High-content Imaging Platform Research Articles

Development of an Automated Morphometric Approach to Assess Vascular Outcomes following Exposure to Environmental Chemicals in Zebrafish.

Disruptions in vascular formation attributable to chemical insults is a pivotal risk factor or potential etiology of developmental defects and various disease settings. Among the thousands of chemicals threatening human health, the highly concerning groups prevalent in the environment and detected in biological monitoring in the general population ought to be prioritized because of their high exposure risks. However, the impacts of a large number of environmental chemicals on vasculature are far from understood. The angioarchitecture complexity and technical limitations make it challenging to analyze the entire vasculature efficiently and identify subtle changes through a high-throughput in vivo assay. We aimed to develop an automated morphometric approach for the vascular profile and assess the vascular morphology of health-concerning environmental chemicals. High-resolution images of the entire vasculature in Tg(fli1a:eGFP) zebrafish were collected using a high-content imaging platform. We established a deep learning-based quantitative framework, ECA-ResXUnet, combined with MATLAB to segment the vascular networks and extract features. Vessel scores based on the rates of morphological changes were calculated to rank vascular toxicity. Potential biomarkers were identified by vessel-endothelium-gene-disease integrative analysis. Whole-trunk blood vessels and the cerebral vasculature in larvae exposed to 150 representative chemicals were automatically segmented as comparable to human-level accuracy, with sensitivity and specificity of 95.56% and 95.81%, respectively. Chemical treatments led to heterogeneous vascular patterns manifested by 31 architecture indexes, and the common cardinal vein (CCV) was the most affected vessel. The antipsychotic medicine haloperidol, flame retardant 2,2-bis(chloromethyl)trimethylenebis[bis(2-chloroethyl) phosphate], and tert-butylphenyl diphenyl phosphate ranked as the top three in vessel scores. Pesticides accounted for the largest group, with a vessel score of , characterized by a remarkable inhibition of subintestinal venous plexus and delayed development of CCV. Multiple-concentration evaluation of nine per- and polyfluoroalkyl substances (PFAS) indicated a low-concentration effect on vascular impairment and a positive association between carbon chain length and benchmark concentration. Target vessel-directed single-cell RNA sequencing of cells from larvae treated with , perfluorohexanesulfonic acid, or benzylbutyl phthalate, along with vessel-endothelium-gene-disease integrative analysis, uncovered potential associations with vascular disorders and identified biomarker candidates. This study provides a novel paradigm for phenotype-driven screenings of vascular-disrupting chemicals by converging morphological and transcriptomic profiles at a high-resolution level, serving as a powerful tool for large-scale toxicity tests. Our approach and the high-quality morphometric data facilitate the precise evaluation of vascular effects caused by environmental chemicals. https://doi.org/10.1289/EHP13214.

Abstract 2047: Scale up and scale down approaches for screening of 3D patient-derived cell models

Abstract 3D cell culture is becoming more prevalent as scientists work to better model human physiology using in vitro systems. However, differences in handling 3D cell cultures compared to traditional 2D cell lines have limited adoption of 3D techniques in compound and cell therapy screening experiments. To facilitate use of patient-derived 3D tumoroid models, we developed protocols for both scale up and scale down of these models in Gibco™ OncoPro™ Tumoroid Culture Medium. OncoPro Tumoroid Culture Medium is a serum-free, conditioned medium-free culture medium designed to promote the growth of patient-derived 3D cancer models (tumoroids, cancer organoids). OncoPro medium is compatible with a suspension culture approach for easier handling compared to traditional embedded culture formats. We studied the growth of tumoroids in different flask sizes during suspension culture to optimize scale up for downstream assays. Tumoroid growth rates and morphologies were consistent across non-tissue culture treated flask sizes, and viable cell yield increased with surface area during scale up. In some cases, as many as 100 × 106 dissociated tumoroid cells can be recovered from a single Nunc™ TripleFlask™ after a week of growth. After scaling up, tumoroids were dissociated and seeded in multiwell plates to test multiple screening conditions (compound identity, compound concentration) in parallel. Dissociated cells were seeded in 96-well plates using both manual and automated liquid handling (Tecan Fluent 780). Due to the tendency of 3D cell models to aggregate and fall out of solution, initial seeding in a 96-well flat bottom plate resulted in high well-to-well variability. Optimization of cell seeding protocols led to standard deviations in tumoroid metabolic activity, number, and size that were comparable to manual seeding, with a coefficient of variation of less than 3% between wells for multiple tumoroid lines when automation was implemented. Generally, variability in cell seeding was lower when using the optimized, automated cell seeding protocol compared to manual methods. After seeding, cells were grown for three days to form tumoroids prior to the addition of compounds. At this time point, there was low well-to-well variability in tumoroid metabolic activity (CV<2%). Compounds and reagents to analyze cell health could also be added using automated liquid handling prior to analysis on plate readers or high-content imaging platforms. Citation Format: Colin Paul, Anthony Chatman, Amber Bullock, Xiaoyu Jenny Yang, Garrett Wong, Brittany Balhouse, Chris Yankaskas, Erik Willems, Matt Dallas, David Kuninger. Scale up and scale down approaches for screening of 3D patient-derived cell models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2047.

Comparative analysis of micronucleus induction and DNA damage biomarkers in TK6 and A375 cells using flow cytometry.

Previously, we introduced an alternative adherent A375 cell line for clastogenicity and aneugenicity testing using a high content imaging platform. To further characterize the performance of A375 cells, we investigated the sensitivity and specificity of A375 and TK6 cells by directly comparing micronucleus (MN) induction, cytotoxicity (relative cell counts, viability, and apoptosis), clastogenicity (γH2AX), and aneuploidy markers (pH 3, MPM-2, and polyploidy) using flow cytometric methods. We evaluated 14 compounds across different mechanisms (non-genotoxic apoptosis inducers, clastogens, and aneugens with either tubulin binding or aurora kinase inhibiting phenotypes) at 4-h and 24-h post treatment. Both aneugens and clastogens tested positive for micronucleus induction in both cell lines. Apoptosis continued to be a confounding factor for flow cytometry-based micronuclei assessment in TK6 cells as evidenced by positive responses by the three cytotoxicants. Conversely, A375 cells were not affected by apoptosis-related false positive signals and did not produce a positive response in the in vitro micronucleus assay. Benchmark dose response (BMD) analysis showed that the induction of micronuclei and biomarkers occurred at similar concentrations in both cell lines for clastogens and aneugens. By showing that A375 cells have similar sensitivity to TK6 cells but a greater specificity, these results provide additional support for A375 cells to be used as an alternative adherent cell line for in vitro genetic toxicology assessment.

A flexible, image-based, high-throughput platform encompassing in-depth cell profiling to identify broad-spectrum coronavirus antivirals with limited off-target effects

The recent pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) posed a major threat to global health. Although the World Health Organization ended the public health emergency status, antiviral drugs are needed to address new variants of SARS-CoV-2 and future pandemics. To identify novel broad-spectrum coronavirus drugs, we developed a high-content imaging platform compatible with high-throughput screening. The platform is broadly applicable as it can be adapted to include various cell types, viruses, antibodies, and dyes. We demonstrated that the antiviral activity of compounds against SARS-CoV-2 variants (Omicron BA.5 and Omicron XBB.1.5), SARS-CoV, and human coronavirus 229E could easily be assessed. The inclusion of cellular dyes and immunostaining in combination with in-depth image analysis enabled us to identify compounds that induced undesirable phenotypes in host cells, such as changes in cell morphology or in lysosomal activity. With the platform, we screened ∼900K compounds and triaged hits, thereby identifying potential candidate compounds carrying broad-spectrum activity with limited off-target effects. The flexibility and early-stage identification of compounds with limited host cell effects provided by this high-content imaging platform can facilitate coronavirus drug discovery. We anticipate that its rapid deployability and fast turnaround can also be applied to combat future pandemics.

Targeting tumour-associated macrophages in hodgkin lymphoma using engineered extracellular matrix-mimicking cryogels

Tumour-associated macrophages are linked with poor prognosis and resistance to therapy in Hodgkin lymphoma; however, there are no suitable preclinical models to identify macrophage-targeting therapeutics. We used primary human tumours to guide the development of a mimetic cryogel, wherein Hodgkin (but not Non-Hodgkin) lymphoma cells promoted primary human macrophage invasion. In an invasion inhibitor screen, we identified five drug hits that significantly reduced tumour-associated macrophage invasion: marimastat, batimastat, AS1517499, ruxolitinib, and PD-169316. Importantly, ruxolitinib has demonstrated recent success in Hodgkin lymphoma clinical trials. Both ruxolitinib and PD-169316 (a p38 mitogen-activated protein kinase (p38 MAPK) inhibitor) decreased the percent of M2-like macrophages; however, only PD-169316 enhanced the percentage of M1-like macrophages. We validated p38 MAPK as an anti-invasion drug target with five additional drugs using a high-content imaging platform. With our biomimetic cryogel, we modeled macrophage invasion in Hodgkin lymphoma and then used it for target discovery and drug screening, ultimately identifying potential future therapeutics.

Abstract 2151: Identification of transcript adenosine fingerprint to enrich for A2AR and PD-1 inhibition responders

Abstract Background: Precision cancer medicine aims to identify the right drug for the right patient, enriching for patients more likely to respond to a particular treatment. This paradigm is gaining importance during the early clinical lifecycle of a new potential drug to improve patient-centric trial designs, drive clinical success and eventually increase approval rates - enlarging the therapeutic arsenal available for oncology patients. To optimize the chance of success with our A2AR-selective antagonist, EXS-21546 (546; NCT04727138, discovered in collaboration with Evotec), we have identified an adenosine-induced immunosuppression biomarker signature (adenosine burden score or ABS) for clinical trial patient selection that also correlates with checkpoint inhibitor (CI) response prediction in ex vivo primary models. Here we present transcriptional and functional data mapping adenosine burden at the single cell level, and investigate subsequent modulation through antagonism of A2AR with 546, combination effects with CI, to prioritize patients for 546+CI therapy. Methods: By leveraging disease-relevant primary human tissues together with matched single cell and bulk transcriptomics, we assess adenosine-induced anticancer immune suppression and show initial biological confirmation of patient selection methodology and combination therapy effects with a translatable high content imaging platform (Kornauth et al 2021 & Snidjer et al 2017). Results: The ABS detects adenosine rich microenvironments with greater specificity and sensitivity than other published signatures. Validating the ABS in TGCA, we found the ABS anti-correlates with a validated predictor of anti-PD-1 therapy success (TIS, Damotte et al 2019), unraveling that high-adenosine/ABS cases are among patients least likely to respond to immunotherapy (low TIS). A2AR antagonism with 546 demonstrated a reduction of the adenosine burden, and restored the CI response potential as addressed by the ABS and TIS, respectively. Further immune reactivation was seen with antagonism of adenosine signaling by ‘546/CI combination ex vivo in primary tissues pre-selected with our ABS signature. Conclusions: Combining deep learning of single cell functional and multi-omics profiling data of disease relevant primary model systems, we model the association of the immune response potential to A2AR antagonism in cancer to define a biomarker signature to predict patients likely to benefit from A2AR antagonism and CI. This will be confirmed and validated retrospectively in an ongoing clinical study of 546 in two cancer indications. Citation Format: Isabella Alt, Robert Sehlke, Anna Lobley, Claudia Baumgaertler, Maja Stulic, Klaus Hackner, Lucia Dzurillova, Edgar Petru, Laudia Hadjari, Judith Lafleur, Josef Singer, Nikolaus Krall, Jozef Šufliarsky, Lukas Hefler, Thorsten Füreder, Christina Taubert, Andrew Payne, Christophe Boudesco, Gregory Ian Vladimer. Identification of transcript adenosine fingerprint to enrich for A2AR and PD-1 inhibition responders [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2151.

High-throughput functional annotation of natural products by integrated activity profiling

Determining mechanism of action (MOA) is one of the biggest challenges in natural products discovery. Here, we report a comprehensive platform that uses Similarity Network Fusion (SNF) to improve MOA predictions by integrating data from the cytological profiling high-content imaging platform and the gene expression platform FunctionalSignature Ontology, and pairs these data with untargeted metabolomics analysis for de novo bioactive compound discovery. The predictive value of the integrative approach was assessed using a library of target-annotated small molecules as benchmarks. Using Kolmogorov-Smirnov (KS) tests to compare in-class to out-of-class similarity, we found that SNF retains the ability to identify significant in-class similarity across a diverse set of target classes, and could find target classes not detectable in either platform alone. This confirmed that integration of expression-based and image-based phenotypes can accurately report on MOA. Furthermore, we integrated untargeted metabolomics of complex natural product fractions with the SNF network to map biological signatures to specific metabolites. Three examples are presented where SNF coupled with metabolomics was used to directly functionally characterize natural products and accelerate identification of bioactive metabolites, including the discovery of the azoxy-containing biaryl compounds parkamycins A and B. Our results support SNF integration of multiple phenotypic screening approaches along with untargeted metabolomics as a powerful approach for advancing natural products drug discovery.

Abstract A073: Multiplexed therapeutic sensitivity of patient derived pancreatic cancer organoids after neoadjuvant chemotherapy by high content imaging

Abstract Background: Therapeutic development in pancreatic ductal adenocarcinoma (PDAC) requires accurate models for assessing response. Patient-derived cancer organoids (PCOs) have been shown to faithfully recapitulate genomic features of advanced PDAC. Mechanisms of subclonal resistance or intratumoral heterogeneity cannot be characterized using well-level viability assays. Methods: A high-content imaging platform was adapted in low volume, 96-well format for using Cytation 5 (Biotek). PDAC PCOs were plated from organoid suspension in 1:1 reduced growth factor Cultrex plating 10uL per well. After 24h, physiologic chemotherapy was applied to match pharmacologic exposure of FOLFIRINOX (FFX) and gemcitabine/nab-paclitaxel (g/n-pac). Initial response was assessed by normalized change in PCO area at 72h. Subsequent viability staining was performed for single organoid level response for apoptosis (caspase-3/7-FITC) and necrosis (TO-PRO-3). Analyses were automated in Gen5.12 (Biotek) with selection for elements using circularity (>0.4) and alignment by location within <88 mm. Response was assessed using descriptive statistics and effect size (Glass’s Delta) normalized to media control. Results: PCOs were generated from patient-derived pancreatic tumor without prior treatment. Low volume plating facilitated imaging with reduced Z stack (300 mm) with an average of 14 PCOs evaluable per well. Increasing markers of apoptosis by caspase-3/7 staining stratified serial decrease in mean organoid growth by quartile [+285, +175, +42%, +28]. Increasing markers of necrosis using TO-PRO-3 staining stratified serial decrease in mean organoid growth by quartile [+259, +191, +54%, +26]. Normalized change in area was reduced with g/npac +11.9% (GD=1.43) and FFX +20.4% (GD=1.38) versus control +281%. Subclonal populations existed with normalized change in area >50% which represented 17.8% of g/npac and 18.5% of FFX treated PCOs. Individual organoids with mean area staining positive for apoptosis was increased in g/npac +67.3% (GD=2.96) and FFX +65.1 (GD=2.84) versus background control +12.8%. Individual organoids with mean with area staining positive for necrosis was increased in g/npac +47.3% (GD=1.88) as compared to both FFX +34.9 (GD=1.20, p<0.002) and background control staining of +11.1% (p<0.001). Conclusions: High content imaging in PDAC PCOs provide scalable model for response assessment. This method can track subclonal populations with residual growth after treatment with chemotherapy. Here, we provide proof of concept in patient-derived tissue for clinically relevant response assessment with increased induced necrosis with g/npac in comparison to FFX. Ongoing investigations are generating sensitivity thresholds to define subclonal populations with residual growth and viability for application in clinical prediction. Citation Format: Md Shahadat Hossan, Ethan S. Lin, Ellie E. Riedl, Austin Stram, Jamie M. Warner, Jeremy D. Kratz. Multiplexed therapeutic sensitivity of patient derived pancreatic cancer organoids after neoadjuvant chemotherapy by high content imaging [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr A073.

A high-content endogenous GLUT4 trafficking assay reveals new aspects of adipocyte biology.

Insulin-induced GLUT4 translocation to the plasma membrane in muscle and adipocytes is crucial for whole-body glucose homeostasis. Currently, GLUT4 trafficking assays rely on overexpression of tagged GLUT4. Here we describe a high-content imaging platform for studying endogenous GLUT4 translocation in intact adipocytes. This method enables high fidelity analysis of GLUT4 responses to specific perturbations, multiplexing of other trafficking proteins and other features including lipid droplet morphology. Using this multiplexed approach we showed that Vps45 and Rab14 are selective regulators of GLUT4, but Trarg1, Stx6, Stx16, Tbc1d4 and Rab10 knockdown affected both GLUT4 and TfR translocation. Thus, GLUT4 and TfR translocation machinery likely have some overlap upon insulin-stimulation. In addition, we identified Kif13A, a Rab10 binding molecular motor, as a novel regulator of GLUT4 traffic. Finally, comparison of endogenous to overexpressed GLUT4 highlights that the endogenous GLUT4 methodology has an enhanced sensitivity to genetic perturbations and emphasises the advantage of studying endogenous protein trafficking for drug discovery and genetic analysis of insulin action in relevant cell types.

324 (PB104) - Quantitative analysis of EGFR expression and distribution upon drug treatment in colorectal organoid models

Background: Human organoids are patient-derived tissues that can be expanded in vitro by stimulating the (cancer) stem cells with WNT pathway activators, treatment with differentiation inhibitors and by providing growth factors in an extracellular matrix environment. These organoids form three-dimensional (3D) multicellular structures that polarize and self-organize and express relevant disease-related markers, which makes an organoid biobank ideal for testing the efficacy and mode of action of compounds and antibodies across a diverse patient population. Here, our colorectal organoid biobank and high content imaging platform were used to characterize EGFR dynamics upon drug treatment. Methods: An established biobank of normal colon and colorectal cancer organoid models was characterized for its sensitivity to the growth factor EGF, EGFR-inhibitors (Cetuximab), and standard-of-care compounds. To study the distribution of the EGF receptor, antibodies followed by immunofluorescence staining were used to detect the localization and distribution upon growth factor stimulation. (Inducible) knockdown organoid models with shRNA constructs targeting EGFR were generated to validate the findings. Results: The 3D organoid screening and our proprietary image analysis platform allows the in-depth detection and distinction of growth factor responses that not necessarily only relate to proliferation. By making use of this system, the sensitivity of organoid models to EGF stimulation that are independent of EGF for their outgrowth could be determined. By combining the detection of the target, EGFR, with the detection of targeting EGFR-inhibitory antibodies by immunofluorescence followed by image analysis, the redistribution of the receptor upon EGF-stimulation and in response to antibody exposure could be visualized and quantified. This revealed that EGFR is internalized in the first hours upon EGF stimulation. Along with making use of (inducible) knockdown organoids, it also revealed that different EGFR-targeting antibodies have different effects on the redistribution, internalization, and degradation of EGFR. Conclusions: The high content imaging platform in combination with high throughput screening in 3D-cultured organoid models allows compound and antibody testing in physiologically relevant patient-derived models to not only study the sensitivity to novel compounds, but also for patient stratification and to study the mode of action or understand the underlying relevant biology. The outcome of this work demonstrated that organoids are versatile, multicellular structures that are highly suitable for studying the expression and redistribution of disease-relevant targets. No conflict of interest.

124 (PB114) - Defining activity and patient selection of a novel CDK7 inhibitor, GTAEXS-617, through AI-supported primary cancer tissue profiling

Background: Dual inhibition of CDK4/6 has become a mainstay treatment for several cancers, including HR-positive/HER2-negative breast cancer. CDK7 represents another potentially attractive CDK target that could combine the cell cycle inhibition found in CDK4/6 inhibitors with inhibition of transcription. We have generated a highly potent, selective and bioavailable inhibitor of CDK7, GTAEXS-617 (‘617). CDK7 is expressed in both normal and diseased tissue, thus understanding expression, sensitivity profiles and effects of CDK7 inhibition on cancer and non-transformed cells (e.g. stromal or immune) is crucial to elucidate MOA and determine the therapeutic window. In order to identify those patients more likely to benefit from CDK7 inhibition and ‘617 therapy in particular, we have used machine learning and other approaches in part to analyse multiparameter response in heterogeneous patient tissue samples. Materials and Methods: To achieve full understanding of the potency and activity of ‘617, including versus other CDK7 and CDK4/6 inhibitors, we deployed disease relevant primary sample model systems from, for instance, ovarian, breast, lung and MCL patients that represent the cancer microenvironment. Single cell ex vivo functional screening combined with transcriptomics after CDK7 perturbation in disease relevant primary human cancer samples helps reveal cancer-specific effects and patient selection methods. A translatable high content imaging platform amenable to primary human material supported by deep learning driven image analysis is used for all functional profiling. Results: Primary cancer samples from various indications had a broad differential sensitivity to ‘617, with specific sensitivity in high grade ovarian cancer versus low grade. Ex vivo cancer cell sensitivity differences in various ovarian cancer grades, as identified by correlation of phenotypic response to differential single cell transcriptomics after ‘617 perturbation, indicates a potential stratification point that could be used for patient enrichment in clinical trials. Further, ‘617 displayed less cytotoxic effects on the immune compartment than other CDK7 and CDK4/6 inhibitors. Conclusions: We used single cell functional profiling and transcriptomics to begin to maximise our understanding of ‘617 effect with the goal of enriching likely responding patient groups. We’ve described approaches which enable the rapid assessment of new targeted therapies in primary human disease samples containing host immune cells, together with functional data. Conflict of interest: Ownership: MS, ED, JB, MS, OB, JlC, BE, RP, TWP, RS, CB, GIV are shareholders and employees of Exscientia. FA and JJ are shareholders and employees of GT Aperion.

High-Throughput Neurite Outgrowth Assay Using GFP-Labeled iPSC-Derived Neurons.

The potential neurotoxicity from an increasing number of drugs and untested environmental chemicals creates a need to develop reliable and efficient in vitro methods for identifying chemicals that may adversely affect the nervous system. An important process in neurodevelopment is neurite outgrowth, which can be affected by developmental neurotoxicity. Currently, neurite outgrowth assays rely mainly on staining, which requires multiple sample processing steps, particularly washing steps, that may introduce variation and limit throughput. Here, we describe a neurite outgrowth assay that uses induced pluripotent stem cell (iPSC)-derived human cortical glutamatergic neurons and/or spinal motor neurons labeled with green fluorescent protein (GFP) to test compounds in a high-content and high-throughput format. This method enables live and time-lapse imaging of GFP-labeled neurons using an assay plate that is continuously imaged at multiple times after chemical treatment. In this article, we describe how to thaw frozen GFP-labeled neurons, culture them, treat them with a compound of interest, and analyze neurite outgrowth using a high-content imaging platform. In this assay, GFP-labeled iPSC-derived human neurons represent a promising tool for identifying and prioritizing compounds with potential developmental neurotoxicity for further hazard characterization. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA. Basic Protocol 1: Thawing and seeding of iPSC-derived neurons Basic Protocol 2: Compound plate preparation and treatment of neurons Basic Protocol 3: High-content imaging and analysis.

Abstract 4150: Enriching for adenosine antagonist patient responses through deep learning

Abstract Background: Adenosine signaling is a key metabolic pathway regulating tumor immunity. The conversion of inflammatory extracellular ATP into immunosuppressive adenosine invokes signaling of the A2a receptor (A2AR) in the tumor microenvironment. This dampens immune responses and creates a pro-tumor niche. A number of novel IO drugs targeting the adenosine pathway through inhibition of the ectonucleotidases CD39 and CD73 or the A2AR/BR are in clinical trials, including our non-CNS penetrant A2AR-selective antagonist, EXS21546 (NCT04727138). While early clinical results from other adenosine receptor-inhibitors (A2ARi) have shown modest monotherapy activity in nonspecific patient populations, we believe greater success can be achieved by leveraging methods that enable the evaluation of single-cell effects in patient samples preclinically. Using our deep learning driven image analysis platform, we define an adenosine-induced, tumor protective immunosuppression biomarker to augment A2AR antagonist responder identification. Here we describe efforts to transcriptionally and functionally map the adenosine suppressed immune potential and activation by inhibition of A2AR with EXS21546 in primary material. The goal is to reveal gene signatures indicative of adenosine immunosuppression deployable in clinical studies, increasing the likelihood of trial success by identifying patients that have the highest efficiency potential for A2AR targeted therapy. Methods: Leveraging patient material as disease relevant model systems, and collecting baseline and treatment condition transcriptomics, we model the patient specific anti-cancer immune repertoire and validate patient selection methods functionally with a translatable high content imaging platform amenable to primary human material supported by end-to-end deep learning driven image analysis. Results: Combining single cell transcriptomic and functional response data, we demonstrate preclinical mechanistic studies of A2AR antagonism on infiltrating immune cells, with the ultimate aim of discovering predictive algorithms to enrich patients more likely respond to adenosine pathway inhibitors. Patient selection gene signatures are functionally validated using a high content imaging platform with proven translational capabilities (Kornauth et al, Cancer Disc., 2021), demonstrating the association of anti-cancer immune activity with inhibition of adenosine signaling by EXS21546. Signatures and patient selection algorithms are cross-validated with publicly available data. Discussion: Gathering multiple layers of data from primary tumor tissues, we reveal and map the association of immune response potential to A2AR inhibition in cancer. Patient stratification gene signatures identified have the aim to be implemented in future studies of our candidate A2ARi EXS21546, to deliver the right drug at the right time in the right patients. Citation Format: Isabella Alt, Robert Shelke, Anna Lobley, Claudia Baumgaertler, Maja Stulic, Pierre Fons, Mark Whittaker, Klaus Hackner, Lucia Dzurillova, Edga Petru, Laudia Hadjari, Judith Lafleur, Josef Singer, Nikolaus Krall, Lukas Hefler, Thorsten Füreder, Christina Taubert, Christophe Boudesco, Andrew Payne, Gregory Ian Vladimer. Enriching for adenosine antagonist patient responses through deep learning [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4150.

A new imaging platform (iScreen) allows for the concurrent assessment of micronucleus induction and genotoxic mode of action in human A375 cells.

Genotoxicity testing guidelines require the assessment of the clastogenic and aneugenic potential of compounds. While in vitro micronucleus assays detect both types of endpoints, it requires labor-intensive microscopic scoring and does not discriminate between the two modes of actions. Here, we present a novel high-content imaging platform in A375 human cells that addresses the need for rapid scoring while providing additional mechanistic information. We evaluated the new platform with 12 compounds, three compounds from each mechanistic class (clastogen, aneugen tubulin binder, aneugen aurora inhibitor, and nongenotoxicant) following 4- and 24-h compound treatments. The approach we developed is first discriminating between genotoxicant and nongenotoxicant using an image analysis algorithm to quantify micronucleus induction below a 60% cytotoxicity cutoff. Then it uses centromere protein A (CENPA) staining for the genotoxic compounds to discriminate between aneugens and clastogens. Lastly, we use phosphorylated histone H2AX Ser139 (γH2AX) staining to confirm clastogenicity and changes in phosphorylated histone 3 Ser10 (pH3) and increases in polyploidy in mitotic cells to discriminate between aneugens that bind tubulin from those that affect aurora kinases. All compounds were correctly classified, and we showed by using benchmark dose-response analysis that the imaging platform in A375 cells is at least as sensitive as the MicroFlow® assay in TK6 cells for genotoxicant but appears to be more specific for the nongenotoxicants. A detailed comparison of the cell lines and a more comprehensive validation with a much larger compound set, predictive and dose-response modeling will be presented in the future.

High-Content Imaging Platform to Discover Chemical Modulators of Plasma Membrane Rafts.

Plasma membrane organization profoundly impacts cellular functionality. A well-known mechanism underlying this organization is through nanoscopic clustering of distinct lipids and proteins in membrane rafts. Despite their physiological importance, rafts remain a difficult-to-study aspect of membrane organization, in part because of the paucity of chemical tools to experimentally modulate their properties. Methods to selectively target rafts for therapeutic purposes are also currently lacking. To tackle these problems, we developed a high-throughput screen and an accompanying image analysis pipeline to identify small molecules that enhance or inhibit raft formation. Cell-derived giant plasma membrane vesicles were used as the experimental platform. A proof-of-principle screen using a bioactive lipid library demonstrates that this method is robust and capable of validating established raft modulators including C6- and C8-ceramide, miltefosine, and epigallocatechin gallate as well as identifying new ones. The platform we describe here represents a powerful tool to discover new chemical approaches to manipulate rafts and their components.

Multiparametric platform for profiling lipid trafficking in human leukocytes

SummarySystematic insight into cellular dysfunction can improve understanding of disease etiology, risk assessment, and patient stratification. We present a multiparametric high-content imaging platform enabling quantification of low-density lipoprotein (LDL) uptake and lipid storage in cytoplasmic droplets of primary leukocyte subpopulations. We validate this platform with samples from 65 individuals with variable blood LDL-cholesterol (LDL-c) levels, including familial hypercholesterolemia (FH) and non-FH subjects. We integrate lipid storage data into another readout parameter, lipid mobilization, measuring the efficiency with which cells deplete lipid reservoirs. Lipid mobilization correlates positively with LDL uptake and negatively with hypercholesterolemia and age, improving differentiation of individuals with normal and elevated LDL-c. Moreover, combination of cell-based readouts with a polygenic risk score for LDL-c explains hypercholesterolemia better than the genetic risk score alone. This platform provides functional insights into cellular lipid trafficking and has broad possible applications in dissecting the cellular basis of metabolic disorders.

Leveraging High-Content Imaging Platforms for Drug Discovery

Leveraging High-Content Imaging Platforms for Drug Discovery

Abstract 2978: Unique 3D organoids autologous TIL coculture platform enables high throughput immune-oncology drug response studies

Abstract Background: Cancer progression and response to therapy are governed by complex cellular interactions in the tumor microenvironment (TME). A better understanding of TME and the immune microenvironment requires robust experimental systems modeling patient specific immune interactions. Conventional 2D cultures lack in recapitulating 3D morphological structures and complex immune biology of native human tumors. A vastly heterogenous TME impacts patient treatment response. There is a dearth of 2D or 3D in vitro models that mimic in vivo diversity of TME, including infiltrating immune populations. 3D organoid cultures typically contain neoplastic epithelium and fail to retain syngeneic tumor-infiltrating lymphocytes (TILs) interactions vital for exhibiting a clinically significant drug response. Here we describe patient-derived xenograft (PDX) derived 3D organoid (PDXO) cultures with autologous TILs to avoid alloreactivity and simulate tumor specific immune response. The described model allows the evaluation of TIL infiltration and high throughput screening of immune-modulatory therapies. Methods: Patient-derived xenografts from mice were enzymatically digested to establish PDXO. PDXO were characterized for expression of cancer specific cell-surface markers. TILs were expanded in culture from PBMCs from matching patients and characterized using flow cytometry. Organoids and TILs from the same patient were fluorescently labeled and cocultured for four days, and tumor infiltration and drug cytotoxicity with and without immune-therapeutics was evaluated. CellInsight CX7 high content imaging platform was used to track TILs, and cancer cells, and TIL infiltration was confirmed via immunofluorescence. Luminex technology was used to quantify changes in the cytokine profile upon drug treatment. Results: PDXO were established to mimic in vivo tumor biology. Tumor-specific TILs were expanded and characterized for expression of memory, inhibitory, proliferation, and regulatory T cell markers. TIL infiltration in organoids was observed from day one in culture and maintained over four days. Immunofluorescence for T cell marker CD3 (cluster of differentiation 3) within PDXO confirmed TIL infiltration. Infiltrating TILs and tumor cell killing evaluation using fluorescent dyes via high throughput imaging platform showed disease and patient-specific response. PDXO treatment with immune-modulatory therapeutics led to changes in the secreted levels of cytokines IL2 (interleukin 2), IFNγ (interferon gamma), and TNFα (tumor necrotic factor alpha). Conclusion: Our patient autologous TILs - PDXO culture platform can be used for high throughput drug screening to model immune-therapeutic response with the tumor specific immune microenvironment. Citation Format: Garima Kaushik, Padma Kamineny, Amy Wesa. Unique 3D organoids autologous TIL coculture platform enables high throughput immune-oncology drug response studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2978.

Anti-SARS-CoV-2 Activity of Andrographis paniculata Extract and Its Major Component Andrographolide in Human Lung Epithelial Cells and Cytotoxicity Evaluation in Major Organ Cell Representatives.

The coronaviruses disease 2019 (COVID-19) caused by a novel coronavirus (SARS-CoV-2) has become a major health problem, affecting more than 50 million people with over one million deaths globally. Effective antivirals are still lacking. Here, we optimized a high-content imaging platform and the plaque assay for viral output study using the legitimate model of human lung epithelial cells, Calu-3, to determine the anti-SARS-CoV-2 activity of Andrographis paniculata extract and its major component, andrographolide. SARS-CoV-2 at 25TCID50 was able to reach the maximal infectivity of 95% in Calu-3 cells. Postinfection treatment of A. paniculata and andrographolide in SARS-CoV-2-infected Calu-3 cells significantly inhibited the production of infectious virions with an IC50 of 0.036 μg/mL and 0.034 μM, respectively, as determined by the plaque assay. The cytotoxicity profile developed over the cell line representatives of major organs, including liver (HepG2 and imHC), kidney (HK-2), intestine (Caco-2), lung (Calu-3), and brain (SH-SY5Y), showed a CC50 of >100 μg/mL for A. paniculata extract and 13.2–81.5 μM for andrographolide, respectively, corresponding to a selectivity index of over 380. In conclusion, this study provided experimental evidence in favor of A. paniculata and andrographolide for further development as a monotherapy or in combination with other effective drugs against SARS-CoV-2 infection.

A High-Throughput In Situ Method for Estimation of Hepatocyte Nuclear Ploidy in Mice.

When the liver is injured, hepatocyte numbers decrease, while cell size, nuclear size and ploidy increase. The expansion of non-parenchymal cells such as cholangiocytes, myofibroblasts, progenitors and inflammatory cells also indicate chronic liver damage, tissue remodeling and disease progression. In this protocol, we describe a simple high-throughput approach for calculating changes in the cellular composition of the liver that are associated with injury, chronic disease and cancer. We show how information extracted from two-dimensional (2D) tissue sections can be used to quantify and calibrate hepatocyte nuclear ploidy within a sample and enable the user to locate specific ploidy subsets within the liver in situ. Our method requires access to fixed/frozen liver material, basic immunocytochemistry reagents and any standard high-content imaging platform. It serves as a powerful alternative to standard flow cytometry techniques, which require disruption of freshly collected tissue, loss of spatial information and potential disaggregation bias.