Biology subjects

Elliott, R. J.

Publications and source records attributed to Elliott, R. J..

5 recordsLinked to original sources

bioRxiv2025

Phenotypic Screening Identifies Flunarizine as an Inhibitor of Radiotherapy-Induced Astrocyte Reactivity with Therapeutic Potential in Glioblastoma

Radiotherapy is part of the standard-of-care for glioblastoma, yet tumors invariably recur as incurable lesions post-treatment. Recent studies suggest that radiation-induced astrocyte reactivity fosters a tumor-supportive environment, however effective strategies targeting reactive astrocyte phenotypes are lacking. Using a novel image-based assay, we screened over 1,700 small molecule compounds, identifying 29 that inhibit radiation-induced astrocyte reactivity in human astrocytes. Among these, Flunarizine, a calcium-entry blocker approved for migraine treatment, significantly reduced astrocyte reactivity in vitro and in vivo. In a genetically engineered glioblastoma mouse model, combining Flunarizine with radiotherapy markedly improved survival without affecting unirradiated controls, indicating specificity for a radiation-induced phenotype. Mechanistically, Flunarizine inhibited radiation-induced fibrosis in vivo and directly suppressed astrocytic TGF-beta activation in vitro. Notably, Flunarizine treatment had no direct effect on primary glioblastoma cells, emphasizing its microenvironmental specificity. In conclusion, we identified Flunarizine as a promising repurposed compound capable of effectively mitigating radiation-induced astrocyte reactivity and delaying glioblastoma recurrence. This approach offers a viable therapeutic strategy to enhance current glioblastoma treatments. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=195 SRC="FIGDIR/small/664538v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@d4d0d6org.highwire.dtl.DTLVardef@1dac551org.highwire.dtl.DTLVardef@1d071ccorg.highwire.dtl.DTLVardef@1df1a72_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

A comprehensive pharmacological survey across heterogeneous patient-derived GBM stem cell models

Despite substantial drug discovery investments, the lack of any significant therapeutic advancement in the treatment of glioblastoma (GBM) over the past two decades calls for more innovation in the identification of effective treatments. The inter-and intra-patient heterogeneity of GBM presents significant obstacles to effective clinical progression of novel treatments by contributing to tumour plasticity and rapid drug resistance that confounds contemporary target directed drug discovery strategies. Phenotypic drug screening is ideally suited to heterogeneous diseases, where targeting specific oncogenic drivers have been broadly ineffective. Our hypothesis is that a modern phenotypic led approach using disease relevant patient-derived GBM stem cell systems will be the most productive approach to identifying new therapeutic targets, drug classes and future drug combinations that target the heterogeneity of GBM. In this study we incorporate a panel of patient-derived GBM stem cell lines into an automated and unbiased Cell Painting assay to quantify multiple GBM stem cell phenotypes. By screening several compound libraries at multiple concentrations across a panel of patient-derived GBM stem cells we provide the first comprehensive survey of distinct pharmacological classes and known druggable targets, including all clinically approved drug classes and oncology drug candidates upon multiple GBM stem cell phenotypes linked to cell proliferation, survival and differentiation. Our data set representing, 3866 compounds, 2.2million images and 64000 datapoints is the largest phenotypic screen carried out to date on a panel of patient-derived GBM stem cell models that we are aware of. We seek to identify agents and target classes which engender potent activity across heterogenous GBM genotypes and phenotypes, in this study we further characterize two validated target classes, histone deacetylase inhibitors and cyclin dependent kinases that exert broad and potent effects on the phenotypic and transcriptomic profiles of GBM stem cells. Here we present all validated hit compounds and their target assignments for the GBM community to explore.

cancer biology↗

bioRxiv2024

Drug combinations targeting FAK and MEK overcomes tumour heterogeneity in glioblastoma

Glioblastoma (GBM) is an aggressive brain tumour with limited treatment options and poor prognosis, largely due to its heterogeneity and the involvement of multiple intracellular signalling pathways that contribute to drug resistance. Standard therapies have not significantly improved patient outcomes over the past two decades. While recent advancements in targeted drug combination therapies, such as dabrafenib and trametinib, show promise for certain GBM subgroups, identifying drug combinations effective across the broader GBM population remains a challenge. Integrin-mediated signalling, particularly through Focal Adhesion Kinase (FAK), plays a pivotal role in GBM pathogenesis and invasion, making it a potential therapeutic target [1]. In our study, we utilized a chemogenomic screening approach to identify synergistic drug combinations that target FAK in glioblastoma. We initially employed a CRISPR-engineered GBM model to assess the effects of FAK depletion and discovered that combining FAK inhibitors with MEK inhibitors, particularly trametinib, demonstrated synergistic effects. This potent combination was validated through various 2D & 3D assays, including cell viability/apoptotic assessment, synergistic analysis, cellular imaging, and target engagement assays. The combination also effectively inhibited spheroid growth and invasion across a diverse panel of patient derived GBM stem cells. Molecular mechanisms underlying these effects included suppression of multiple kinase signalling pathways and enhanced apoptosis, elucidated using Reverse Phase Protein Array (RPPA) profiling and western blot validation. In vivo, the combination therapy significantly reduced tumour volume in orthotopic transplantation models. These findings suggest that combining FAK and MEK inhibitors represent a promising therapeutic strategy to overcome the challenges of GBM treatment.

cancer biology↗

bioRxiv2023

Morphological profiling by cell painting in human neural progenitor cells classifies hit compounds in a pilot drug screen for Alzheimer's disease

1Alzheimers disease (AD) accounts for 60-70% of dementia cases. Current treatments are inadequate and there is a need to develop new approaches to AD drug discovery. We chose to develop a cell phenotype-based drug screen centred on the AD-risk gene, SORL1, which encodes the protein SORLA. Increased AD risk has been repeatedly linked to variants in SORL1, particularly those that confer loss of, or decreased, SORLA. This is consistent with the lower SORL1 levels observed in post-mortem brain samples from individuals with AD. Consistent with its role in the endolysosomal pathway, deletion of SORL1 is associated with enlarged endosomes in neural progenitor cells (NPCs) and neurons. We, therefore, hypothesised that multiparametric, image-based phenotyping would identify features characteristic of SORL1 deletion. An automated morphological profiling assay (known as Cell Painting) was adapted to wild-type and SORL1-/- NPCs. This methodology was used to determine the phenotypic response of SORL1-/- NPCs to treatment with compounds from a small FDA/internationally-approved drug library (TargetMol, 330 compounds). We detected distinct phenotypic signatures for SORL1-/- NPCs compared to isogenic wild-type controls. Furthermore, we identified 16 approved drugs that reversed the mutant morphological signatures in NPCs derived from 3 SORL1-/- subclonal iPSC lines. Network pharmacology analysis revealed the 16 compounds belonged to five mechanistic groups: 20S proteasome, aldehyde dehydrogenase, topoisomerase I and II, and DNA synthesis inhibitors. Enrichment analysis confirmed targeting to gene sets associated with these annotated targets, and to pathways/biological processes associated with DNA synthesis/damage/repair, Proteases/proteasome and metabolism._Prediction of novel targets for some compounds revealed enrichment in pathways associated with neural cell function and AD. The findings suggest that image-based phenotyping by morphological profiling distinguishes SORL1-/- NPCs from isogenic wild-type lines, and predicts treatment responses that rescue SORL1-/--associated cellular signatures that are relevant to both SORLA function and AD. Overall, this work suggests that i) a quantitative phenotypic metric can distinguish iPSC-derived SORL1-/- NPCs from isogenic wild-type control and ii) phenotypic screening combined with multiparametric high-content image analysis is a viable option for drug repurposing and discovery in this human neural cell model of Alzheimers disease.

neuroscience↗

bioRxiv2021

High-content profiling reveals a unified model of copper ionophore dependent cell death in oesophageal adenocarcinoma

Background and AimsOesophageal adenocarcinoma (OAC) is of increasing global concern due to increasing incidence, a lack of effective treatments, and poor prognosis. Therapeutic target discovery and clinical trials have been hindered by the heterogeneity of the disease, lack of driver mutations, and the dominance of large-scale genomic rearrangements. In this work we have characterised three potent and selective hit compounds identified in an innovative high-content phenotypic screening assay. The three hits include two approved drugs; elesclomol and disulfiram, and another small molecule compound, ammonium pyrrolidinedithiocarbamate. We uncover their mechanism of action, discover a targetable vulnerability, and gain insight into drug sensitivity for biomarker-based clinical trials in OAC. MethodsElesclomol, disulfiram, and ammonium pyrrolidinedithiocarbamate were systematically characterised across panels of oesophageal cell lines and patient-derived organoids. Drug treated oesophageal cell lines were morphologically profiled using a high-content, imaging platform. Compounds were assessed for efficacy across patient-derived organoids. Metabolomics and transcriptomics were assessed for the identification of oesophageal-cancer specific drug mechanisms and patient stratification hypotheses. ResultsHigh-content profiling revealed that all three compounds were highly selective for OAC over tissue-matched controls. Comparison of gene expression and morphological signatures unveiled a unified mechanism of action involving the accumulation of copper selectively in cancer cells, leading to dysregulation of proteostasis and cancer cell death. Basal omic analyses revealed proteasome and metabolic markers of drug sensitivity, forming the basis for biomarker-based clinical trials in OAC. ConclusionsIntegrated analysis of high-content imaging, transcriptomic and metabolomic data has revealed a new therapeutic mechanism for the treatment of OAC and represents an alternative target-agnostic drug discovery strategy.

cancer biology↗