Biology subjects

West, J.

Publications and source records attributed to West, J..

At least 73 records · Page 4Linked to original sources

bioRxiv2019

Metabolic Profiling of Aortic Stenosis and Hypertrophic Cardiomyopathy Identifies Mechanistic Contrasts in Substrate Utilisation

BackgroundAortic stenosis (AS) and hypertrophic cardiomyopathy (HCM) are highly distinct disorders leading to left ventricular hypertrophy (LVH), but whether cardiac metabolism substantially differs between these in humans remains to be elucidated.\n\nMethodWe undertook a detailed invasive (aortic root and coronary sinus) metabolic profiling in patients with severe AS and HCM in comparison to non-LVH controls, to investigate cardiac fuel selection and metabolic remodelling. These patients were assessed under different physiological states (at rest and during stress induced by pacing). The identified changes in the metabolome were further validated by metabolomic and orthogonal transcriptomic analysis, in separately recruited patient cohorts.\n\nResultsWe identified a highly discriminant metabolomic signature in severe AS characterised by striking accumulation of long-chain acylcarnitines, intermediates of long-chain transport and fatty acid metabolism, and validated this in a separate cohort. Mechanistically, we identify a down-regulation in the PPAR- transcriptional network, including expression of genes regulating FAO.\n\nConclusionsWe present a comprehensive analysis of changes in the metabolic pathways (transcriptome to metabolome) in severe AS, and its comparison to HCM. Our results demonstrate fundamental distinctions in substrate preference between AS and HCM, highlighting insufficient long-chain FAO, and the PPAR- signalling network as a specific metabolic therapeutic target in AS.

systems biology↗

bioRxiv2019

Macrophage-mediated immunoediting drives ductal carcinoma evolution: Space is the game changer

Under normal conditions, the immune system is capable of rapidly detecting and eliminating potentially dangerous entities, including tumor cells. Due to intense selection pressure imposed by the immune response, tumor cells often evolve strategies to avoid elimination in a process known as immunoediting. It is less known how the evolutionary response to immune predation is altered by context. We explore the evolution of immune escape strategies in ductal cancers, a natural case in which to study evolution in different contexts: inside and outside of ducts. We highlight the role of macrophages as a source of \"public goods,\" releasing diffusible factors (reactive oxygen species and growth factors). Immunohistochemistry reveals differences between macrophage densities of invasive ductal carcinomas and non-invasive ductal carcinomas in situ. For the first time, immunohistochemistry (IHC) imaging data comparing DCIS to IDC were used to initialize mechanistic agent-based models of evolutionary dynamics. By using IHC to map the initial conditions of a growing tumor, we show that spatial competition and structure influence transient dynamics during invasion. These dynamics are context-dependent, a conclusion that may be missed from interpreting imaging or non-spatial modeling alone. Before invasion, the presence of macrophages correlate with shorter ductal breach times. After invasion, tumors may employ a \"pioneer-engineer\" strategy where pioneering immunoresistant cells on the tumors edge stimulate the release of M1-macrophage-derived reactive oxygen species, degrading surrounding stroma. Behind the invasive edge, the engineering immunosuppressive cells promote the release of M2-macrophage-derived growth factors, providing a long-term immune escape strategy. Together, mathematical modeling and image analysis highlight the crucial role tumor-associated macrophages play in immune escape and invasion, both inside and outside of ducts.

cancer biology↗

bioRxiv2019

Clonal Architecture of the Epidermis: Homeostasis Limits Keratinocyte Evolution

The skin is the largest human organ, functioning to serve as the protective barrier to the harsh, outside world. Recent studies have revealed that large numbers of somatic mutations accumulate in normal tissue, which can be used to infer skin cell dynamics1-5. Here we present the first realistic, cell-genome mechanistic epidermal model that shows homeostasis imposes a characteristic log-linear subclone size distribution for both neutral and oncogenic driver mutations, where the largest skin subclones are the oldest subclones. Because homeostasis inherently limits proliferation and therefore clonal sweeps, selection for driver mutations (NOTCH1 and TP53) in normal epidermis is instead conferred by greater persistence, which leads to larger subclone sizes. These results highlight how the integration of mechanistic modeling with genomic data provide novel insights into the evolutionary cell dynamics of normal human homeostatic tissues.

evolutionary biology↗

bioRxiv2019

Tissue structure accelerates evolution: premalignant sweeps precede neutral expansion

Cancer has been hypothesized to be a caricature of the renewal process of the tissue of origin: arising from (and maintained by) small subpopulations capable of continuous growth1. The strong influence of the tissue structure has been convincingly demonstrated in intestinal cancers where adenomas grow by the fission of stem-cell-maintained glands influenced by early expression of abnormal cell mobility in cancer progenitors2, 3. So-called "born to be bad" tumors arise from progenitors which may already possess the necessary driver mutations for malignancy4, 5 and metastasis6. These tumors subsequently evolve neutrally, thereby maximizing intratumoral heterogeneity and increasing the probability of therapeutic resistance. These findings have been nuanced by the advent of multi-region sequencing, which uses spatial and temporal patterns of genetic variation among competing tumor cell populations to shed light on the mode of tumor evolution (neutral or Darwinian) and also the tempo4, 7-11. Using a classic, well-studied model of tumor evolution (a passenger-driver mutation model12-16) we systematically alter spatial constraints and cell mixing rates to show how tissue structure influences functional (driver) mutations and genetic heterogeneity over time. This model approach explores a key mechanism behind both inter-patient and intratumoral tumor heterogeneity: competition for space. Initial spatial constraints determine the emergent mode of evolution (neutral to Darwinian) without a change in cell-specific mutation rate or fitness effects. Transition from early Darwinian to late neutral evolution is accelerated by the combination of two factors: spatial constraints and well-timed dispersal events.

cancer biology↗

bioRxiv2019

Genomic programming of antigen cross-presentation in IRF4-expressing human Langerhans cells

Langerhans cells (LCs) in the epidermis present MHC I and MHC II-restricted antigens thereby priming either CD8 or CD4 T cell immune responses. The genomic programs and transcription factors regulating antigen presentation in LCs remain to be elucidated. We show human LCs are highly efficient in MHC I-antigen cross-presentation but lack the transcription factor IRF8 that is critical in dendritic cells. LC migration from the epidermis enhances their ability to cross-present antigens and is accompanied by the induction of the transcription factor IRF4, whose expression is correlated by scRNA-seq with genes involved in ubiquitin-dependent protein degradation. Chromatin profiling reveals enrichment of EICE and AICE composite DNA binding motifs in regulatory regions of antigen-presentation genes, which can be recognized by IRF4 in conjunction with PU.1 or BATF3 expressed in LCs. Thus, the genomic programming of human LCs including inducible expression of IRF4 with enhanced cross-presentation distinguishes them from conventional dendritic cells.

immunology↗

bioRxiv2018

Which author is which? Gender Authorship Position in Aquaculture Literature

Examining authorship position in aquaculture facilitates an improved understanding of status of women in the discipline, as authorship is a critical factor in professional success. In a review of more than eight million papers in the JSTOR Corpus across disciplines, West et al. 2013 found that men predominate in the first and last author positions and women are underrepresented in single-authored papers. Other studies have assessed women authorship, and found that a gender gap in published literature persists. This study applies the large sample size and methodology of West et al. 2013 to the broad discipline of aquaculture, and compares these results to gender authorship in the International Aquaculture Curated Database (IACD) - a compilation of 543 peer-reviewed publications supported by four international aquaculture programs headquartered at Oregon State University -- and two curated databases in the JSTOR in the Web of Science.\n\nResults reveal that the percentage of women authors (13.8%) was similar for the JSTOR aquaculture subsample and the IACD (15.7%), yet significantly lower for that of the Web of Science database (3.7%). Women are not well represented any of the databases, and remain underrepresented as authors in any position in aquaculture journals. To contextualize our findings, we examined the number of women graduates in agricultural, biological, natural, and social sciences who earned degrees in the U.S. from 1991-2015. Results from the U.S. Department of Educations National Center for Education Statistics and the percent of female graduates in the IACD show that the percent of women graduates each year has increased with women representing more than 50% of graduates, providing contextualization for the proportion of women in the discipline. Learning how authorship has changed in the aquaculture discipline over the recent decades is critical for promoting gender equity for future aquaculture scholarship and the sustainability of the professional discipline.

scientific communication and education↗

bioRxiv2018

Towards multi-drug adaptive therapy

A new ecologically inspired paradigm in cancer treatment known as \"adaptive therapy\" capitalizes on competitive interactions between drug-sensitive and drug-resistant subclones. The goal of adaptive therapy is to maintain a controllable stable tumor burden by allowing a significant population of treatment sensitive cells to survive. These, in turn, suppress proliferation of the less fit resistant populations. However, there remain several open challenges in designing adaptive therapies, particularly in extending these therapeutic concepts to multiple treatments. We present a cancer treatment case study (metastatic castrate resistant prostate cancer) as a point of departure to illustrate three novel concepts to aid the design of multi-drug adaptive therapies. First, frequency-dependent \"cycles\" of tumor evolution can trap tumor evolution in a periodic, controllable loop. Second, the availability and selection of treatments may limit the evolutionary \"absorbing region\" reachable by the tumor. Third, the velocity of evolution significantly influences the optimal timing of drug sequences.

cancer 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↗