Biology subjects

Makda, A.

Publications and source records attributed to Makda, A..

4 recordsLinked to original sources

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↗

bioRxiv2020

A novel high-content phenotypic screen to identify inhibitors of mitochondrial DNA maintenance in trypanosomes

Kinetoplastid parasites cause diverse neglected diseases in humans and livestock, with an urgent need for new treatments. Survival of kinetoplastids depends on their uniquely structured mitochondrial genome (kDNA), the eponymous kinetoplast. Here we report development of a high-content screen for pharmacologically induced kDNA loss, based on specific staining of parasites and automated image analysis. As proof-of-concept we screened a diverse set of [~]14,000 small molecules and exemplify a validated hit as a novel kDNA-targeting compound.

molecular biology↗

bioRxiv2020

High Content Phenotypic Profiling in Oesophageal Adenocarcinoma Identifies Selectively Active Pharmacological Classes of Drugs for Repurposing and Chemical Starting Points for Novel Drug Discovery

Oesophageal adenocarcinoma (OAC) is a highly heterogeneous disease, dominated by large-scale genomic rearrangements and copy number alterations. Such characteristics have hampered conventional target-directed drug discovery and personalized medicine strategies contributing to poor outcomes for patients diagnosed with OAC. We describe the development and application of a phenotypic-led OAC drug discovery platform incorporating image-based, high-content cell profiling and associated image-informatics tools to classify drug mechanism-of-action (MoA). We applied a high-content Cell Painting assay to profile the phenotypic response of 19,555 compounds across a panel of six OAC cell lines representing the genetic heterogeneity of disease, a pre-neoplastic Barretts oesophagus line and a non-transformed squamous oesophageal line. We built an automated phenotypic screening and high-content image analysis pipeline to identify compounds that selectively modified the phenotype of OAC cell lines. We further trained a machine-learning model to predict the MoA of OAC selective compounds using phenotypic fingerprints from a library of reference compounds. We identified a number of phenotypic clusters enriched with similar pharmacological classes e.g. Methotrexate and three other antimetabolites which are highly selective for OAC cell lines. We further identify a small number of hits from our diverse chemical library which show potent and selective activity for OAC cell lines and which do not cluster with the reference library of known MoA, indicating they may be selectively targeting novel oesophageal cancer biology. Our results demonstrate that our OAC phenotypic screening platform can identify existing pharmacological classes and novel compounds with selective activity for OAC cell phenotypes.

cancer biology↗

bioRxiv2019

A Synergistic Anti-Cancer FAK and HDAC Inhibitor Combination Discovered by a Novel Chemical-Genetic High Content Phenotypic Screen

We mutated the Focal Adhesion Kinase (FAK) catalytic domain to inhibit binding of the chaperone, Cdc37 and ATP, mimicking the actions of a FAK kinase inhibitor. We re-expressed mutant and wild-type FAK in squamous cell carcinoma (SCC) cells from which endogenous FAK had been deleted, genetically fixing one axis of a FAK inhibitor combination high-content phenotypic screen to discover drugs that may synergize with FAK inhibitors. HDAC inhibitors represented the major class of compounds that potently induced multi-parametric phenotypic changes when FAK was rendered kinase-defective, or inhibited pharmacologically in SCC cells. Indeed, combined FAK and HDAC inhibitors arrest proliferation and induce apoptosis in a sub-set of cancer cell lines in vitro and efficiently inhibits tumor growth in vivo. Mechanistically, HDAC inhibitors potentiate inhibitor-induced FAK inactivation and reverses FAK-associated nuclear YAP in sensitive cancer cell lines. Here we report the discovery of a new clinically actionable synergistic combination between FAK and HDAC inhibitors.\n\nSignificanceWe describe a chemical-genetic, high-content phenotypic screening approach to discover effective anti-cancer combinations of targeted therapeutics through which we identified a novel, synergistic and clinically actionable, combination of FAK and HDAC inhibitors.

cancer biology↗