Biology subjects

Meade, A.

Publications and source records attributed to Meade, A..

5 recordsLinked to original sources

bioRxiv2026

Oncogenic KRAS-MAPK signaling sustains a CD73 dependent therapeutic vulnerability in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is predominantly driven by oncogenic KRAS signaling and sustained by a desmoplastic, immunosuppressive microenvironment limiting therapeutic response. CD73 mediated adenosine signaling supports this immune-excluded, tumor supportive microenvironment. Whether dual targeting of KRAS-MAPK and CD73 signaling creates a therapeutic opportunity to improve tumor control remains unexplored. Analysis of KRAS mutant cancer cell lines revealed increased expression of NT5E and adenosine receptor ADORA2B. Pharmacologic and genetic suppression of oncogenic KRAS inhibited CD73 expression through a MAPK-dependent program. In syngeneic KPC tumors, conversely, CD73 inhibition with quemliclustat increased ERK phosphorylation in vivo, suggesting adaptive MAPK activation following CD73 blockade. Combined CD73 and RAS(ON) inhibition in vivo produced the strongest antitumor response, reducing endpoint tumor volume beyond either monotherapy. This combination significantly suppressed tumor proliferation and SMA-positive stroma and resulted in a substantial reduction in CD163-positive macrophage infiltration. RAS-MAPK targeted therapy was also associated with increased CD8-positive T cell infiltration and granzyme B-positive staining. As therapeutic responses in PDAC have been linked to the gut microbiome, we further examined treatment-associated changes in the microbiome. RAS-MAPK inhibition produced the most pronounced microbial alterations, which correlated with tumor volume and immune markers. Together, these findings identify KRAS-MAPK driven CD73 signaling as a therapeutic vulnerability in PDAC and support combined CD73 and RAS(ON) inhibition as a strategy to suppress tumor growth, remodel stroma, and alleviate tumor-associated immune suppression.

cancer biology↗

bioRxiv2025

Molecular Clock Dating of Deep-Time Evolution Using Complex Mixture Models

Molecular clocks are a fundamental technique in evolutionary biology for establishing the timing and tempo of organismal divergence. However, currently available molecular clock methods, which often rely on simple homogeneous substitution models, can produce inaccurate time estimates, particularly for deep-time or rapidly evolving lineages where substitution heterogeneity and saturation are common. Hereby, we introduce phyloHessian (https://github.com/evolbeginner/phyloHessianWrapper), a Julia-based software to enable the use of complex mixture substitution models in molecular dating. phyloHessian computes the phylogenetic Hessian matrix and integrates it into PAML-MCMCtrees approximate likelihood framework to conduct dating analyses. Simulations mimicking phylogenies at different timescales demonstrate that complex mixture substitution models significantly enhance the accuracy of divergence time and substitution rate estimates in deep-time phylogenies. This pattern remains consistent across a wide range of uncertainties associated with molecular clock analysis. Additionally, mixture models display greater robustness to model and calibration specifications compared to their homogeneous counterparts. Empirical analysis of ancient symbiont lineages Microsporidia and Rickettsiales with different substitution models shows that mixture models, compared to homogeneous models, yield accelerated substitution rates and in some cases significantly different divergence times, leading to a revised understanding of their host association origins. Our findings underscore the importance of incorporating complex mixture substitution models for constructing reliable evolutionary timelines and elucidating the evolutionary history of deep-time or fast-evolving lineages.

evolutionary biology↗

bioRxiv2024

Enabling Transparent Toxicokinetic Modeling for Public Health Risk Assessment

Toxicokinetics describes the absorption, distribution, metabolism, and elimination of chemicals by the body. Predictions from toxicokinetic models provide key information for chemical risk assessment. Traditionally, these predictions extrapolate from experimental animal species data (for example, in rats) to humans. More recently, toxicokinetics has been used for extrapolation from in vitro "new approach methods (NAMs)" for toxicology to in vivo. Chemical-specific in vivo toxicokinetic data are often unavailable for the thousands of chemicals in commerce. Therefore, large amounts of in vitro data measuring chemical-specific toxicokinetics have been collected. These data enable "high-throughput toxicokinetic" or HTTK modeling. The httk R package provides a library of chemical-specific data from peer-reviewed HTTK studies. httk further provides a suite of tools for parameterizing and evaluating toxicokinetic models. httk uses the open-source language MCSim to describe models for compartmental and physiologically based toxicokinetics (PBTK), MCSim can convert the model descriptions into a high-speed C code script. New models are integrated into httk using the open-source package development functionality in R, a model documentation file (R script), and the HTTK model description code file (C script). In addition to HTTK models, httk provides a series of functionalities such as unit conversion, model parameterization, Monte Carlo simulations for uncertainty propagation and biological variability, in vivo-derived data for evaluating model predictions, and other model utility functions. Here, we describe in detail how to add new HTTK models to httk and take advantage of the pre-existing data and functionality in the package. As a demonstration, we describe the integration of the gas inhalation PBTK model into httk. Modern modeling approaches, as exemplified by httk, allow for clear communication, reproducibility, and public scrutiny. The intention of httk is to provide a transparent, open-source tool for toxicokinetics, bioinformatics, and public health risk assessment. Author SummaryWe describe the integration and evaluation of new physiologically based toxicokinetic (PBTK) models into an open-source R package. Adding a new model to the R package allows a modeler to use the existing tools and data for in vitro to in vivo extrapolation (IVIVE). Integration with the R statistical analysis environment further allows model assessment. This workflow is designed to create a more transparent and reproducible approach to toxicokinetic models developed for various exposure scenarios. Here, we demonstrate the model integration and evaluation workflow with an inhalation model. Additionally, we provide an evaluation of the overall package performance as new models, data, and functionality are added over time. Our results show that transparent development of models, and use of existing data within the open-source R package format, allows for improvement of in vitro to in vivo extrapolation estimations. IVIVE is vital for advancement of 21st century human health risk assessment.

pharmacology and toxicology↗

bioRxiv2020

Phenotypic reconstruction of the last universal common ancestor reveals a complex cell

A fundamental concept in evolutionary theory is the last universal common ancestor (LUCA) from which all living organisms originated. While hypotheses regarding the phenotype of LUCA do exist, most are at best based on gene presence or absence. However, despite recent attempts to link genes and phenotypic traits in prokaryotes, it is still inherently difficult to predict phenotype based on the presence or absence of genes alone. Here, we apply a novel approach based on phylogenetically informed ancestral character reconstruction with 22 fundamental descriptors of prokaryotic cells to reconstruct LUCAs phenotype. We infer that the last universal common ancestor of all living organisms was likely an ovoid cell with a large genome, which probably had a cell wall and was actively motile. Potentially obtaining energy from the oxidation of inorganic compounds, tolerant of saltwater and thriving at temperatures above 70{degrees}C, LUCA was probably found living freely in anaerobic conditions in water of neutral pH. Our results depict LUCA as likely to be a far more complex cell than has previously been proposed, challenging the evolutionary model of increased complexity through time in prokaryotes. Given current estimates for the emergence of LUCA we suggest that early life very rapidly evolved considerable cellular complexity.

evolutionary biology↗

bioRxiv2017

150 million years of sustained increase in pterosaur flight efficiency

The long-term accumulation of biodiversity has been punctuated by remarkable evolutionary transitions that allowed organisms to exploit new ecological opportunities, and often resulted in large radiations of species. The Mesozoic flying reptiles - pterosaurs - which dominated the skies for over 150 million years (Myr), were the product of such a transition. The ancestors of pterosaurs were small and likely bipedal early archosaurs, which were certainly well adapted to terrestrial locomotion. More than 220 Myr ago, at some point in the Triassic, pterosaurs took flight and subsequently appear to have become capable and efficient flyers. However, the evolutionary processes that led to this efficiency remain enigmatic. Given the lack of proto-pterosaurs it is difficult to study how flight first evolved in this group, but we can test hypotheses about evolutionary changes to the energetics of locomotion following the transition to flight. Early pterosaurs were challenged by the c ...

evolutionary biology↗