Biology subjects

Richards, R.

Publications and source records attributed to Richards, R..

8 recordsLinked to original sources

bioRxiv2026

Low-dose radiopharmaceutical therapy enhances the efficacy of B7-H3 CAR T cells in murine metastatic neuroblastoma

Background: Chimeric antigen receptor (CAR) T cell therapy has had clinical success in hematologic malignancies, but limited efficacy is seen in solid tumors. In this study, we investigated whether systemic CAR T cell therapy could be enhanced in metastatic models of neuroblastoma when combined with radiopharmaceutical therapy (RPT). Methods: Non-irradiated or irradiated tumor cells were co-cultured with CAR T cells (1:1) in vitro and supernatant media was subsequently collected for cytokines analyses. CAR T cell phenotypes were characterized by flow cytometry including checkpoint marker expression. Xenograft models of metastatic neuroblastoma were generated in NOD-Rag1nullIL2rgnull (NRG) mice. Tumor-bearing mice received 1.8 Gy of radiation delivered by 177Lu-NM600 RPT five days after tumor implantation. Nine days after RPT, CAR T cells were administered intravenously. To evaluate tumor burden, mice were imaged weekly for 4 weeks. Results: In models of metastatic neuroblastoma, 177Lu-NM600 RPT significantly increased overall survival when combined with CAR T cell therapy in vivo. Pre-treatment of tumor cells with 177Lu also significantly increased CAR T cell cytotoxicity while decreasing production of IL-4 and IL-10 in vitro. Co-culture of CAR T cells with irradiated tumors led to increases in PD-1+TIM3+LAG3+ T cells, suggesting that further combination with immune checkpoint inhibitors may enhance clinical efficacy. Conclusions: Our findings demonstrate that low-dose RPT can potentiate the anti-tumor efficacy of CAR T cells in metastatic neuroblastoma. To our knowledge, this is the first report of dosimetry-based RPT being combined with CAR T cells in a metastatic solid tumor setting. These findings underscore the potential of combining RPT and CAR T cells to overcome the unique challenges of solid tumors, particularly when treating metastatic disease.

cancer biology↗

bioRxiv2025

Biophysical Modeling Elucidates Mechanistic Principles for Rational Molecular Glue Design

Molecular glues are small molecules that offer a powerful strategy to target previously "undruggable" proteins of interest (POI) by enhancing their interactions with other proteins (effector). Depending on the nature of the effectors, molecular glues can induce stabilizing sequestration or degradation of POI. However, their rational design has been hindered by a poor understanding of how kinetic parameters impact their performance. To address this, we developed a unified mathematical framework that accurately analyzes the dynamics of both glue degraders and stabilizers. Our model reveals that the strong binding affinity of the ternary complex is the key determinant of performance across both modalities, provided that the initial component concentrations and degradation rate constants are fixed. Furthermore, we demonstrate that degrader performance is ultimately limited by its catalytic efficiency and the target proteins natural half-life. We also identify distinct roles for effector abundance, showing that the relative concentrations of the effector and POI are critical for stabilizers but less so for degraders. This quantitative framework provides mechanistic principles for the rationale design and optimization of molecular glues.

molecular biology↗

bioRxiv2022

Self-paced treadmill controller algorithm based on position and speed of centre of mass

BackgroundSelf-paced treadmills are increasingly used in clinical and research settings. Using self-paced (SP) treadmills, researchers can simulate overground walking while participants can walk with different but comfortable gait speeds in a controlled environment. Several algorithms have been designed for self-paced treadmills based on data from force plates, motion capture, and even marker-less systems such as 3D depth cameras. MethodsWe present a non-linear controller that implements a self-paced algorithm integrated with treadmills. This algorithm uses the subjects centre-of-mass (CoM) position and velocity, relative to the front and back end of the treadmill as inputs. The controller continuously adjusts the treadmills belt speed via belt acceleration. The algorithm attempts to prevent the subject reaching the front and back of treadmill via minimal treadmill acceleration. FindingsThis method has been safely used in previous studies with over 410 subjects in various populations. We simulated the use of the SP algorithm with three different sensitivities (0.2, 1 and 2). The belt speed predicted by algorithm simulation in matched well with the belt speeds of experiments in (Gait Realtime Analysis Interactive Lab (GRAIL) system. InterpretationThis algorithm is integrated with a VR environment in which the subject can be immersed and even be mechanically perturbed. Additionally, this algorithm can be implemented in other treadmills where CoM position is known. We encourage researchers to use and build upon our well-established SP algorithm toward a more standardized SP algorithm in different gait scenarios across various instrumented treadmills with different populations.

bioengineering↗

bioRxiv2020

Drug GRADE: an integrated analysis of population growth and cell death reveals drug- specific and cancer subtype-specific response profiles

In the pre-clinical evaluation of anti-cancer drugs, two different measurement approaches are used: relative viability, which scores an amalgam of growth arrest and cell death, and fractional viability, which more specifically scores the degree of cell killing. In this study, we directly quantify relationships between drug-induced growth inhibition and drug-induced cell death by counting live and dead cells over time using quantitative microscopy. We find that most drugs affect both growth and death, but with different proportions and with different relative timing. These features lead to a non-uniform and unpredictable relationship between the canonical relative and fractional drug response measurements. To unify these disparate measurements, we create a new data visualization and data analysis platform, called drug GRADE, which characterizes the degree to which cell death contributes to an observed reduction in population size for any given drug. Our new method reveals both drug- and genotype-specific drug responses, which are not captured using traditional pharmaco-metrics. Taken together, this study highlights the extremely idiosyncratic nature of drug-induced growth and cell death and provides a new analysis tool for quantitatively evaluating these behaviors.

systems biology↗

bioRxiv2019

Drug Combination Antagonism and Single Agent Dominance Result from Differences in Death Activation Kinetics

Therapeutic regimens for cancer generally involve drugs used in combinations. Most prior work has focused on identifying and understanding synergistic drug-drug interactions; however, understanding sources of antagonistic interactions remains an important and understudied issue. To enrich for antagonistic interactions and reveal common features of these drug combinations, we screened all pairwise combinations of drugs characterized as canonical activators of different forms of regulated cell death. We find that this network is strongly enriched for antagonistic interactions, and in particular, enriched for an extreme form of antagonism, which we call \"single agent dominance\". Single agent dominance refers to antagonisms in which a two drug combination phenocopies one of the two agents. We find that dominance results from differences in the cell death onset time, with dominant drugs inducing death earlier and at faster rates than their suppressed counterparts. Finally, we explored the mechanisms by which parthanatotic agents dominate apoptotic agents, finding that dominance in this scenario is caused by mutually exclusive and conflicting use of PARP1. Taken together, our study reveals death activation kinetics as a predictive feature of antagonism, due to inhibitory crosstalk between cell death pathways.

systems biology↗

bioRxiv2018

4D imaging and analysis of multicellular tumour spheroid cell migration and invasion

Studying and characterising tumour cell migration is critical for understanding disease progression and for assessing drug efficacy. Whilst tumour cell migration occurs fundamentally in 3 spatial dimensions (3D), for practical reasons, most migration studies to date have performed analysis in 2D. Here we imaged live multicellular tumour spheroids with lightsheet fluorescence microscopy to determine cellular migration and invasion in 3D over time (4D). We focused on glioblastoma, which are aggressive brain tumours, where cell invasion into the surrounding normal brain remains a major clinical challenge. We developed a workflow for analysing complex 3D cell movement, taking into account migration within the spheroid as well as invasion into the surrounding matrix. This provided metrics characterising cell motion, which we used to evaluate the efficacy of chemother-apeutics on invasion. These rich datasets open avenues for further studies on drug efficacy, microenvironment composition, as well as collective cell migration and metastatic potential.

cell biology↗

bioRxiv2017

Fibroblasts from metastatic sites induce broad-spectrum drug desensitization via modulation of mitochondrial priming

Due to tumor heterogeneity, most believe that effective treatments should be tailored to the features of an individual tumor or tumor subclass. It is still unclear what information should be considered for optimal disease stratification, and most prior work focuses on tumor genomics. Here, we focus on the tumor micro-environment. Using a large-scale co-culture assay optimized to measure drug-induced cell death, we identify tumor-stroma interactions that modulate drug sensitivity. Our data show that the chemo-insensitivity typically associated with aggressive subtypes of breast cancer is not cell intrinsic, but rather a product of tumor-fibroblast interactions. Additionally, we find that fibroblast cells influence tumor drug response in two distinct and divergent manners, which were predicable based on the anatomical origin from which the fibroblasts were harvested. These divergent phenotypes result from modulation of \"mitochondrial priming\" of tumor cells, caused by secretion of inflammatory cytokines, such as IL6 and IL8, from stromal cells.

cancer biology↗

bioRxiv2017

Estimating environmental suitability

Author statementJD proposed the model, JD and RR wrote the code and performed the analysis, JD wrote the first draft of the manuscript, and all authors contributed substantially to revisions.\n\nAbstractMethods for modeling species, distributions in nature are typically evaluated empirically with respect to data from observations of species occurrence and, occasionally, absence at surveyed locations. Such models are relatively \"theory-free\". In contrast, theories for explaining species, distributions draw on concepts like fitness, niche, and environmental suitability. This paper proposes that environmental suitability be defined as the conditional probability of occurrence of a species given the state of the environment at a location. Any quantity that is proportional to this probability is a measure of relative suitability and the support of this probability is the niche. This formulation suggests new methods for presence-background modeling of species distributions that unify statistical methodology with the conceptual framework of niche theory. One method, the plug-and-play approach, is introduced for the first time. Variations on the plug-and-play approach were studied with respect to their numerical performance on 106 species from an exhaustively sampled presence/absence survey of vegetation in the Canton of Vaud, Switzerland. Additionally, we looked at the robustness of these methods to the presence of irrelevant information and sample size. Although irrelevant variables eroded the predictive performance of all methods, these methods were found to be both numerically and statistically robust.

ecology↗