High-content Image Analysis Research Articles

High-throughput drug screening identifies novel therapeutics for Low Grade Serous Ovarian Carcinoma

Low grade serous carcinoma (LGSOC) is a rare epithelial ovarian cancer with unique molecular characteristics compared to the more common tubo-ovarian high-grade serous ovarian carcinoma. Pivotal clinical trials guiding the management of epithelial ovarian cancer lack sufficient cases of LGSOC for meaningful subgroup analysis, hence overall findings cannot be extrapolated to rarer chemo-resistant subtypes such as LGSOC. Furthermore, there is a need for more effective therapies for the treatment of relapsed disease, as treatment options are limited. To address this, we conducted the largest quantitative high-throughput drug screening effort (n = 3436 compounds) in 12 patient-derived LGSOC cell lines and one normal ovary cell line to identify unexplored therapeutic avenues. Using a combination of high-throughput robotics, high-content imaging and novel data analysis pipelines, our data set identified 60 high and 19 moderate confidence hits which induced cancer cell specific cytotoxicity at the lowest compound dose assessed (0.1 µM). We also revealed a series of known (mTOR/PI3K/AKT) and novel (EGFR and MDM2-p53) drug classes in which LGSOC cell lines showed demonstrable susceptibility to.

Senescent cell heterogeneity and responses to senolytic treatment are related to cell cycle status during cell growth arrest.

Cellular senescence has been strongly linked to aging and age-related diseases. It is well established that the phenotype of senescent cells is highly heterogeneous and influenced by their cell type and senescence-inducing stimulus. Recent single-cell RNA-sequencing studies identified heterogeneity within senescent cell populations. However, proof of functional differences between such subpopulations is lacking. To identify functionally distinct senescent cell subpopulations, we employed high-content image analysis to measure senescence marker expression in primary human endothelial cells and fibroblasts. We found that G2-arrested senescent cells feature higher senescence marker expression than G1-arrested senescent cells. To investigate functional differences, we compared IL-6 secretion and response to ABT263 senolytic treatment in G1 and G2 senescent cells. We determined that G2-arrested senescent cells secrete more IL-6 and are more sensitive to ABT263 than G1-arrested cells. We hypothesize that cell cycle dependent DNA content is a key contributor to the heterogeneity within senescent cell populations. This study demonstrates the existence of functionally distinct senescent subpopulations even in culture. This data provides the first evidence of selective cell response to senolytic treatment among senescent cell subpopulations. Overall, this study emphasizes the importance of considering the senescent cell heterogeneity in the development of future senolytic therapies.

The matrisome landscape controlling in vivo germ cell fates

The developmental fate of cells is regulated by intrinsic factors and the extracellular environment. The extracellular matrix (matrisome) delivers chemical and mechanical cues that can modify cellular development. However, comprehensive understanding of how matrisome factors control cells in vivo is lacking. Here we show that specific matrisome factors act individually and collectively to control germ cell development. Surveying development of undifferentiated germline stem cells through to mature oocytes in the Caenorhabditis elegans germ line enabled holistic functional analysis of 443 conserved matrisome-coding genes. Using high-content imaging, 3D reconstruction, and cell behavior analysis, we identify 321 matrisome genes that impact germ cell development, the majority of which (>80%) are undescribed. Our analysis identifies key matrisome networks acting autonomously and non-autonomously to coordinate germ cell behavior. Further, our results demonstrate that germ cell development requires continual remodeling of the matrisome landscape. Together, this study provides a comprehensive platform for deciphering how extracellular signaling controls cellular development and anticipate this will establish new opportunities for manipulating cell fates.

The effects of fine particulate matter (SRM 2786) on three different 3D lung models exposed at the air-liquid interface – A comparative study

3D cell culture models exposed at the air-liquid interface (ALI) represent a potential alternative to animal experiments for hazard and risk assessment of inhaled compounds. This study compares cocultures composed of either Calu-3, A549 or HBEC3-KT lung epithelial cells, cultured together with THP-1-derived macrophages and EA.hy926 endothelial cells, in terms of barrier capacity and responses to a standard reference sample of fine particulate matter (SRM 2786). High-content imaging analysis revealed a similar cellular composition between the different cell models. The 3D cell cultures with Calu-3 cells showed the greatest barrier capacity, as measured by transepithelial electrical resistance and permeability to Na-fluorescein. Mucus production was detected in 3D cell cultures based on Calu-3 and A549 cells. Exposure to SRM 2786 at ALI increased cytokine release and expression of genes associated with inflammation and xenobiotic metabolism. Moreover, the presence of THP-1-derived macrophages was central to the cytokine responses in all cell models. While the different 3D cell culture models produced qualitatively similar responses, more pronounced pro-inflammatory responses were observed in the basolateral compartment of the A549 and HBEC3-KT models compared to the Calu-3 model, likely due to their reduced barrier capacity and lower retention of secreted mediators in the apical compartment.

Prediction of cell cycle distribution after drug exposure by high content imaging analysis using low-toxic DNA staining dye.

Interference in cell cycle progression has been noted as one of the important properties of anticancer drugs. In this study, we developed the cell cycle prediction model using high-content imaging data of recipient cells after drug exposure and DNA-staining with a low-toxic DNA dye, SiR-DNA. For this purpose, we exploited HeLa and MCF7 cells introduced with a fluorescent ubiquitination-based cell cycle indicator (Fucci). Fucci-expressing cancer cells were subjected to high-content imaging analysis using OperettaCLS after 36-h exposure to anticancer drugs; the nuclei were segmented, and the morphological and intensity properties of each nucleus characterized by SiR-DNA staining were calculated using imaging analysis software, Harmony. For the use of training, we classified cells into each phase of the cell cycle using the Fucci system. Training data (n = 7500) and validation data (n = 2500) were randomly sampled and the binary classification prediction models for G1, early S, and S/G2/M phases of the cell cycle were developed using four supervised machine learning algorithms. We selected random forest as the model with the best performance through 10-fold cross-validation; the accuracy rate was approximately 75%-87%. Regarding feature importance, variables expected to be biologically related to the cell cycle, for example, signal intensity and nuclear size, were highly ranked, suggesting the validity of the model. These results showed that the cell cycle can be predicted in cancer cells by simply exploiting the current prediction model using fluorescent images of DNA-staining dye, and the model could be applied for the use of future exvivo drug sensitivity diagnosis.

Abstract 4703: Automated 42 PDX 3D in vitro tumor models of the TME screen immuno-oncology and targeted compounds and biologics for antitumor effects and MOA

Abstract High throughput screening has been widely utilized for its efficiency in testing novel therapeutic agents. However, the conventional screening using 2D culture of cancer cell lines lacks the biological complexity of the tumor microenvironment or the immune compartment which limits their application in testing immune-oncology therapies. Particularly with the passing of the FDA Modernization Act 2.0, it is critical to create more biologically relevant 3D in vitro models that can be used to reduce, refine and ultimately replace preclinical animal models. Here we have developed a highly automated 3D high throughput screening platform comprised of 42 patient-derived xenograft models in coculture with fibroblasts in engineered extracellular matrix hydrogels that resemble tumor stromal microenvironment. The PDX models cover a diverse range of tumor and histological types including NSCLC, CRC, gastric, TNBC, RCC, bladder, ovarian, melanoma, pancreatic, and others. Moreover, PBMCs or other immune cells can be incorporated into the system for evaluating immuno-oncology drugs. The panel has been tested against chemotherapy drug cisplatin and the immunotherapy biologic, Solitomab, an EpCAM/CD3 bispecific antibody. The endpoint analyses for antitumor effects include the dose response of tumor size and tumor cell death percentage based on high content imaging analysis. In addition, immune cells and supernatant in the IO assay can be recovered from the wells and used for flow cytometry profiling and cytokine assays. In summary, the novel 42-PDX panel described here offers a unique and powerful tool for rapidly generating preclinical data and a better understanding the drug activity at the pharmacology stages, opening the door for faster and more human relevant drug discovery for cancer patients. Citation Format: Bin Xue, Christopher Harrod, Long Le, Julia Schüler, Kolin C. Hribar. Automated 42 PDX 3D in vitro tumor models of the TME screen immuno-oncology and targeted compounds and biologics for antitumor effects and MOA [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 4703.

Abstract 2060: Automation of 3D cancer spheroid assay for compound screening

Abstract Finding efficient drug combinations to treat cancer patients is critical for therapy success. Accordingly, there is a critical need to develop methods for efficient testing drug efficacy to discover new therapeutic targets. 3D cancer models are highly valuable tools for cancer research and drug development. However, the complexity of performing 3D assays remains a hurdle for adopting these methods for compound screening. To alleviate the bottlenecks that come with labor-intensive manual protocols we developed cell culture automation methods using CellXpress.ai instrument. The instrument enables automation of 2D or 3D culture for prolonged complex workflows. The CellXpress.ai provides automated plating, passaging, media exchanges, monitoring organoids, alone with compound treatment and the end point assays with high content image analysis. In the present study we describe full automation of imaging, analysis, and cell culture process which enables scaling up complex 3D cell-based assays and compound screening. As an example of 3D protocol, we automated culture and imaging of colorectal cancer 3D spheroids formed from HCT116 cell line in U-shape low attachment plates. HCT116 cells were expanded in 2D, then spheroids were formed after automated dispensing of cell suspension into U-shape 96 or 384 plates. After 48h spheroids were treated with 12 anti-cancer compounds, at multiple concentrations for 3-5 days, then stained and imaged. Cell plating, compound additions, media exchange, and staining were performed automatically by CellXpressAI instrument. During the culture spheroids were monitored using transmitted light, with immediate analysis of phenotypic changes, including inhibition of growth or spheroid disintegration. For endpoint assay spheroids were stained with combination of Hoechst nuclear stain and viability dyes Calcein AM and EtHD, then imaged, and analyzed for multiple read-outs including spheroid size, marker intensities, and live-dead cell scoring. We observed concentration-dependent inhibition of spheroid growth and cell death in response to anti-cancer compounds and evaluated effective compound concentrations for cytotoxic or cytostatic effects. Cell culture process automation for 3D assays, powered by imaging and image analysis has a potential to bring 3D biology into another level, allowing to increase throughput and reproducibility, and enabling variety of high throughput drug discovery and precision medicine applications. Citation Format: Oksana Sirenko, Angeline Lim, Astrid Michlmayr, Zhisong Tong, Emilie Keidel, Felix Spira. Automation of 3D cancer spheroid assay for compound screening [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 2060.

Abstract 87: Integrated pipeline for immuno-oncology drug testing: from patient-derived organoid assays with reconstituted TME to fresh ex vivo patient tissue cultures

Abstract Introduction: Successful pre-clinical evaluation of immuno-oncology drugs requires complex models to accurately represent all components of the human tumor microenvironment (TME). Patient-derived organoids (PDO) are known to reflect genetic and morphological profiles of the original patient’s tumors. In our immuno-oncology in vitro assays, PDOs can be combined with immune cells and fibroblasts to re-constitute the TME and study drug efficacy and mechanism of action. Alternatively, we have developed assays with fresh tumor material containing native TME in the 3D Ex Vivo Patient Tissue (EVPT) platform. Both types of assays have advantages and limitations. Here, we will present a case study displaying both capabilities and benchmarking the technologies against each other. Methods: Patient tumor tissues were obtained from tissue providers and processed within 24 hours to preserve the TME. Freshly isolated ex vivo tumor clusters were embedded in a protein-rich hydrogel and exposed to drug panels in a 384-well format for 5-7 days. Phenotypic effects of therapies on morphological features were measured using our proprietary automated high content imaging (HCI) analysis platform. IHC, FACS, or sequencing, were used for in-depth sample characterization. In parallel, PDOs were generated, biobanked and characterized from same ex vivo samples. Allogenic or autologous PBMCs were isolated from blood. PDOs and PBMCs were then co-cultured together in presence of immuno-oncology drugs, and drug effects were analyzed by the same automated HCI analysis platform. Results: Samples from ovarian, head and neck, breast, prostate, lung cancer, and melanoma were used in the pipeline. Fresh ex vivo culture of a melanoma sample presented here has shown mild responses (tumoroid size reduction) to immunomodulatory treatments (SEA and Pembrolizumab) and strong responses to targeted therapy treatment (Dabrafenib and Trametinib). Genetic characterization of the sample identified heterozygous BRAF V600E mutation and IHC analysis showed a large proportion of immune cells (CD3, CD4, CD8, CD80 and CD68 positive cells) present, confirming the observed ex vivo drug responses. Part of the melanoma sample was allocated for PDO generation and biobanking. Established PDOs were used in co-culture with allogeneic and autologous PBMCs and treatment responses to SEA stimulation and CD3/CD28 beads as well as increased PBMC infiltration rates were observed. Conclusion: Choice of the pre-clinical model for immuno-oncology studies relies on multiple factors such as biological relevance, replicability, TME representation, and scalability. Here we present a spectrum of assays ranging from complex ex vivo systems (EVPT) for ‘close to the clinic’ scenarios to more scalable PDOs co-cultured with allogeneic and/or autologous PBMCs for high-throughput mechanistic drug screenings. Citation Format: Ezgi Kaya Aksoy, Sergei Chavez Abiega, Talita Stessuk, Saskia De Man, Marrit Putker, Sander Basten, Niels Meesters, Emma Spanjaard, Leo S. Price, Gera Goverse, Nataliia Beztsinna. Integrated pipeline for immuno-oncology drug testing: from patient-derived organoid assays with reconstituted TME to fresh ex vivo patient tissue cultures [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 87.

High-content analysis identified synergistic drug interactions between INK128, an mTOR inhibitor, and HDAC inhibitors in a non-small cell lung cancer cell line

BackgroundThe development of drug resistance is a major cause of cancer therapy failures. To inhibit drug resistance, multiple drugs are often treated together as a combinatorial therapy. In particular, synergistic drug combinations, which kill cancer cells at a lower concentration, guarantee a better prognosis and fewer side effects in cancer patients. Many studies have sought out synergistic combinations by small-scale function-based targeted growth assays or large-scale nontargeted growth assays, but their discoveries are always challenging due to technical problems such as a large number of possible test combinations.MethodsTo address this issue, we carried out a medium-scale optical drug synergy screening in a non-small cell lung cancer cell line and further investigated individual drug interactions in combination drug responses by high-content image analysis. Optical high-content analysis of cellular responses has recently attracted much interest in the field of drug discovery, functional genomics, and toxicology. Here, we adopted a similar approach to study combinatorial drug responses.ResultsBy examining all possible combinations of 12 drug compounds in 6 different drug classes, such as mTOR inhibitors, HDAC inhibitors, HSP90 inhibitors, MT inhibitors, DNA inhibitors, and proteasome inhibitors, we successfully identified synergism between INK128, an mTOR inhibitor, and HDAC inhibitors, which has also been reported elsewhere. Our high-content analysis further showed that HDAC inhibitors, HSP90 inhibitors, and proteasome inhibitors played a dominant role in combinatorial drug responses when they were mixed with MT inhibitors, DNA inhibitors, or mTOR inhibitors, suggesting that recessive drugs could be less prioritized as components of multidrug cocktails.ConclusionsIn conclusion, our optical drug screening platform efficiently identified synergistic drug combinations in a non-small cell lung cancer cell line, and our high-content analysis further revealed how individual drugs in the drug mix interact with each other to generate combinatorial drug response.

Proton therapy induces a local microglial neuroimmune response

Background and purposeAlthough proton therapy is increasingly being used in the treatment of paediatric and adult brain tumours, there are still uncertainties surrounding the biological effect of protons on the normal brain. Microglia, the brain-resident macrophages, have been shown to play a role in the development of radiation-induced neurotoxicity. However, their molecular and hence functional response to proton irradiation remains unknown. This study investigates the effect of protons on microglia by comparing the effect of photons and protons as well as the influence of age and different irradiated volumes. Materials and methodsRats were irradiated with 14 Gy to the whole brain with photons (X-rays), plateau protons, spread-out Bragg peak (SOBP) protons or to 50 % anterior, or 50 % posterior brain sub-volumes with plateau protons. RNA sequencing, validation of microglial priming gene expression using qPCR and high-content imaging analysis of microglial morphology were performed in the cortex at 12 weeks post irradiation. ResultsPhotons and plateau protons induced a shared transcriptomic response associated with neuroinflammation. This response was associated with a similar microglial priming gene expression signature and distribution of microglial morphologies. Expression of the priming gene signature was less pronounced in juvenile rats compared to adults and slightly increased in rats irradiated with SOBP protons. High-precision partial brain irradiation with protons induced a local microglial priming response and morphological changes. ConclusionOverall, our data indicate that the brain responds in a similar manner to photons and plateau protons with a shared local upregulation of microglial priming-associated genes, potentially enhancing the immune response to subsequent inflammatory challenges.

Morphological profiling in human neural progenitor cells classifies hits in a pilot drug screen for Alzheimer's disease.

Alzheimer's disease accounts for 60-70% of dementia cases. Current treatments are inadequate and there is a need to develop new approaches to drug discovery. Recently, in cancer, morphological profiling has been used in combination with high-throughput screening of small-molecule libraries in human cells in vitro. To test feasibility of this approach for Alzheimer's disease, we developed a cell morphology-based drug screen centred on the risk gene, SORL1 (which encodes the protein SORLA). Increased Alzheimer's disease risk has been repeatedly linked to variants in SORL1, particularly those conferring loss or decreased expression of SORLA, and lower SORL1 levels are observed in post-mortem brain samples from individuals with Alzheimer's disease. Consistent with its role in the endolysosomal pathway, SORL1 deletion is associated with enlarged endosomes in neural progenitor cells and neurons. We, therefore, hypothesized that multi-parametric, image-based cell phenotyping would identify features characteristic of SORL1 deletion. An automated morphological profiling method (Cell Painting) was adapted to neural progenitor cells and used to determine the phenotypic response of SORL1-/- neural progenitor cells to treatment with compounds from a small internationally approved drug library (TargetMol, 330 compounds). We detected distinct phenotypic signatures for SORL1-/- neural progenitor cells compared to isogenic wild-type controls. Furthermore, we identified 16 compounds (representing 14 drugs) that reversed the mutant morphological signatures in neural progenitor cells derived from three SORL1-/- induced pluripotent stem cell sub-clones. Network pharmacology analysis revealed the 16 compounds belonged to five mechanistic groups: 20S proteasome, aldehyde dehydrogenase, topoisomerase I and II, and DNA synthesis inhibitors. Enrichment analysis identified DNA synthesis/damage/repair, proteases/proteasome and metabolism as key pathways/biological processes. Prediction of novel targets revealed enrichment in pathways associated with neural cell function and Alzheimer's disease. Overall, this work suggests that (i) a quantitative phenotypic metric can distinguish induced pluripotent stem cell-derived SORL1-/- neural progenitor cells from isogenic wild-type controls and (ii) phenotypic screening combined with multi-parametric high-content image analysis is a viable option for drug repurposing and discovery in this human neural cell model of Alzheimer's disease.

Identification of Active Components for Sports Supplements: Machine Learning-Driven Classification and Cell-Based Validation.

The identification of active components is critical for the development of sports supplements. However, high-throughput screening of active components remains a challenge. This study sought to construct prediction models to screen active components from herbal medicines via machine learning and validate the screening by using cell-based assays. The six constructed models had an accuracy of >0.88. Twelve randomly selected active components from the screening were tested for their active potency on C2C12 cells, and 11 components induced a significant increase in myotube diameters and protein synthesis. The effect and mechanism of luteolin among the 11 active components as potential sports supplements were then investigated by using immunofluorescence staining and high-content imaging analysis. It showed that luteolin increased the skeletal muscle performance via the activation of PGC-1α and MAPK signaling pathways. Thus, high-throughput prediction models can be effectively used to screen active components as sports supplements.

Machine learning-assisted high-content imaging analysis of 3D MCF7 microtissues for estrogenic effect prediction

Endocrine-disrupting chemicals (EDCs) pose a significant threat to human well-being and the ecosystem. However, in managing the many thousands of uncharacterized chemical entities, the high-throughput screening of EDCs using relevant biological endpoints remains challenging. Three-dimensional (3D) culture technology enables the development of more physiologically relevant systems in more realistic biochemical microenvironments. The high-content and quantitative imaging techniques enable quantifying endpoints associated with cell morphology, cell–cell interaction, and microtissue organization. In the present study, 3D microtissues formed by MCF-7 breast cancer cells were exposed to the model EDCs estradiol (E2) and propyl pyrazole triol (PPT). A 3D imaging and image analysis pipeline was established to extract quantitative image features from estrogen-exposed microtissues. Moreover, a machine-learning classification model was built using estrogenic-associated differential imaging features. Based on 140 common differential image features found between the E2 and PPT group, the classification model predicted E2 and PPT exposure with AUC-ROC at 0.9528 and 0.9513, respectively. Deep learning-assisted analysis software was developed to characterize microtissue gland lumen formation. The fully automated tool can accurately characterize the number of identified lumens and the total luminal volume of each microtissue. Overall, the current study established an integrated approach by combining non-supervised image feature profiling and supervised luminal volume characterization, which reflected the complexity of functional ER signaling and highlighted a promising conceptual framework for estrogenic EDC risk assessment.

CRISPR activation as a platform to identify interferon stimulated genes with anti-viral function.

Interferon Stimulated Gene (ISG) expression plays a key role in the control of viral replication and development of a robust adaptive response. Understanding this dynamic relationship between the pathogen and host is critical to our understanding of viral life-cycles and development of potential novel anti-viral strategies. Traditionally, plasmid based exogenous prompter driven expression of ISGs has been used to investigate anti-viral ISG function, however there are deficiencies in this approach. To overcome this, we investigated the utility of CRISPR activation (CRISPRa), which allows for targeted transcriptional activation of a gene from its endogenous promoter. Using the CRISPRa-SAM system to induce targeted expression of a panel of anti-viral ISGs we showed robust induction of mRNA and protein expression. We then employed our CRISPRa-SAM ISG panel in several antiviral screen formats to test for the ability of ISGs to prevent viral induced cytopathic cell death (CPE) and replication of Dengue Virus (DENV), Zika Virus (ZIKV), West Nile Virus Kunjin (WNVKUN), Hepatitis A Virus (HAV) and Human Coronavirus 229E (HCoV-229E). Our CRISPRa approach confirmed the anti-viral activity of ISGs like IFI6, IFNβ and IFNλ2 that prevented viral induced CPE, which was supported by high-content immunofluorescence imaging analysis. This work highlights CRISPRa as a rapid, agile, and powerful methodology to identify and characterise ISGs and viral restriction factors.

The antibacterial activity of berberine against Cutibacterium acnes: its therapeutic potential in inflammatory acne.

Cutibacterium acnes (C. acnes) is a major pathogen implicated in the evolution of acne inflammation. Inhibition of C. acnes-induced inflammation is a prospective acne therapy strategy. Berberine (BBR), a safe and effective natural ingredient, has been proven to exhibit powerful antimicrobial and anti-inflammatory properties. However, the antimicrobial effect of BBR against C. acnes and its role in C. acnes-mediated inflammatory acne have not been explored. The objective of this investigation was to assess the antibacterial activity of BBR against C. acnes and its inhibitory effect on the inflammatory response. The results of in vitro experiments showed that BBR exhibited significant inhibition zones against four C. acnes strains, with the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) in the range of 6.25-12.5 μg/mL and 12.5-25 μg/mL, respectively. On the bacterial growth curve, the BBR-treated C. acnes exhibited obvious growth inhibition. Transmission electron microscopy (TEM) images indicated that BBR treatment resulted in significant morphological changes in C. acnes. High-content imaging analysis further confirmed that BBR could effectively inhibit the proliferation of C. acnes. The disruption of cell wall and cell membrane structure by BBR treatment was preliminary confirmed according to the leakage of cellular contents such as potassium (K+), magnesium (Mg2+), and alkaline phosphatase (AKP). Furthermore, we found that BBR could reduce the transcript levels of genes associated with peptidoglycan synthesis (murC, murD, mraY, and murG). Meanwhile, we investigated the modulatory ability of BBR on C. acnes-induced skin inflammation in mice. The results showed that BBR effectively reduced the number of C. acnes colonized in mice's ears, thereby alleviating ear swelling and erythema and significantly decreasing ear thickness and weight. In addition, BBR significantly decreased the levels of pro-inflammatory cytokines IL-6, IL-1β, and TNF-α in auricular tissues. These results suggest that BBR has the potential to treat inflammatory acne induced by C. acnes.

Immunofluorescence-Based Assay for High-Throughput Analysis of Multidrug Resistance Markers in Non-Small Cell Lung Carcinoma Patient-Derived Cells.

Lung cancer remains the leading cause of cancer death globally, with non-small cell lung cancer (NSCLC) accounting for the majority of cases. Multidrug resistance (MDR), often caused by ATP-binding cassette (ABC) transporters, represents a significant obstacle in the treatment of NSCLC. While genetic profiling has an important role in personalized therapy, functional assays that measure cellular responses to drugs are gaining in importance. We developed an automated microplate-based immunofluorescence assay for the evaluation of MDR markers ABCB1, ABCC1, and ABCG2 in cells obtained from NSCLC patients through high-content imaging and image analysis, as part of a functional diagnostic approach. This assay effectively discriminated cancer from non-cancer cells within mixed cultures, which is vital for accurate assessment of changes in MDR marker expression in different cell populations in response to anticancer drugs. Validation was performed using established drug-sensitive (NCI-H460) and drug-resistant (NCI-H460/R) NSCLC cell lines, demonstrating the assay's capacity to distinguish and evaluate different MDR profiles. The obtained results revealed wide-ranging effects of various chemotherapeutic agents on MDR marker expression in different patient-derived NSCLC cultures, emphasizing the need for MDR diagnostics in NSCLC. In addition to being a valuable tool for assessing drug effects on MDR markers in different cell populations, the assay can complement genetic profiling to optimize treatment. Further assay adaptations may extend its application to other cancer types, improving treatment efficacy while minimizing the development of resistance.

Abstract LB_B16: Quantification of immune-oncology drug responses in autologous co-cultures of ex vivo patient tumor tissues with PBMCs

Abstract Introduction Immuno-oncology drug treatments, including immune checkpoint inhibitors, represent a huge promise for cancer patients and have been clinically approved for some cancer indications. However, patient response rates stay relatively low (about 10-20% responders across indications) hampering the success of such drugs in clinical trials. In addition, current in vitro and in vivo pre-clinical models often lack the (immunological) complexity necessary to predict the clinical effectiveness of such drugs or drug combinations. To bridge this gap in translational models, we have recently developed the 3D Ex vivo Patient Tissue (EVPT) platform. The EVPT platform is leveraging short-term 3D ex vivo tumor culture system containing micro-tissues generated from fresh human tumor material and high content imaging analysis. The platform is preserving the innate tumor microenvironment including resident immune cells, which are crucial for addressing immunological drug responses. In this study we aimed to further boost immune compartment of the assay by addition of autologous immune cells (PBMCs) isolated from whole blood of the patient in parallel with ex vivo tumor processing. Methods Patient tumor tissues from resected NSCLC and muscle-invasive bladder cancer (MIBC) tumors and matching peripheral blood were obtained from commercial tissue providers and processed within 24 hours to preserve the TME. PBMCs were isolated from whole blood and pre-stained with cell tracker. Fresh, minimally processed tumor material was embedded in a protein-rich hydrogel with or without matching PBMCs and exposed to mono- and combination immunotherapies at various doses. Next, the phenotypic screening using our proprietary automated HCI analysis platform was performed. Where applicable, IHC biomarker, flow cytometry and cytokine measurements were performed on fixed tissues or culture supernatants. Results 3D ex vivo co-cultures were executed in 22 NSCLC and 5 MIBC patient samples. Immunological treatment responses varied between tested patients. When comparing co-culture to mono-culture conditions, one third of the samples showed baseline killing associated with PBMCs addition. About 20% of tissues from both indications responded to antiPD1 treatment (Pembrolizumab) and on average 50% of tissues responded to immunostimulatory control SEA. Overall best effects were observed for one test article that was used in three doses in combination with antiPD1. Five out five tested NSLCLC samples showed functional responses in these conditions as wells as two out five MIBC samples. In addition, it induced immunostimulatory effects on the PBMCs in the assay – increased numbers and tumor infiltration rates compared to vehicle control. Conclusions 3D Ex vivo Patient Tissue platform combined with autologous PBMCs offers supplementary readouts such as tumor infiltration and immune cell proliferation while providing TME-rich environment for functional immune-oncology drug testing. Citation Format: Niels Meesters, Sander Basten, Ezgi Kaya Aksoy, Mariusz Madej, Kuan Yan, Emma Spanjaard, Leo S. Price, Nataliia Beztsinna. Quantification of immune-oncology drug responses in autologous co-cultures of ex vivo patient tumor tissues with PBMCs [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 LB_B16.

WITHDRAWN: Detection and impact of hypoxic regions in multicellular tumor spheroid cultures formed by head and neck squamous cell carcinoma cells lines

In solid tumors like head and neck cancer (HNC), chronic and acute hypoxia have serious adverse clinical consequences including poorer overall patient prognosis, enhanced metastasis, increased genomic instability, and resistance to radiation-, chemo-, or immuno-therapies. However, cells in the two-dimensional monolayer cultures typically used for cancer drug discovery experience 20%-21% O2 levels (normoxic) which are 4-fold higher than O2 levels in normal tissues and ≥10-fold higher than in the hypoxic regions of solid tumors. The oxygen electrodes, exogenous bio-reductive markers, and increased expression of endogenous hypoxia-regulated proteins like HIF-1α generally used to mark hypoxic regions in solid tumors are impractical in large sample numbers and longitudinal studies. We used a novel homogeneous live-cell permeant HypoxiTRAK™ (HPTK) molecular probe compatible with high content imaging detection, analysis, and throughput to identify and quantify hypoxia levels in live HNC multicellular tumor spheroid (MCTS) cultures over time. Accumulation of fluorescence HPTK metabolite in live normoxic HNC MCTS cultures correlated with hypoxia detection by both pimonidazole and HIF-1α staining. In HNC MCTSs, hypoxic cytotoxicity ratios for the hypoxia activated prodrugs (HAP) evofosfamide and tirapazamine were much smaller than have been reported for uniformly hypoxic 2D monolayers in gas chambers, and many viable cells remained after HAP exposure. Cells in solid tumors and MCTSs experience three distinct O2 microenvironments dictated by their distances from blood vessels or MCTS surfaces, respectively; oxic, hypoxic, or intermediate levels of hypoxia. These studies support the application of more physiologically relevant in vitro 3D models that recapitulate the heterogeneous microenvironments of solid tumors for preclinical cancer drug discovery.

Integrated systems biology approach identifies gene targets for endothelial dysfunction.

Endothelial dysfunction (ED) is critical in the development and progression of cardiovascular (CV) disorders, yet effective therapeutic targets for ED remain elusive due to limited understanding of its underlying molecular mechanisms. To address this gap, we employed a systems biology approach to identify potential targets for ED. Our study combined multi omics data integration, with siRNA screening, high content imaging and network analysis to prioritise key ED genes and identify a pro- and anti-ED network. We found 26 genes that, upon silencing, exacerbated the ED phenotypes tested, and network propagation identified a pro-ED network enriched in functions associated with inflammatory responses. Conversely, 31 genes ameliorated ED phenotypes, pointing to potential ED targets, and the respective anti-ED network was enriched in hypoxia, angiogenesis and cancer-related processes. An independent screen with 17 drugs found general agreement with the trends from our siRNA screen and further highlighted DUSP1, IL6 and CCL2 as potential candidates for targeting ED. Overall, our results demonstrate the potential of integrated system biology approaches in discovering disease-specific candidate drug targets for endothelial dysfunction.

Feeling the Heat. Mapping the Epigenetic Modifications of Histone during Burn Wound Healing.

Burn injuries are observed throughout a wide range of ages, with over 1.1 million Americans suffering burns yearly, and half of these require hospitalization. Epigenetic modifications are fast-acting mechanisms that allow the human body to respond and adapt to environmental changes, including burn injuries. There is a lack of understanding of the epigenetic role during burn-induced tissue repair. Here, we characterize the histone modifications that follow burn injury, aiming at future pharmacological intervention using drugs capable of targeting epigenetic events. A clinically relevant porcine burn model was used to recapitulate the skin healing process after the burn. Isolated skin tissues at different time points were used to detect the acetylation levels of histones H3K27, H4K5, H4K8, and H4K12 as significant players of gene transcription using MetaXpress High-Content Imaging Analysis. We observed that the acetylation of histones is dynamically adjusted throughout healing, and its modifications are uniquely expressed according to the anatomical location and time of healing. We also observed that histone H4K5 is the most widely expressed during healing, followed by histone H3K27. We observed that histones expressed in intact skin tissue adjacent to the burn site could sense the burn injury by changing its histone acetylation pattern compared to control skin from uninjured and distant skin. Using a clinically relevant animal model, we have generated a comprehensive landscape of epigenetic modifications during burn healing. Our data will help us identify novel epi-drugs capable of manipulating histone modifications during healing to accelerate the healing process.