High-throughput Functional Assays Research Articles

Scalable approaches for generating, validating and incorporating data from high-throughput functional assays to improve clinical variant classification

As the adoption and scope of genetic testing continue to expand, interpreting the clinical significance of DNA sequence variants at scale remains a formidable challenge, with a high proportion classified as variants of uncertain significance (VUSs). Genetic testing laboratories have historically relied, in part, on functional data from academic literature to support variant classification. High-throughput functional assays or multiplex assays of variant effect (MAVEs), designed to assess the effects of DNA variants on protein stability and function, represent an important and increasingly available source of evidence for variant classification, but their potential is just beginning to be realized in clinical lab settings. Here, we describe a framework for generating, validating and incorporating data from MAVEs into a semi-quantitative variant classification method applied to clinical genetic testing. Using single-cell gene expression measurements, cellular evidence models were built to assess the effects of DNA variation in 44 genes of clinical interest. This framework was also applied to models for an additional 22 genes with previously published MAVE datasets. In total, modeling data was incorporated from 24 genes into our variant classification method. These data contributed evidence for classifying 4043 observed variants in over 57,000 individuals. Genetic testing laboratories are uniquely positioned to generate, analyze, validate, and incorporate evidence from high-throughput functional data and ultimately enable the use of these data to provide definitive clinical variant classifications for more patients.

Multiplexed Assays of Variant Effect and Automated Patch-clamping Improve KCNH2-LQTS Variant Classification and Cardiac Event Risk Stratification.

Long QT syndrome (LQTS) is a lethal arrhythmia syndrome, frequently caused by rare loss-of-function variants in the potassium channel encoded by KCNH2. Variant classification is difficult, often owing to lack of functional data. Moreover, variant-based risk stratification is also complicated by heterogenous clinical data and incomplete penetrance. Here, we sought to test whether variant-specific information, primarily from high-throughput functional assays, could improve both classification and cardiac event risk stratification in a large, harmonized cohort of KCNH2 missense variant heterozygotes. We quantified cell-surface trafficking of 18,796 variants in KCNH2 using a Multiplexed Assay of Variant Effect (MAVE). We recorded KCNH2 current density for 533 variants by automated patch clamping (APC). We calibrated the strength of evidence of MAVE data according to ClinGen guidelines. We deeply phenotyped 1,458 patients with KCNH2 missense variants, including QTc, cardiac event history, and mortality. We correlated variant functional data and Bayesian LQTS penetrance estimates with cohort phenotypes and assessed hazard ratios for cardiac events. Variant MAVE trafficking scores and APC peak tail currents were highly correlated (Spearman Rank-order ρ = 0.69). The MAVE data were found to provide up to pathogenic very strong evidence for severe loss-of-function variants. In the cohort, both functional assays and Bayesian LQTS penetrance estimates were significantly predictive of cardiac events when independently modeled with patient sex and adjusted QT interval (QTc); however, MAVE data became non-significant when peak-tail current and penetrance estimates were also available. The area under the ROC for 20-year event outcomes based on patient-specific sex and QTc (AUC 0.80 [0.76-0.83]) was improved with prospectively available penetrance scores conditioned on MAVE (AUC 0.86 [0.83-0.89]) or attainable APC peak tail current data (AUC 0.84 [0.81-0.88]). High throughput KCNH2 variant MAVE data meaningfully contribute to variant classification at scale while LQTS penetrance estimates and APC peak tail current measurements meaningfully contribute to risk stratification of cardiac events in patients with heterozygous KCNH2 missense variants.

A robust high-throughput functional screening assay for plant pathogen effectors using the TMV-GFP vector.

Uncovering the function of phytopathogen effectors is crucial for understanding mechanisms of pathogen pathogenicity and for improving our ability to protect plants from diseases. An increasing number of effectors have been predicted in various plant pathogens. Functional characterization of these effectors has become a major focus in the study of plant-pathogen interactions. In this study, we designed a novel screening system that combines the TMV (tobacco mosaic virus)-GFP vector and Agrobacterium-mediated transient expression in the model plant Nicotiana benthamiana. This system enables the rapid identification of effectors that interfere with plant immunity. The biological function of these effectors can be easily evaluated by observing the GFP fluorescence signal using a UV lamp within just a few days. To evaluate the TMV-GFP system, we initially tested it with well-described virulence and avirulence type III effectors from the bacterial pathogen Ralstonia solanacearum. After proving the accuracy and efficiency of the TMV-GFP system, we successfully screened a novel virulence effector, RipS1, using this approach. Furthermore, using the TMV-GFP system, we reproduced consistent results with previously known cytoplasmic effectors from a diverse array of pathogens. Additionally, we demonstrated the effectiveness of the TMV-GFP system in identifying apoplastic effectors. The easy operation, time-saving nature, broad effectiveness, and low technical requirements of the TMV-GFP system make it a promising approach for high-throughput screening of effectors with immune interference activity from various pathogens.

Improving the performance of supervised deep learning for regulatory genomics using phylogenetic augmentation.

Supervised deep learning is used to model the complex relationship between genomic sequence and regulatory function. Understanding how these models make predictions can provide biological insight into regulatory functions. Given the complexity of the sequence to regulatory function mapping (the cis-regulatory code), it has been suggested that the genome contains insufficient sequence variation to train models with suitable complexity. Data augmentation is a widely used approach to increase the data variation available for model training, however current data augmentation methods for genomic sequence data are limited. Inspired by the success of comparative genomics, we show that augmenting genomic sequences with evolutionarily related sequences from other species, which we term phylogenetic augmentation, improves the performance of deep learning models trained on regulatory genomic sequences to predict high-throughput functional assay measurements. Additionally, we show that phylogenetic augmentation can rescue model performance when the training set is down-sampled and permits deep learning on a real-world small dataset, demonstrating that this approach improves data efficiency. Overall, this data augmentation method represents a solution for improving model performance that is applicable to many supervised deep-learning problems in genomics. The open-source GitHub repository agduncan94/phylogenetic_augmentation_paper includes the code for rerunning the analyses here and recreating the figures.

Genome-wide association study identifies human genetic variants associated with fatal outcome from Lassa fever

Infection with Lassa virus (LASV) can cause Lassa fever, a haemorrhagic illness with an estimated fatality rate of 29.7%, but causes no or mild symptoms in many individuals. Here, to investigate whether human genetic variation underlies the heterogeneity of LASV infection, we carried out genome-wide association studies (GWAS) as well as seroprevalence surveys, human leukocyte antigen typing and high-throughput variant functional characterization assays. We analysed Lassa fever susceptibility and fatal outcomes in 533 cases of Lassa fever and 1,986 population controls recruited over a 7 year period in Nigeria and Sierra Leone. We detected genome-wide significant variant associations with Lassa fever fatal outcomes near GRM7 and LIF in the Nigerian cohort. We also show that a haplotype bearing signatures of positive selection and overlapping LARGE1, a required LASV entry factor, is associated with decreased risk of Lassa fever in the Nigerian cohort but not in the Sierra Leone cohort. Overall, we identified variants and genes that may impact the risk of severe Lassa fever, demonstrating how GWAS can provide insight into viral pathogenesis.

Tumor-derived small extracellular vesicles facilitate omental metastasis of ovarian cancer by triggering activation of mesenchymal stem cells

BackgroundOmental metastasis is the major cause of ovarian cancer recurrence and shortens patient survival, which can be largely attributed to the dynamic evolution of the fertile metastatic microenvironment driven by cancer cells. Previously, we found that adipose-derived mesenchymal stem cells (ADSCs) undergoing a phenotype shift toward cancer-associated fibroblasts (CAFs) participated in the orchestrated omental premetastatic niche for ovarian cancer. Here, we aim to elucidate the underlying mechanisms.MethodsSmall extracellular vesicles were isolated from ovarian cancer cell lines (ES-2 and its highly metastatic subline, ES-2-HM) and patient ascites using ultracentrifugation. Functional experiments, including Transwell and EdU assays, and molecular detection, including Western blot, immunofluorescence, and RT–qPCR, were performed to investigate the activation of ADSCs in vitro. High-throughput transcriptional sequencing and functional assays were employed to identify the crucial functional molecules inducing CAF-like activation of ADSCs and the downstream effector of miR-320a. The impact of extracellular vesicles and miR-320a-activated ADSCs on tumor growth and metastasis was assessed in subcutaneous and orthotopic ovarian cancer xenograft mouse models. The expression of miR-320a in human samples was evaluated using in situ hybridization staining.ResultsPrimary human ADSCs cocultured with small extracellular vesicles, especially those derived from ES-2-HM, exhibited boosted migration, invasion, and proliferation capacities and elevated α-SMA and FAP levels. Tumor-derived small extracellular vesicles increased α-SMA-positive stromal cells, fostered omental metastasis, and shortened the survival of mice harboring orthotopic ovarian cancer xenografts. miR-320a was abundant in highly metastatic cell-derived extracellular vesicles, evoked dramatic CAF-like transition of ADSCs, targeted the 3′-untranslated region of integrin subunit alpha 7 and attenuated its expression. miR-320a overexpression in ovarian cancer was associated with omental metastasis and shorter survival. miR-320a-activated ADSCs facilitated tumor cell growth and omental metastasis. Depletion of integrin alpha 7 triggered CAF-like activation of ADSCs in vitro.8TP37CR9mn1qNp5Xi3wswYVideo ConclusionsmiR-320a in small extracellular vesicles secreted by tumor cells targets integrin subunit alpha 7 in ADSCs and drives CAF-like activation, which in turn facilitates omental metastasis of ovarian cancer.Graphical

Atherosclerotic three-layer nanomatrix vascular sheets for high-throughput therapeutic evaluation

In vitro atherosclerosis models are essential to evaluate therapeutics before in vivo and clinical studies, but significant limitations remain, such as the lack of three-layer vascular architecture and limited atherosclerotic features. Moreover, no scalable 3D atherosclerosis model is available for making high-throughput assays for therapeutic evaluation. Herein, we report an in vitro 3D three-layer nanomatrix vascular sheet with critical atherosclerosis multi-features (VSA), including endothelial dysfunction, monocyte recruitment, macrophages, extracellular matrix remodeling, smooth muscle cell phenotype transition, inflammatory cytokine secretion, foam cells, and calcification initiation. Notably, we present the creation of high-throughput functional assays with VSAs and the use of these assays for evaluating therapeutics for atherosclerosis treatment. The therapeutics include conventional drugs (statin and sirolimus), candidates for treating atherosclerosis (curcumin and colchicine), and potential gene therapy (miR-146a-loaded liposomes). The high efficiency and flexibility of the scalable VSA functional assays should facilitate drug discovery and development for atherosclerosis.

Employment of a high throughput functional assay to define the critical factors that influence vaccine induced cross-variant neutralizing antibodies for SARS-CoV-2

The scale and duration of neutralizing antibody responses targeting SARS-CoV-2 viral variants represents a critically important serological parameter that predicts protective immunity for COVID-19. In this study, we describe the development and employment of a new functional assay that measures neutralizing antibodies for SARS-CoV-2 and present longitudinal data illustrating the impact of age, sex and comorbidities on the kinetics and strength of vaccine-induced antibody responses for key variants in an Asian volunteer cohort. We also present an accurate quantitation of serological responses for SARS-CoV-2 that exploits a unique set of in-house, recombinant human monoclonal antibodies targeting the viral Spike and nucleocapsid proteins and demonstrate a reduction in neutralizing antibody titres across all groups 6 months post-vaccination. We also observe a marked reduction in the serological binding activity and neutralizing responses targeting recently newly emerged Omicron variants including XBB 1.5 and highlight a significant increase in cross-protective neutralizing antibody responses following a third dose (boost) of vaccine. These data illustrate how key virological factors such as immune escape mutations combined with host demographic factors such as age and sex of the vaccinated individual influence the strength and duration of cross-protective serological immunity for COVID-19.

GetPrimers: A generalized PCR-based genetic targeting primer designer enabling easy and standardized targeted gene modification across multiple systems.

Genetic targeting (e.g., gene knockout and tagging) based on polymerase chain reaction (PCR) is a simple yet powerful approach for studying gene functions. Although originally developed in classic budding and fission yeast models, the same principle applies to other eukaryotic systems with efficient homologous recombination. One-stepPCR-based genetic targeting is conventionally used but the sizes of the homologous arms that it generates for recombination-mediated genetic targeting are usually limited. Alternatively, gene targeting can also be performed via fusion PCR, which can create homologous arms that are orders of magnitude larger, therefore substantially increasing the efficiency of recombination-mediated genetic targeting. Here, we present GetPrimers (https://www.evomicslab.org/app/getprimers/), a generalized computational framework and web toolto assist automatic targeting and verification primer design for both one-stepPCR-based and fusionPCR-based genetic targeting experiments. Moreover, GetPrimers by design runs for any given genetic background of any species with full genome scalability. Therefore, GetPrimers is capable of empowering high-throughput functional genomic assays at multipopulation and multispecies levels. Comprehensive experimental validations have been performed for targeting and verification primers designed by GetPrimers across multiple organism systems and experimental setups. We anticipate GetPrimers to become a highly useful and popular tool to facilitate easy and standardized gene modification across multiple systems.

Abstract A095: The paradox-breaker BRAF inhibitor plixorafenib (FORE8394) efficiently inhibits non-V600 mutations and fusions

Abstract The use of several BRAF inhibitors to target BRAF V600 (Class I BRAF mutations) mutated tumors has shown clinical benefit in multiple types of cancer. Nonetheless, V600 mutations comprise about 40% of the BRAF-altered patient population, and the remainder of the BRAF mutated patients are in need of novel targeted therapies. Clinical trials aimed at evaluating the effect of these inhibitors in non-V600 patients, mostly in combination with a MEK inhibitor, have been performed with mixed results. However, the experimental sensitivity to a wide range of class 2 (RAS independent non-V600 including BRAF fusions) or class 3 (RAS dependent non-V600) alterations to different types of BRAF inhibitors has not been reported. Here we tested the efficacy of plixorafenib (a novel paradox braker BRAF inhibitor) compared with several BRAF inhibitors in BRAF V600 and non-V600 alterations. We implemented a high-throughput cell-based functional assay to profile the response of different BRAF variants to plixorafenib (paradox breaker), vemurafenib (a first-generation inhibitor) and tovorafenib (a pan-RAF inhibitor). This method quantifies MAPK signaling pathway activation using fluorescent imaging coupled with image analysis of cells expressing the mutated protein together with a fluorescently labeled ERK2 as a signaling pathway reporter. We also validated a subset of the findings using standard western blot and cell viability experiments. Comparing the response of 4 Class I, 26 Class II and 94 BRAF fusions to plixorafenib and vemurafenib Results showed that Plixorafenib was more potent in inhibiting the majority of BRAF alterations tested, i.e., a lower IC50 value was measured for plixorafenib over vemurafenib. Furthermore, of the 94 BRAF fusions proteins tested, over 75% showed at least a 50% inhibition over the concentrations tested, while less than 20% were inhibited by vemurafenib. A smaller cohort of 23 BRAF alterations was tested with the investigational pan-RAF inhibitor tovorafenib. The IC:50 values for the Class I and II BRAF alterations tested were higher with tovorafenib compared with plixorafenib, and 6 of 13 BRAF fusions tested were resistant to tovorafenib and sensitive to plixorafenib. In conclusion, we show here that plixorafenib inhibits a wide range of V600 and non-V600 BRAF alterations, more potently compared with first generation BRAFi (vemurafenib) and a pan-RAF inhibitor (tovorafenib). Importantly, this effect has the potential to overcome an unmet clinical need in cancers with non-V600 alterations. Citation Format: Limor Cohen, Natalie Filippov-Levy, Hana Billauer, Lea Birnbaum, Sara Gasasa, Roey Maor, Yakir Amrusi, Reham Abu-Liel, Eden Goldfarb, Gabi Tarcic. The paradox-breaker BRAF inhibitor plixorafenib (FORE8394) efficiently inhibits non-V600 mutations and fusions [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr A095.

Development of automated patch clamp assays to overcome the burden of variants of uncertain significance in inheritable arrhythmia syndromes

Advances in next-generation sequencing have been exceptionally valuable for identifying variants in medically actionable genes. However, for most missense variants there is insufficient evidence to permit definitive classification of variants as benign or pathogenic. To overcome the deluge of Variants of Uncertain Significance, there is an urgent need for high throughput functional assays to assist with the classification of variants. Advances in parallel planar patch clamp technologies has enabled the development of automated high throughput platforms capable of increasing throughput 10- to 100-fold compared to manual patch clamp methods. Automated patch clamp electrophysiology is poised to revolutionize the field of functional genomics for inheritable cardiac ion channelopathies. In this review, we outline i) the evolution of patch clamping, ii) the development of high-throughput automated patch clamp assays to assess cardiac ion channel variants, iii) clinical application of these assays and iv) where the field is heading.

Using the structural diversity of RNA: protein interfaces to selectively target RNA with small molecules in cells: methods and perspectives.

In recent years, RNA has gained traction both as a therapeutic molecule and as a therapeutic target in several human pathologies. In this review, we consider the approach of targeting RNA using small molecules for both research and therapeutic purposes. Given the primary challenge presented by the low structural diversity of RNA, we discuss the potential for targeting RNA: protein interactions to enhance the structural and sequence specificity of drug candidates. We review available tools and inherent challenges in this approach, ranging from adapted bioinformatics tools to in vitro and cellular high-throughput screening and functional analysis. We further consider two critical steps in targeting RNA/protein interactions: first, the integration of in silico and structural analyses to improve the efficacy of molecules by identifying scaffolds with high affinity, and second, increasing the likelihood of identifying on-target compounds in cells through a combination of high-throughput approaches and functional assays. We anticipate that the development of a new class of molecules targeting RNA: protein interactions to prevent physio-pathological mechanisms could significantly expand the arsenal of effective therapeutic compounds.

An improved method for large scale generation and high-throughput functional characterization of human iPSC-derived microglia

Neuroscience drug discovery has faced significant challenges due to restricted access to relevant human cell models and limited translatability of existing preclinical findings to human pathophysiology. Induced pluripotent stem cells (iPSCs) have emerged as a promising solution, offering the potential to generate patient-specific cell types, including in the recent years, iPSC-derived microglia (iMGL). Current methods rely on complex and time-consuming differentiation procedures, leading to considerable batch-to-batch variability consequently hindering the establishment of standardized and reproducible high-throughput functional screening approaches. Addressing these challenges is critical in ensuring the generation of homogenous iMGL populations with consistent functional properties. In this study we describe an improved high-yield protocol for generating iMGL, which allows for increased reproducibility and flexibility in the execution of high-throughput functional screens. We introduce a two-step process in embryoid bodie (EB) maintenance and a stop point allowing for cryopreservation at the hematopoietic progenitor cell (iHPC) stages. Furthermore, we demonstrate inter-operator robustness of this modified protocol in a range of high-throughput functional assays including phagocytosis, lysosomal acidification, chemotaxis, and cytokine release. Our study underscores the importance of quality control checks at various stages of iPSC-differentiation and functional assay set up, highlighting novel workarounds to the existing challenges such as limited yield, flexibility, and reproducibility, all critical in drug discovery.

INV02 High throughput functional assays to improve interpretation of rare variants discovered in neuromuscular disease genes

INV02 High throughput functional assays to improve interpretation of rare variants discovered in neuromuscular disease genes

Saturation genome editing of 11 codons and exon 13 of BRCA2 coupled with chemotherapeutic drug response accurately determines pathogenicity of variants.

The unknown pathogenicity of a significant number of variants found in cancer-related genes is attributed to limited epidemiological data, resulting in their classification as variant of uncertain significance (VUS). To date, Breast Cancer gene-2 (BRCA2) has the highest number of VUSs, which has necessitated the development of several robust functional assays to determine their functional significance. Here we report the use of a humanized-mouse embryonic stem cell (mESC) line expressing a single copy of the human BRCA2 for a CRISPR-Cas9-based high-throughput functional assay. As a proof-of-principle, we have saturated 11 codons encoded by BRCA2 exons 3, 18, 19 and all possible single-nucleotide variants in exon 13 and multiplexed these variants for their functional categorization. Specifically, we used a pool of 180-mer single-stranded donor DNA to generate all possible combination of variants. Using a high throughput sequencing-based approach, we show a significant drop in the frequency of non-functional variants, whereas functional variants are enriched in the pool of the cells. We further demonstrate the response of these variants to the DNA-damaging agents, cisplatin and olaparib, allowing us to use cellular survival and drug response as parameters for variant classification. Using this approach, we have categorized 599 BRCA2 variants including 93-single nucleotide variants (SNVs) across the 11 codons, of which 28 are reported in ClinVar. We also functionally categorized 252 SNVs from exon 13 into 188 functional and 60 non-functional variants, demonstrating that saturation genome editing (SGE) coupled with drug sensitivity assays can enhance functional annotation of BRCA2 VUS.

Dynamic genetic adaptation of Bacteroides thetaiotaomicron during murine gut colonization

To understand how a bacterium ultimately succeeds or fails in adapting to a new host, it is essential to assess the temporal dynamics of its fitness over the course of colonization. Here, we introduce a human-derived commensal organism, Bacteroides thetaiotaomicron (Bt), into the guts of germ-free mice to determine whether and how the genetic requirements for colonization shift over time. Combining a high-throughput functional genetics assay and transcriptomics, we find that gene usage changes drastically during the first days of colonization, shifting from high expression of amino acid biosynthesis genes to broad upregulation of diverse polysaccharide utilization loci. Within the first week, metabolism becomes centered around utilization of a predominant dietary oligosaccharide, and these changes are largely sustained through 6weeks of colonization. Spontaneous mutations in wild-type Bt also evolve around this locus. These findings highlight the importance of considering temporal colonization dynamics in developing more effective microbiome-based therapies.

Plasmonic Functional Assay Platform Determines the Therapeutic Profile of Cancer Cells.

Functional assay platforms could identify the biophysical properties of cells and their therapeutic response to drug treatments. Despite their strong ability to assess cellular pathways, functional assays require large tissue samples, long-term cell culture, and bulk measurements. Even though such a drawback is still valid, these limitations did not hinder the interest in these platforms for their capacity to reveal drug susceptibility. Some of the limitations could be overcome with single-cell functional assays by identifying subpopulations using small sample volumes. Along this direction, in this article, we developed a high-throughput plasmonic functional assay platform to identify the growth profile of cells and their therapeutic profile under therapies using mass and growth rate statistics of individual cells. Our technology could determine populations' growth profiles using the growth rate data of multiple single cells of the same population. Evaluating spectral variations based on the plasmonic diffraction field intensity images in real time, we could simultaneously monitor the mass change for the cells within the field of view of a camera with the capacity of > ∼500 cells/h scanning rate. Our technology could determine the therapeutic profile of cells under cancer drugs within few hours, while the classical techniques require days to show reduction in viability due to antitumor effects. The platform could reveal the heterogeneity within the therapeutic profile of populations and determine subpopulations showing resistance to drug therapies. As a proof-of-principle demonstration, we studied the growth profile of MCF-7 cells and their therapeutic behavior to standard-of-care drugs that have antitumor effects as shown in the literature, including difluoromethylornithine (DFMO), 5-fluorouracil (5-FU), paclitaxel (PTX), and doxorubicin (Dox). We successfully demonstrated the resistant behavior of an MCF-7 variant that could survive in the presence of DFMO. More importantly, we could precisely identify synergic and antagonistic effects of drug combinations based on the order of use in cancer therapy. Rapidly assessing the therapeutic profile of cancer cells, our plasmonic functional assay platform could be used to reveal personalized drug therapies for cancer patients.

Estimating clinical risk in gene regions from population sequencing cohort data

While pathogenic variants can significantly increase disease risk, it is still challenging to estimate the clinical impact of rare missense variants more generally. Even in genes such as BRCA2 or PALB2, large cohort studies find no significant association between breast cancer and rare missense variants collectively. Here, we introduce REGatta, a method to estimate clinical risk from variants in smaller segments of individual genes. We first define these regions by using the density of pathogenic diagnostic reports and then calculate the relative risk in each region by using over 200,000 exome sequences in the UK Biobank. We apply this method in 13 genes with established roles across several monogenic disorders. In genes with no significant difference at the gene level, this approach significantly separates disease risk for individuals with rare missense variants at higher or lower risk (BRCA2 regional model OR= 1.46 [1.12, 1.79], p= 0.0036 vs. BRCA2 gene model OR= 0.96 [0.85, 1.07] p= 0.4171). We find high concordance between these regional risk estimates and high-throughput functional assays of variant impact. We compare our method with existing methods and the use of protein domains (Pfam) as regions and find REGatta better identifies individuals at elevated or reduced risk. These regions provide useful priors and are potentially useful for improving risk assessment for genes associated with monogenic diseases.

Understanding and modeling human traits and diseases: Insights from the comparative genomics resources of Zoonomia

Understanding and modeling human traits and diseases: Insights from the comparative genomics resources of Zoonomia

High-throughput method to analyze the cytotoxicity of CAR T Cells in a 3D tumor spheroid model using image cytometry

Abstract Chimeric antigen receptor (CAR)-T cell therapy is an antigen-dependent cellular therapy that has gained considerable traction in the field of cancer immunotherapy. Currently, there are six FDA-approved CAR-T cell therapies, which all target the CD19 or BCMA antigens for hematologic B cell malignancies. In recent years, a strong focus has been placed on CAR T cell therapy discovery for solid tumors, which may better recapitulate physiological conditions, thereby potentially improving the selection of CAR construct candidates. Therefore, it is critical to develop novel methodologies for high-throughput phenotypic and functional assays using 3D tumor spheroid models to better assess CAR-T cell therapies against solid tumors. Recently, plate-based image cytometry has emerged as a method to investigate and characterize CAR T cell functions in a high-throughput manner. Image cytometry has demonstrated capabilities in analyzing transduction efficiency, cell proliferation, and cytotoxicity for CAR T cell therapy. With the development of 3D spheroid models, image cytometry may provide the necessary tools and applications for CAR T cell therapy discovery geared towards solid tumors. In this work, we discuss the use of CAR-T cells targeted towards PSMA, an antigen that is found on prostate cancer tumor cells, the second most common cause of cancer deaths among men worldwide. Herein, we demonstrate the use of high-throughput image cytometry to characterize PSMA CAR-T cell-mediated cytotoxic potency against 3D prostate tumor spheroids and simultaneously monitor location of the T cells in vitro. The proposed method can effectively assess cell-mediated 3D tumor spheroid cytotoxicity and generate time- and dose-dependent results.