High-throughput approaches to uncover synergistic drug combinations in leukemia.

We report a comprehensive drug synergy study in acute myeloid leukemia (AML). In this work, we investigate a panel of cell lines spanning both MLL-rearranged and non-rearranged subtypes. The work comprises a resource for the community, with many synergistic drug combinations that could not have been predicted a priori, and open source code for automation and analyses. We base our definitions of drug synergy on the Chou-Talalay method, which is useful for visualizations of synergy experiments in isobolograms, and median-effects plots, among other representations. Our key findings include drug synergies affecting the chromatin state, specifically in the context of regulation of the modification state of histone H3 lysine-27. We report open source high throughput methodology such that multidimensional drug screening can be accomplished with equipment that is accessible to most laboratories. This study will enable preclinical investigation of new drug combinations in a lethal blood cancer, with data analysis and automation workflows freely available to the community.

Human Pluripotent Stem Cells for High-Throughput Drug Screening and Characterization of Small Molecules.

Human pluripotent stem cells (hPSCs), such as induced pluripotent stem cells (iPSCs), hold great promise for drug discovery, toxicology studies, and regenerative medicine. Here, we describe standardized protocols and experimental procedures that combine automated cell culture for scalable production of hPSCs with quantitative high-throughput screening (qHTS) in miniaturized 384-well plates. As a proof of principle, we established dose-response assessments and determined optimal concentrations of 12 small molecule compounds that are commonly used in the stem cell field. Multi-parametric analysis of readouts from diverse assays including cell viability, mitochondrial membrane potential, plasma membrane integrity, and ATP production was used to distinguish normal biological responses from cellular stress induced by small molecule treatment. Collectively, the establishment of integrated workflows for cell manufacturing, qHTS, high-content imaging, and data analysis provides an end-to-end platform for industrial-scale projects and should leverage the drug discovery process using hPSC-derived cell types.

Therapeutic strategies for diffuse midline glioma from high-throughput combination drug screening.

Diffuse midline gliomas (DMGs) are universally lethal malignancies occurring chiefly during childhood and involving midline structures of the central nervous system, including thalamus, pons, and spinal cord. These molecularly related cancers are characterized by high prevalence of the histone H3K27M mutation. In search of effective therapeutic options, we examined multiple DMG cultures in sequential quantitative high-throughput screens (HTS) of 2706 approved and investigational drugs. This effort generated 19,936 single-agent dose responses that inspired a series of HTS-enabled drug combination assessments encompassing 9195 drug-drug examinations. Top combinations were validated across patient-derived cell cultures representing the major DMG genotypes. In vivo testing in patient-derived xenograft models validated the combination of the multi-histone deacetylase (HDAC) inhibitor panobinostat and the proteasome inhibitor marizomib as a promising therapeutic approach. Transcriptional and metabolomic surveys revealed substantial alterations to key metabolic processes and the cellular unfolded protein response after treatment with panobinostat and marizomib. Mitigation of drug-induced cytotoxicity and basal mitochondrial respiration with exogenous application of nicotinamide mononucleotide (NMN) or exacerbation of these phenotypes when blocking nicotinamide adenine dinucleotide (NAD+) production via nicotinamide phosphoribosyltransferase (NAMPT) inhibition demonstrated that metabolic catastrophe drives the combination-induced cytotoxicity. This study provides a comprehensive single-agent and combinatorial drug screen for DMG and identifies concomitant HDAC and proteasome inhibition as a promising therapeutic strategy that underscores underrecognized metabolic vulnerabilities in DMG.

High-Throughput Screening for Drug Combinations.

The identification of drug combinations as alternatives to single-agent therapeutics has traditionally been a slow, largely manual process. In the last 10 years, high-throughput screening platforms have been developed that enable routine screening of thousands of drug pairs in an in vitro setting. In this chapter, we describe the workflow involved in screening a single agent versus a library of mechanistically annotated, investigation, and approved drugs using a full dose-response matrix scheme using viability as the readout. We provide details of the automation required to run the screen and the informatics required to process data from screening robot and subsequent analysis and visualization of the datasets.