Remdesivir, Molnupiravir and Nirmatrelvir remain active against SARS-CoV-2 Omicron and other variants of concern.

The in vitro effect of GS-441524, remdesivir, EIDD-1931, molnupiravir and nirmatrelvir against the various SARS-CoV-2 VOCs, including Omicron, was determined. VeroE6-GFP cells were pre-treated overnight with serial dilutions of the compounds before infection. The number of fluorescent pixels of GFP signal, determined by high-content imaging on day 4 post-infection, was used as read-out, and the EC50 of each compound on a viral isolate of each VOC was calculated. These experiments were performed in the presence of the Pgp-inhibitor CP-100356 in order to limit compound efflux. A SARS-CoV-2 strain grown from the first Belgian patient sample was used as ancestral strain. All the other isolates were obtained from patients in Belgium as well. Our results indicate that GS-441524, remdesivir, EIDD-1931, molnupiravir and nirmatrelvir retain their activity against the VOCs Alpha, Beta, Gamma, Delta and Omicron. This is in accordance with the observation that the target proteins of these antivirals are highly conserved.

Integrated cytometry with machine learning applied to high-content imaging of human kidney tissue for in-situ cell classification and neighborhood analysis

The human kidney is a complex organ with various cell types that are intricately organized to perform key physiological functions and maintain homeostasis. New imaging modalities such as mesoscale and highly multiplexed fluorescence microscopy are increasingly applied to human kidney tissue to create single cell resolution datasets that are both spatially large and multi-dimensional. These single cell resolution high-content imaging datasets have a great potential to uncover the complex spatial organization and cellular make-up of the human kidney. Tissue cytometry is a novel approach used for quantitative analysis of imaging data, but the scale and complexity of such datasets pose unique challenges for processing and analysis. We have developed the Volumetric Tissue Exploration and Analysis (VTEA) software, a unique tool that integrates image processing, segmentation and interactive cytometry analysis into a single framework on desktop computers. Supported by an extensible and open-source framework, VTEA's integrated pipeline now includes enhanced analytical tools, such as machine learning, data visualization, and neighborhood analyses for hyperdimensional large-scale imaging datasets. These novel capabilities enable the analysis of mesoscale two and three-dimensional multiplexed human kidney imaging datasets (such as CODEX and 3D confocal multiplexed fluorescence imaging). We demonstrate the utility of this approach in identifying cell subtypes in the kidney based on labels, spatial association and their microenvironment or neighborhood membership. VTEA provides integrated and intuitive approach to decipher the cellular and spatial complexity of the human kidney and complement other transcriptomics and epigenetic efforts to define the landscape of kidney cell types.

P-OGC32 Copper-dependent cell death is a cancer specific vulnerability in oesophageal adenocarcinoma and provides the opportunity for future biomarker-stratified clinical trials

Background Oesophageal adenocarcinoma (OAC) is of increasing global concern due to increasing incidence, lack of effective treatments, and poor prognosis. Therapeutic target discovery and clinical trials have been hindered by the heterogeneity of the disease, dominance of large-scale genomic rearrangements, and lack of driver mutations. We have profiled small-molecule compounds using an innovative high content imaging assay in a panel of transformed and non-transformed oesophageal cell lines to identify OAC-specific cytotoxic compounds, new therapeutic targets, potential drug repurposing opportunities, and chemical starting points for the treatment of OAC. Methods We have comprehensively profiled 19,555 small-molecule compounds using an innovative high content assay to quantify 1000’s of subcellular imaging features to capture important phenotypes missed by standard approaches. Prioritised molecules then underwent functional, transcriptomic, and metabolomic characterisation across panels of oesophageal cell lines and patient-derived organoids for the identification of OAC-specific drug mechanisms. Results We identified 72 lead compounds as exhibiting OAC-specific cytotoxicity and characterised three of the most potent and selective compounds in depth, each of different proposed classes and chemical structures. Using several orthogonal methods we uncovered a unified mechanism of action and a targetable vulnerability in OAC involving copper-dependent cell death. Strikingly no phenotypic effects or changes in gene-expression were observed following treatment with these compounds in non-transformed oesophageal cell lines or normal gastric organoids providing support for this mechanism as a cancer-specific phenomenon. Conclusions We have applied high content imaging, transcriptomic and metabolomic analyses to reveal a unique vulnerability in OAC. We have defined a unified mechanism of OAC-specific copper-dependent cell death for the three highly potent compounds. Finally, through the integration of transcriptomic and metabolomics analyses we gained insight into drug sensitivity and provide the basis for a future biomarker-stratified clinical trial of these drugs in OAC.

Targeting cellular senescence with novel senotherapeutics by design to extend healthspan

Senescent cells accumulate with age in various tissues and organs, leading to the decline in tissue function and deterioration of many age-related diseases and aging. Senolytics have emerged as an effective therapeutic approach to eliminate senescent cells to improve aging phenotypes and associated co-morbidities. Despite their promising potential, only a handful of senolytics have been reported, including a natural flavonoid fisetin discovered by our group. Fisetin has been shown to reduce senescence, suppress age-related pathology, and extend healthspan in aged mice. However, its moderate potency, potential mutagenic risk and poor bioavailability have limited its further clinical applications. By leveraging drug design, medicinal chemistry and high-content imaging analysis, we have successfully optimized the senolytic activity of fisetin, leading to the identification of two improved fisetin senolytic analogs (FAs) with reduced toxicity in non-senescent cells. The improved senolytic activity of these FAs was demonstrated in murine and human senescent cell models as well as in accelerated aging and naturally aged mouse models. The analysis of the senolytic activity of the FAs as well as several other recently identified senolytics, including a senolytic lipid, will be presented.

Development of a chemogenomics library for phenotypic screening

With the development of advanced technologies in cell-based phenotypic screening, phenotypic drug discovery (PDD) strategies have re-emerged as promising approaches in the identification and development of novel and safe drugs. However, phenotypic screening does not rely on knowledge of specific drug targets and needs to be combined with chemical biology approaches to identify therapeutic targets and mechanisms of actions induced by drugs and associated with an observable phenotype. In this study, we developed a system pharmacology network integrating drug-target-pathway-disease relationships as well as morphological profile from an existing high content imaging-based high-throughput phenotypic profiling assay known as “Cell Painting”. Furthermore, from this network, a chemogenomic library of 5000 small molecules that represent a large and diverse panel of drug targets involved in diverse biological effects and diseases has been developed. Such a platform and a chemogenomic library could assist in the target identification and mechanism deconvolution of some phenotypic assays. The usefulness of the platform is illustrated through examples.

943 3D in vitro tumor model platform rapidly assays immunotherapy efficacy with high content imaging and downstream phenotypic changes with flow cytometry and cytokine analysis

BackgroundCancer immunotherapy represents a burgeoning new direction for oncology therapeutic innovation, with the principal thesis of activating one’s own immune system to irradicate cancer as opposed to the injection of foreign cytotoxic agents like chemotherapy. The first generation of checkpoint inhibitors unleash cytotoxic T cells to locate and kill their tumor target, however, only a small subset of patients (e.g. ~30% of NSCLC patients1) respond favorably. In order to advance the next generation of immunotherapy to the clinic, we critically need models which more accurately represent the immunosuppressive tumor microenvironment (TME).MethodsHere, we describe a novel 3D in vitro tumor model platform which engineers the tumor, stromal, and immune cell compartments of the TME in an extracellular matrix hydrogel (VersaGel2) and a high throughput 96-well format. The system has been extensively tested across multiple solid tumor indications, such as colorectal, lung, pancreatic, breast, and others. Specifically for this study, we utilized NSCLC PDX cells from the Charles River compendium and cocultured with human dermal fibroblasts (HDF) and PBMCs to study the effects of checkpoint inhibitor monoclonal antibodies, Pembrolizumab (anti-PD1) and Atezolizumab (anti-PDL1), on T cell infiltration and T cell-mediated killing using high content imaging. Supernatants were analyzed for cytokines and the 3D models were subsequently digested for flow cytometry.ResultsThe 3D models demonstrated varying degrees of T cell infiltration and killing capacity across PDX in a dose-dependent manner to checkpoint inhibitors, and the inclusion of fibroblasts played a critical role in further modulating response. Moreover, the data revealed clinically-relevant levels of CD3+, CD4+, and CD8+ T cell subpopulations and cytokine secretions such as IFN-gamma.ConclusionsThese data suggest a novel 3D model platform for assaying immunotherapeutic efficacy as well as its mechanism of action in the context of the TME. Future studies will include applying this novel platform to additional tumor models and screening multiple forms of immunotherapy – such as small molecules, biologics, and cell and gene therapy – in drug discovery, preclinical testing, and precision medicine.ReferencesHaslam A, Prasad V. Estimation of the percentage of US patients with cancer who are eligible for and respond to checkpoint inhibitor immunotherapy drugs. JAMA Netw 2019;2(5):e192535.Hribar KC, Wheeler CJ, Bazarov A, Varshneya K, Yamada R, Buckley P, Patil CG. A simple three-dimensional hydrogel platform enables ex vivo cell culture of patient and PDX tumors for assaying their response to clinically relevant therapies. Mol Canc Ther 2019;18(3):718–725.

4 3D Coculture platform reveals insights into patient autologous immune cell-tumor interaction and immune modulation in vitro

BackgroundUnderstanding tumor microenvironment (TME) and immune microenvironment are vital to devising therapeutic interventions against tumors. Robust models that mimic patient-specific immune interactions in vitro become necessary with the recent promise of immunotherapeutics. Organoid models recapitulate patient tumor morphology and 3D architecture but fall short in recapitulating complex immune biology of native human tumors. Infiltrating immune populations, especially tumor-infiltrating lymphocytes (TIL), vastly impact patients‘ response to therapies. Here we describe a co-culture platform of patient-derived xenograft (PDX) derived organoids (PDXO) with autologous TIL to simulate the tumor-specific immune response and immune modulation ex vivo. The described model allows high throughput screening of immune-modulatory therapies on anti-tumor T cell functions.MethodsPrimary patient tumor fragments simultaneously implanted in NOG mice to establish PDX and in parallel were placed in culture to expand primary TIL ex vivo. PDXO established from resected xenograft tumors were characterized for cancer marker expression and tumor histology. Expanded TIL were characterized by flow cytometry. A 3D autologous co-culture using fluorescently labeled PDXO and matching labeled patient TIL were incubated for four days with and without anti-PD1 treatment. High content imaging was used to measure T cell infiltration and tumor-specific cytotoxicity. Flow cytometry analysis was used to further evaluate T cell function with and without immunomodulatory therapy.ResultsPDXO were established and characterized to mimic in vivo tumor biology and histology. TIL were successfully expanded and characterized to express memory, inhibitory, activation, and regulatory T cell markers. In cocultures, TIL infiltration in PDXO was observed by high content imaging and confirmed using immunofluorescence detection of CD8+ T cells within the PDXO. Immune infiltration in the PDXO and resultant tumor cell killing were quantified in response to immunotherapeutic intervention. Treatment with immune-modulatory therapeutics impacted T cell infiltration and tumor cytotoxicity. Flow cytometry analysis further elucidated the impact of co-culture and drug treatment on T cell phenotype and functional activity.ConclusionsThis autologous, patient-derived, 3D ex vivo platform provides an improved model for evaluating therapeutic efficacy and pharmacodynamics of therapeutic drugs, while simultaneously providing a window into T cell-tumor cell interactions constrained within the existent patient T cell repertoire and autologous MHC restriction.

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

Background and Aims: Oesophageal 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. Methods: Elesclomol, 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. Results: High-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. Conclusions: Integrated 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.