilized to accelerate healing of chronic wounds in diabetic patients with varying degrees of success. We hypothesize that the distribution of proangiogenic drugs in the wound area critically impacts the rate of closure of diabetic wounds. To evaluate this hypothesis, we developed a mathematical model that predicts how spatial distribution of VEGF-A produced by delivery of a modified mRNA (AZD8601) accelerates diabetic wound healing. METHODS: We modified a previously published model of cutaneous wound healing based on coupled partial differential equations that describe the density of sprouting capillary tips, chemoattractant concentration, and density of blood vessels in a circular wound. Key model parameters identified by a sensitivity analysis were fit to data obtained from an in vivo wound healing study performed in the dorsum of diabetic mice, and a pharmacokinetic model was used to simulate mRNA and VEGF-A distribution following injections with AZD8601. Due to the limited availability of data regarding the spatial distribution of AZD8601 in the wound bed, we performed simulations with perturbations to the location of injections and diffusion coefficient of mRNA to understand the impact of these spatial parameters on wound healing. RESULTS: When simulating injections delivered at the wound border, the model predicted that injections delivered on day 0 were more effective in accelerating wound healing than injections delivered at later time points. When the location of the injection was varied throughout the wound space, the model predicted that healing could be accelerated by delivering injections a distance of 1-2 mm inside the wound bed when compared to injections delivered on the same day at the wound border. Perturbations to the diffusivity of mRNA predicted that restricting diffusion of mRNA delayed wound healing by creating an accumulation of VEGF-A at the wound border. Alternatively, a high mRNA diffusivity had no effect on wound healing compared to a simulation with vehicle injection due to the rapid loss of mRNA at the wound border to surrounding tissue. CONCLUSIONS: These findings highlight the critical need to consider the location of drug delivery and diffusivity of the drug, parameters not typically explored in pre-clinical experiments, when designing and testing drugs for treating diabetic wounds. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12195-021-00678-9.

Localization dynamics of endogenous fluorescently labeled RAF1 in EGF-stimulated cells.

Activation of the epidermal growth factor (EGF) receptor (EGFR) at the cell surface initiates signaling through the RAS-RAF-MAPK/ERK1/2 pathway and receptor endocytosis. Whether this signaling continues from endosomes remains unclear, because RAS is predominantly located on the plasma membrane, and the localization of endogenous RAF kinases, downstream effectors of RAS, is not defined. To examine RAF localization, we labeled endogenous RAF1 with mVenus using gene editing. From 10 to 15% of RAF1-mVenus (<2000 molecules/cell), which was initially entirely cytosolic, transiently translocated to the plasma membrane after EGF stimulation. Following an early burst of translocation, the membrane-associated RAF1-mVenus was undetectable by microscopy or subcellular fractionation, and this pool was estimated to be <200 molecules per cell. In contrast, persistent EGF-dependent translocation of RAF1-mVenus to the plasma membrane was driven by the RAF inhibitor sorafenib, which increases the affinity of Ras-GTP:RAF1 interactions. RAF1-mVenus was not found in EGFR-containing endosomes under any conditions. Computational modeling of RAF1 dynamics revealed that RAF1 membrane abundance is controlled most prominently by association and dissociation rates from RAS-GTP and by RAS-GTP concentration. The model further suggested that the relatively protracted activation of the RAF-MEK1/2-ERK1/2 module, in comparison with RAF1 membrane localization, may involve multiple rounds of cytosolic RAF1 rebinding to active RAS at the membrane.