Biology subjects

West, J.

Publications and source records attributed to West, J..

16 recordsLinked to original sources

bioRxiv2026

The filopodial scaffold polyphosphate dictates cell adhesion-versus-invasion decisions

Inorganic polyphosphate (polyP) is an ancient polymer conserved across all life, serving cell type and location specific functions in every major compartment. Yet its role at the plasma membrane, where it accumulates to peak levels in many primary cells, is largely unknown. Here we identify polyP as a stabilizing component of filopodia, actin based membrane protrusions that govern cell adhesion, contact inhibition, and chemotaxis. Elevating cellular polyP increases filopodial stability and enhances cell adhesion, whereas reducing polyP accelerates filopodial disassembly and promotes cell migration. Mechanistically, we find that polyP acts as a structural filopodial scaffold, recruiting and organizing IRSp53, a membrane curvature inducing protein. We show that metastatic fibroblasts and breast cancer organoids carry markedly reduced and intracellularly reorganized polyP levels relative to their non transformed counterparts. Restoring endogenous polyP via lipid nanoparticle delivery suppresses their invasive phenotypes and reverses prometastatic gene expression signatures, implicating polyP as a primordial tumor suppressor.

cell biology↗

bioRxiv2018

Evolutionary exploitation of PD-L1 expression in hormone receptor positive breast cancer

Based on clinical data from hormone positive breast cancer patients, we determined that there is a potential tradeoff between reducing tumor burden and altering metastatic potential when administering combination therapy of aromatase inhibitors and immune checkpoint inhibitors. While hormone-deprivation therapies serve to reduce tumor size in the neoadjuvant setting pre-surgery, they may induce tumors to change expression patterns towards a metastatic phenotype. We used mathematical modeling to explore how the timing of the therapies affects tumor burden and metastatic potential with an eye toward developing a dynamic prognostic score and reducing both tumor size and risk of metastasis.

cancer biology↗

bioRxiv2018

Regulation of Cell-Type-Specific Transcriptomes by miRNA Networks During Human Brain Development

MicroRNAs (miRNAs) regulate many cellular events by regulating hundreds of mRNA transcripts. However, it is unclear how miRNA-mRNA interactions are contextualized into the framework of transcriptional heterogeneity among closely related cells of the developing human brain. By combining the multiple complementary approaches, AGO2-HITS-CLIP, single-cell profiling and bipartite network analysis, we show that the miRNA-mRNA network operates as functional modules related to cell-type identities and undergo dynamic transitions during brain development.

developmental biology↗

bioRxiv2018

Efficient propagation of misfolded tau between individual neurons occurs in absence of degeneration

In Alzheimers disease, misfolded tau protein propagates through the brain in a prion-like manner along connected circuits. Tauopathy correlates with significant neuronal death, but the links between tau aggregation, propagation, neuronal dysfunction and death remain poorly understood, and the direct functional consequences for the neuron containing the tau aggregates are unclear. Here, by monitoring individual neurons within a minimal circuit, we demonstrate that misfolded tau efficiently spreads from presynaptic to postsynaptic neurons. Within postsynaptic cells, tau aggregates initially in distal axons, while proximal axons remain free of tau pathology. In the presence of tau aggregates neurons display axonal transport deficits, but remain viable and electrically competent. This shows that misfolded tau species are not immediately toxic to neurons, and suggests that propagation of misfolded tau is an early event in disease, occurring prior to neuronal dysfunction and cell death.

neuroscience↗

bioRxiv2018

The immune checkpoint kick start: Optimization of neoadjuvant combination therapy using game theory

An upcoming clinical trial at the Moffitt Cancer Center for women with stage 2/3 ER+breast cancer combines an aromatase inhibitor and a PD-L1 checkpoint inhibitor, and aims to lower a preoperative endocrine prognostic index (PEPI) that correlates with relapse-free survival. PEPI is fundamentally a static index, measured at the end of neoadjuvant therapy before surgery. We develop a mathematical model of the essential components of the PEPI score in order to identify successful combination therapy regimens that minimize both tumor burden and metastatic potential, based on time-dependent trade-offs in the system. We consider two molecular traits, CCR7 and PD-L1 which correlate with treatment response and increased metastatic risk. We use a matrix game model with the four phenotypic strategies to examine the frequency-dependent interactions of cancer cells. This game was embedded into an ecological model of tumor population growth dynamics. The resulting model predicts both evolutionary and ecological dynamics that track with changes in the PEPI score. We consider various treatment regimens based on combinations of the two therapies with drug holidays. By considering the trade off between tumor burden and metastatic potential, the optimal therapy plan was found to be a 1 month kick start of the immune checkpoint inhibitor followed by five months of continuous combination therapy. Relative to a protocol with both therapeutics given together from the start, this delayed regimen results in transient sub-optimal tumor regression while maintaining a phenotypic constitution that is more amenable to fast tumor regression for the final five months of therapy. The mathematical model provides a useful abstraction of clinical intuition, enabling hypothesis generation and testing of clinical assumptions.

cancer biology↗

bioRxiv2018

Saracatinib and Dasatinib Fail To Prevent Heritable Pulmonary Arterial Hypertension

Evidence suggests that the deregulation of SRC Family Kinases may play a role in the development of heritable pulmonary arterial hypertension, associated with BMPR2 mutations. The truncated c-terminus of the BMPR2 protein is known to increase the phosphorylation and downstream activity of SRC tyrosine kinases. To test the hypothesis that the inhibition of SRC can prevent heritable PAH due to a BMPR2 mutation, we exposed BMPR2 mutant mice to SRC inhibitors, saracatinib and dasatinib, to block the SRC activation caused by the BMPR2 mutation. Saracatinib and dasatinib failed to prevent the development of PAH in BMPR2 mutant mice. Increased pressure in the right ventricle was not normalized and muscularization of large blood vessels was not reduced when compared to wild type mice. Inhibiting SRCs phosphorylation does not prevent heritable PAH, and thus supports evidence that SRCs aberrant localization and trafficking in PAH plays a more critical role in disease development.

molecular biology↗

bioRxiv2018

Tripal Developer Toolkit

Tripal is an open-source biological community database construction toolkit utilizing the content management system Drupal. Tripal is used to make biological, genetic and genomic data more discoverable, shareable, searchable, and standardized. As funding for community level genomics databases declines, Tripals open source codebase provides a means for sites to be built and maintained with a minimal investment in staff and new development. Tripal is ultimately as strong as the community of sites and developers that use it. We present a set of developer tools that will make building and maintaining Tripal 3 sites easier for new and returning users. These tools break down barriers to entry such as setting up developer and testing environments, acquiring and loading test datasets, working with controlled vocabulary terms, and writing new Drupal classes.

bioinformatics↗

bioRxiv2018

C1 CAGE detects transcription start sites and enhancer activity at single-cell resolution

Single-cell transcriptomic profiling is a powerful tool to explore cellular heterogeneity. However, most of these methods focus on the 3-end of polyadenylated transcripts and provide only a partial view of the transcriptome. We introduce C1 CAGE, a method for the detection of transcript 5-ends with an original sample multiplexing strategy in the C1 microfluidic system. We first quantified the performance of C1 CAGE and found it as accurate and sensitive as other methods in C1 system. We then used it to profile promoter and enhancer activities in the cellular response to TGF-{beta} of lung cancer cells and discovered subpopulations of cells differing in their response. We also describe enhancer RNA dynamics revealing transcriptional bursts in subsets of cells with transcripts arising from either strand within a single-cell in a mutually exclusive manner, which was validated using single molecule fluorescence in-situ hybridization.

genomics↗

bioRxiv2018

A multidisciplinary approach towards identification of novel antibiotic scaffolds for Acinetobacter baumannii

Research efforts to discover potential new antibiotics for Gram-negative bacteria suffer from high attrition rates due to the synergistic action of efflux systems and the limited permeability of the outer membrane (OM). One potential strategy to overcome the OM permeability barrier is to identify small molecules that are natural substrates for abundant OM channels, and to use such compounds as scaffolds for the design of efficiently-permeating antibacterials. Here we present a multidisciplinary approach to identify such potential small-molecule scaffolds. Focusing on the pathogenic bacterium Acinetobacter baumannii, we use OM proteomics to identify DcaP as the most abundant channel under various conditions that are relevant for infection. High-resolution X-ray structure determination of DcaP surprisingly reveals a trimeric, porin-like structure and suggests that dicarboxylic acids are potential transport substrates. Electrophysiological experiments and allatom molecular dynamics simulations confirm this notion and provide atomistic information on likely permeation pathways and energy barriers for several small molecules, including a clinically-relevant {beta}-lactamase inhibitor. Our study provides a general blueprint for the identification of molecular scaffolds that will inform the rational design of future antibacterials.

microbiology↗

bioRxiv2018

Cellular cooperation shapes tumor growth: a statistical mechanics mathematical model

A tumor is made up of a heterogeneous collection of cell types all competing on a fitness landscape mediated by micro-environmental conditions that dictate their interactions. Despite the fact that much is known about cell signaling and cellular cooperation, the specifics of how the cell-to-cell coupling and the range over which this coupling acts affect the macroscopic tumor growth laws that govern total volume, mass, and carrying capacity remain poorly understood. We develop a statistical mechanics approach that focuses on the total number of possible states each cell can occupy, and show how different assumptions on correlations of these states gives rise to the many different macroscopic tumor growth laws used in the literature. Although it is widely understood that molecular and cellular heterogeneity within a tumor is a driver of growth, here we emphasize that focusing on the functional coupling of these states at the cellular level is what determines macroscopic growth characteristics.\n\nSignificance statementA mathematical model relating tumor heterogeneity at the cellular level to tumor growth at the macroscopic level is described based on a statistical mechanics framework. The model takes into account the number of accessible states available to each cell as well as their long-range coupling (population cooperation) to other cells. We show that the degree to which cell populations cooperate determine the number of independent cell states, which in turn dictates the macroscopic (volumetric) growth law. It follows that targeting cell-to-cell interactions could be a way of mitigating and controlling tumor growth.

cancer biology↗

bioRxiv2018

Optimizing chemo-scheduling based on tumor growth rates

We review the classic tumor growth and regression laws of Skipper and Schable based on fixed exponential growth assumptions, and Norton and Simons law based on a Gompertzian growth assumption. We then discuss ways to optimize chemotherapeutic scheduling using a Moran process evolutionary game-theory model of tumor growth that incorporates more general dynamical and evolutionary features of tumor cell kinetics. Using this model, and employing the quantitative notion of Shannon entropy which assigns high values to low-dose metronomic (LDM) therapies, and low values to maximum tolerated dose (MTD) therapies, we show that low-dose metronomic strategies can outperform maximum tolerated dose strategies, particularly for faster growing tumors. The general concept of designing different chemotherapeutic strategies for tumors with different growth characteristics is discussed.

cancer biology↗

bioRxiv2018

Competitive release in tumors

Competitive release is a bedrock principle of coevolutionary ecology and population dynamics. It is also the main mechanism by which heterogeneous tumors develop chemotherapeutic resistance. Understanding, controlling, and exploiting this important mechanism represents one of the key challenges and potential opportunities of current medical oncology. The development of sophisticated mathematical and computational models of coevolution among clonal and sub-clonal cell populations in the tumor ecosystem can guide us in predicting and shaping various responses to perturbations in the fitness landscape which is altered by chemo-toxic agents. This in turn can help us design adaptive chemotherapeutic strategies to combat the release resistant cells.

cancer biology↗

bioRxiv2018

Osteoclasts control sensory neurons axonal growth through epidermal growth factor receptor signaling

The patterning of peripheral innervation is accomplished through the tissue expression, in specific space and timeframe, of attractive or repulsive axonal guidance cues. At the bone microenvironment, neurotrophic factors such as nerve growth factor, brain-derived neurotrophic factor, vascular endothelial growth factor, netrin-1 and others were described to regulate the nerve ingrowth towards the bone compartment, by acting directly on receptors expressed at the nerve terminals. Interestingly, besides the gradient of soluble factors, neurons were described to be responsive to extracellular vesicles (EV) derived from myelinating cells and mesenchymal stem cells. Here we provide evidence on a new mechanism by which peripheral innervation can be coordinated. We show that sensory nerves outgrowth and electric signal propagation are dependent on the EV secreted by osteoclasts, the bone resorbing cells. Furthermore, we demonstrate that the axonal sprouting is achieved through the activation of epidermal-growth factor receptor (EGFR) family signaling pathway. We proved that the EV-depleted osteoclast secretome leads to a significant decrease of neurons firing rate and axonal sprouting, concomitant with a decrease of EGFR/ErbB2 activation levels. Excitingly, the proteomic analysis of the osteoclast-derived EV cargo shows a high correlation with synaptic components reinforcing the role on sensory neurons/osteoclast crosstalk. Our findings that osteoclast-derived EV hold effect in axonal outgrowth, contributing actively to the dynamics of the sensory neurons sprouting and electrophysiology, is a step toward unraveling target mechanisms to control electrical signal propagation and nerve fibers sprouting and consequently open new avenues for the development of innovative therapies to control bone pain. Significance StatementSensory nerve fibers sprouting in bone pathologies is highly associated with pain. Thus, understanding the mechanisms behind sensory nerves ingrowth, sprouting and electrical activity, within the bone compartment, is essential for improving the strategies to overcome pain in bone disorders. We provide a new mechanism on the sensory nerves sprouting, indicating that the effect is dependent on the extracellular vesicles (EV) released by osteoclasts, through the epidermal growth factor receptor family targeting, by integrin independent pathways. We show different electrophysiology patterns being triggered in the presence of osteoclasts secretome and the abolishment of sensory neurons firing rate in EV-depleted conditions. Overall, our results elucidate novel mechanisms on the peripheral nerves sprouting, essential for pursuing new targets for bone pain therapies.

cell biology↗

bioRxiv2017

Targeting the Untargetable: Predicting Pramlintide Resistance Using a Neural Network Based Cellular Automata

De novo resistance is a major issue for the use of targeted anticancer drugs in the clinic. By integrating experimental data we have created a hybrid neural network/agent-based model to simulate the evolution and spread of resistance to the drug Pramlintide in cutaneous squamous cell carcinoma. Our model can eventually be used to predict patient responses to the drug and thus enable clinicians to make decisions regarding personalized, precision treatment regimes for patients.

cancer biology↗

bioRxiv2017

Nonlinear dynamical shaping of the fitness landscape of an evolving tumor to combat competitive release

The development of chemotherapeutic resistance resulting in tumor relapse is largely the consequence of the mechanism of competitive release of pre-existing resistant tumor cells selected for regrowth after chemotherapeutic agents attack the previously dominant chemo-sensitive population. We introduce a prisoners dilemma mathematical model based on the replicator of three competing cell populations: healthy (cooperators), sensitive (defectors), and resistant (defectors) cells. The model is shown to recapitulate prostate-specific antigen measurement data from three clinical trials for metastatic castration-resistant prostate cancer patients treated with 1) prednisone, 2) mitoxantrone and prednisone and 3) docetaxel and prednisone. Continuous maximum tolerated dose schedules reduce the sensitive cell population, initially shrinking tumor volume, but subsequently \"release\" the resistant cells to re-populate and re-grow the tumor in a resistant form. Importantly, a model fit of prostate data shows the emergence of a positive fitness cost associated with a majority of patients for each drug, without predetermining a cost in the model a priori. While the specific mechanism associated with this cost may be very different for each of the drugs, a measurable fitness cost emerges in each. The evolutionary model allows us to quantify responses to conventional therapeutic strategies as well as to design adaptive strategies.

cancer biology↗

bioRxiv2017

Chemotherapeutic dose scheduling based on tumor growth rates: the case for low dose metronomic high entropy therapies

We extend classical tumor regression models, such as the Norton-Simon hypothesis, from instantaneous regression rates (i.e. the derivative) to the cumulative effect (i.e. the integral) over one (or many) cycles of chemotherapy. To achieve this end, we use a stochastic Moran process model of tumor cell kinetics, coupled with a prisoners dilemma game-theoretic cell-cell interaction model to design chemotherapeutic strategies tailored to different tumor growth characteristics. Using the Shannon entropy as a novel tool to quantify the success of dosing strategies, we contrast maximum tolerated dose (MTD) strategies as compared with low dose, high density metronomic strategies (LDM) for tumors with different growth rates. Our results show that LDM strategies can outperform MTD strategies in total tumor cell reduction (TCR). The advantage is magnified for fast growing tumors that thrive on long periods of unhindered growth without chemotherapy drugs present and is not evident after a single cycle of chemotherapy, but grows after each subsequent cycle of repeated chemotherapy. The model supports the concept of designing different chemotherapeutic schedules for tumors with different growth rates and develops quantitative tools to optimize these schedules for maintaining low volume tumors. The evolutionary model we introduce in this paper is compared with regression data from murine models and shown to be in good agreement.\n\nMajor FindingsModel simulations show that metronomic (low dose, high density) therapies can outperform maximum tolerated dose (high dose, low density) therapies. This is due to the fact that tumor cell reduction is more sensitive to changes in dose density than changes in dose concentration, especially for faster growing tumors. This effect is negligible after a single cycle of chemotherapy, but magnified after many cycles. The model also allows for novel chemotherapeutic schedules and quantifies their performance according to tumor growth rate.

cancer biology↗