Preclinical Drug Screening Research Articles

The Dawning of a New Age of Preclinical Analgesic Drug Screening.

The Dawning of a New Age of Preclinical Analgesic Drug Screening.

Embedded Bioprinting of Tumor-Scale Pancreatic Cancer-Stroma 3D Models for Preclinical Drug Screening.

The establishment of organotypic preclinical models that accurately resemble the native tumor microenvironment at an anatomic human scale is highly desirable to level up in vitro platforms potential for screening candidate therapies. The bioengineering of anatomic-scaled three-dimensional (3D) models that emulate native tumor scale while recapitulating their cellular and matrix components remains, however, to be fully realized. In this focus, herein, we leveraged embedded 3D bioprinting for biofabricating pancreatic ductal adenocarcinoma (PDAC) in vitro models combining gelatin-methacryloyl and hyaluronic acid methacrylate extracellular matrix (ECM)-mimetic biomaterials with human pancreatic cancer cells and cancer-associated fibroblasts to generate in vitro models capable of emulating native tumor size (∼6 mm) and stromal elements. By using a viscoelastic continuous polymeric supporting bath, tumor-scale 3D models were rapidly generated (∼50 constructs/h) and easily recovered following in-bath visible light photocrosslinking. As a proof-of-concept, tissue-scale constructs displaying physiomimetic designs were biofabricated. These models also encompass the incorporation of a stromal compartment to better emulate the cellular components of the PDAC native tumor microenvironment (TME) and its stratified spatial organization. Cell-laden tumor-size constructs remained viable for up to 14 days and were responsive to Gemcitabine in a dose-dependent mode. Cancer-stroma models also exhibited increased drug resistance compared to their monotypic counterparts, highlighting the key role of stromal cells in chemotherapeutic resistance. Overall, we report for the first time the freeform biofabrication of PDAC models exhibiting anatomic scale, different structural complexities, and engineered cancer-stromal compartments, being highly valuable for preclinical screening of therapeutics.

Modelling myocardial ischemia/reperfusion injury with inflammatory response in human ventricular cardiac organoids.

Current therapeutic drug exploring targeting at myocardial ischemia/reperfusion (I/R) injury is limited due to the lack of humanized cardiac models that resemble myocardial damage and inflammatory response. Herein, we develop ventricular cardiac organoids from human induced pluripotent stem cells (hiPSCs) and simulate I/R injury by hypoxia/reoxygenation (H/R), which results in increased cardiomyocytes apoptosis, elevated oxidative stress, disrupted morphological structure and decreased beat amplitude. RNA-seq reveals a potential role of type I interferon (IFN-I) in this I/R injury model. We then introduce THP-1 cells and reveal inflammatory responses between monocytes/macrophages and H/R-induced ventricular cardiac organoids. Furthermore, we demonstrate Anifrolumab, an FDA approved antagonist of IFN-I receptor, effectively decreases IFN-I secretion and related gene expression, attenuates H/R-induced inflammation and oxidative stress in the co-culture system. This study advances the modelling of myocardial I/R injury with inflammatory response in human cardiac organoids, which provides a reliable platform for preclinical study and drug screening.

A point-of-research decision in synovial tissue engineering: Mesenchymal stromal cells, tissue derived fibroblast or CTGF-mediated mesenchymal-to-fibroblast transition

Rheumatoid arthritis (RA) and osteoarthritis (OA) are prevalent inflammatory joint diseases characterized by synovitis, cartilage, and bone destruction. Fibroblast-like synoviocytes (FLSs) of the synovial membrane are a decisive factor in arthritis, making them a target for future therapies. Developing novel strategies targeting FLSs requires advanced in vitro joint models that accurately replicate non-diseased joint tissue. This study aims to identify a cell source reflecting physiological synovial fibroblasts. Therefore, we newly compared the phenotype and metabolism of “healthy” knee-derived FLSs from patients with ligament injuries (trauma-FLSs) to mesenchymal stromal cells (MSCs), their native precursors. We differentiated MSCs into fibroblasts using connective tissue growth factor (CTGF) and compared selected protein and gene expression patterns to those obtained from trauma-FLSs and OA-FLSs. Based on these findings, we explored the potential of an MSC-derived synovial tissue model to simulate a chronic inflammatory response akin to that seen in arthritis. We have identified MSCs as a suitable cell source for synovial tissue engineering because, despite metabolic differences, they closely resemble human trauma-derived FLSs. CTGF-mediated differentiation of MSCs increased HAS2 expression, essential for hyaluronan synthesis. It showed protein expression patterns akin to OA-FLSs, including markers of ECM components and fibrosis, and enzymes leading to a shift in metabolism towards increased fatty acid oxidation. In general, cytokine stimulation of MSCs in a synovial tissue model induced pro-inflammatory and pro-angiogenic gene expression, hyperproliferation, and increased glucose consumption, reflecting cellular response in human arthritis. We conclude that MSCs can serve as a proxy to study physiological synovial processes and inflammatory responses. In addition, CTGF-mediated mesenchymal-to-fibroblast transition resembles OA-FLSs. Thus, we emphasize MSCs as a valuable cell source for tools in preclinical drug screening and their application in tissue engineering.

Real-time electro-mechanical profiling of dynamically beating human cardiac organoids by coupling resistive skins with microelectrode arrays

Cardiac organoids differentiated from induced pluripotent stem cells are emerging as a promising platform for pre-clinical drug screening, assessing cardiotoxicity, and disease modelling. However, it is challenging to simultaneously measure mechanical contractile forces and electrophysiological signals of cardiac organoids in real-time and in-situ with the existing methods. Here, we present a biting-inspired sensory system based on a resistive skin sensor and a microelectrode array. The bite-like contact can be established with a micromanipulator to precisely position the resistive skin sensor on the top of the cardiac organoid while the 3D microneedle electrode array probes from underneath. Such reliable contact is key to achieving simultaneous electro-mechanical measurements. We demonstrate the use of our system for modelling cardiotoxicity with the anti-cancer drug doxorubicin. The electro-mechanical parameters described here elucidate the acute cardiotoxic effects induced by doxorubicin. This integrated electro-mechanical system enables a suite of new diagnostic options for assessing cardiac organoids and tissues.

Patient-derived organoids and mini-PDX for predicting METN375S-mutated lung cancer patient clinical therapeutic response

Lung cancer as a molecularly and histologically high heterogonous disease, there is an urgent need to predict lung cancer patients' responses to anti-cancer treatment, and patient-derived organoids (PDOs) have been recognized as a valuable platform for preclinical drug screening. In this study, we successfully established 26 PDO lines from various subtypes of lung cancers including benign tumor, adenocarcinoma, squamous cell carcinoma, adenosquamous carcinoma, large-cell carcinoma, and small-cell carcinoma. These PDOs were shown to retain the major genomic and histological characteristics of primary tumors and remain stable during long-term culture. With the help of targeted genomic sequencing, we found that lung cancer that harbors METN375S mutation is selectively sensitive to afatinib, and a combination of afatinib and gemcitabine induced synthetic lethality in PDO and mini-PDX models. In summary, our findings demonstrate the potential of PDO in predicting lung cancer drug response, and reveal a promising strategy for METN375S mutant lung cancer treatment.

Genetic and Environmental Factors Co-Contributing to Behavioral Abnormalities in adnp/adnp2 Mutant Zebrafish.

Human mutations of ADNP and ADNP2 are known to be associated with neural developmental disorders (NDDs), including autism spectrum disorders (ASDs) and schizophrenia (SZ). However, the underlying mechanisms remain elusive. In this study, using CRISPR/Cas9 gene editing technology, we generated adnp and adnp2 mutant zebrafish models, which exhibited developmental delays, brain deficits, and core behavioral features of NDDs. RNA sequencing analysis of adnpa-/-; adnpb-/- and adnp2a-/-; adnp2b-/- larval brains revealed altered gene expression profiles affecting synaptic transmission, autophagy, apoptosis, microtubule dynamics, hormone signaling, and circadian rhythm regulation. Validation using whole-mount in situ hybridization (WISH) and real-time quantitative PCR (qRT-PCR) corroborated these findings, supporting the RNA-seq results. Additionally, loss of adnp and adnp2 resulted in significant downregulation of pan-neuronal HuC and neuronal fiber network α-Tubulin signals. Importantly, prolonged low-dose exposure to environmental endocrine disruptors (EEDs) aggravated behavioral abnormalities in adnp and adnp2 mutants. This comprehensive approach enhances our understanding of the complex interplay between genetic mutations and environmental factors in NDDs. Our findings provide novel insights and experimental foundations into the roles of adnp and adnp2 in neurodevelopment and behavioral regulation, offering a framework for future preclinical drug screening aimed at elucidating the pathogenesis of NDDs and related conditions.

Application and prospect of organoid technology in breast cancer.

Breast cancer is the most common malignant tumor in women. Due to the high heterogeneity of breast cancer cells, traditional in vitro research models still have major limitations. Therefore, it is urgent to establish an experimental model that can accurately simulate the characteristics of human breast cancer. Breast cancer organoid technology emerged as the times required, that is, to construct tissue analogs with organ characteristics by using a patient's tumor tissue through 3D culture in vitro. Since the breast cancer organoid can fully preserve the histology and genetic characteristics of the original tumor, it provides a reliable model for preclinical drug screening, establishment of breast cancer organoid biobanks, research into the mechanisms of tumor development, and determination of cancer targets. It has promoted personalized treatment for clinical breast cancer patients. This article mainly focuses on recent research progress and applications of organoid technology in breast cancer, discussing the current limitations and prospects of breast cancer organoid technology.

Predicting Clinical Outcomes of SARS-CoV-2 Drug Efficacy with a High-Throughput Human Airway Microphysiological System.

The average cost to bring a new drug from its initial discovery to a patient's bedside is estimated to surpass $2 billion and requires over a decade of research and development. There is a need for new drug screening technologies that can parse drug candidates with increased likelihood of clinical utility early in development in order to increase the cost-effectiveness of this pipeline. For example, during the COVID-19 pandemic, resources were rapidly mobilized to identify effective therapeutic treatments but many lead antiviral compounds failed to demonstrate efficacy when progressed to human trials. To address the lack of predictive preclinical drug screening tools, PREDICT96-ALI, a high-throughput (n = 96) microphysiological system (MPS) that recapitulates primary human tracheobronchial tissue,is adapted for the evaluation of differential antiviral efficacy of native SARS-CoV-2 variants of concern. Here, PREDICT96-ALI resolves both the differential viral kinetics between variants and the efficacy of antiviral compounds over a range of drug doses. PREDICT96-ALI is able to distinguish clinically efficacious antiviral therapies like remdesivir and nirmatrelvir from promising lead compounds that do not show clinical efficacy. Importantly, results from this proof-of-concept study track with known clinical outcomes, demonstrate the feasibility of this technology as a prognostic drug discovery tool.

Human and Murine Cell Lines for Adrenocortical Carcinoma and Pheochromocytoma

Adrenocortical carcinoma (ACC) and pheochromocytoma (PCC) are malignancies originating from distinct layers of the adrenal gland. ACCs arise from the adrenal cortex, are often detected at advanced stages and are associated with poor prognosis. PCCs are mostly benign, arise from the adrenal medulla and have a variable prognosis, with 10% of PCCs resulting in metastasis. Genetic background strongly influences metastasis of PCCs, and no reliable biomarkers that predict metastatic behavior exist to date. Current therapeutic strategies for both ACCs and PCCs are overall limited. Thus, novel preclinical models and drug screening approaches need to be established to aid in the identification of more promising drugs and treatment schemes. In this review, we summarize the currently available human and murine cell lines for both tumor entities.

Gastric Cancer Assembloids Derived from Patient-Derived Xenografts: A Preclinical Model for Therapeutic Drug Screening.

The construction of reliable preclinical models is crucial for understanding the molecular mechanisms involved in gastric cancer and for advancing precision medicine. Currently, existing in vitro tumor models often do not accurately replicate the human gastric cancer environment and are unsuitable for high-throughput therapeutic drug screening. In this study, droplet microfluidic technology is employed to create novel gastric cancer assembloids by encapsulating patient-derived xenograft gastric cancer cells and patient stromal cells in Gelatin methacryloyl (GelMA)-Gelatin-Matrigel microgels. The usage of GelMA-Gelatin-Matrigel composite hydrogel effectively alleviated cell aggregation and sedimentation during the assembly process, allowing for the handling of large volumes of cell-laden hydrogel and the uniform generation of assembloids in a high-throughput manner. Notably, the patient-derived xenograft assembloids exhibited high consistency with primary tumors at both transcriptomic and histological levels, and can be efficiently scaled up for preclinical drug screening efforts. Furthermore, the drug screening results clearly demonstrated that the in vitro assembloid model closely mirrored in vivo drug responses. Thus, these findings suggest that gastric cancer assembloids, which effectively replicate the in vivo tumor microenvironment, show promise for enabling more precise high-throughput drug screening and predicting the clinical outcomes of various drugs.

In vivo organoid growth monitoring by stimulated Raman histology

Patient-derived tumor organoids have emerged as a crucial tool for assessing the efficacy of chemotherapy and conducting preclinical drug screenings. However, the conventional histological investigation of these organoids necessitates their devitalization through fixation and slicing, limiting their utility to a single-time analysis. Here, we use stimulated Raman histology (SRH) to demonstrate non-destructive, label-free virtual staining of 3D organoids, while preserving their viability and growth. This novel approach provides contrast similar to conventional staining methods, allowing for the continuous monitoring of organoids over time. Our results demonstrate that SRH transforms organoids from one-time use products into repeatable models, facilitating the efficient selection of effective drug combinations. This advancement holds promise for personalized cancer treatment, allowing for the dynamic assessment and optimization of chemotherapy treatments in patient-specific contexts.

In Situ Self-Assembling Liver Spheroids with Synthetic Nanoscaffolds for Preclinical Drug Screening Applications.

Drug-induced liver injury (DILI) is one of the most common reasons for acute liver failure and a major reason for the withdrawal of medications from the market. There is a growing need for advanced in vitro liver models that can effectively recapitulate hepatic function, offering a robust platform for preclinical drug screening applications. Here, we explore the potential of self-assembling liver spheroids in the presence of electrospun and cryomilled poly(caprolactone) (PCL) nanoscaffolds for use as a new preclinical drug screening tool. This study investigated the extent to which nanoscaffold concentration may have on spheroid size and viability and liver-specific biofunctionality. The efficacy of our model was further validated using a comprehensive dose-dependent acetaminophen toxicity protocol. Our findings show the strong potential of PCL-based nanoscaffolds to facilitate in situ self-assembly of liver spheroids with sizes under 350 μm. The presence of the PCL-based nanoscaffolds (0.005 and 0.01% w/v) improved spheroid viability and the secretion of critical liver-specific biomarkers, namely, albumin and urea. Liver spheroids with nanoscaffolds showed improved drug-metabolizing enzyme activity and greater sensitivity to acetaminophen compared to two-dimensional monolayer cultures and scaffold-free liver spheroids. These promising findings highlight the potential of our nanoscaffold-based liver spheroids as an in vitro liver model for drug-induced hepatotoxicity and drug screening.

Hepatic spheroid-on-a-chip: Fabrication and characterization of a spheroid-based in vitro model of the human liver for drug screening applications.

The integration of microfabrication and microfluidics techniques into cell culture technology has significantly transformed cell culture conditions, scaffold architecture, and tissue biofabrication. These tools offer precise control over cell positioning and enable high-resolution analysis and testing. Culturing cells in 3D systems, such as spheroids and organoids, enables recapitulating the interaction between cells and the extracellular matrix, thereby allowing the creation of human-based biomimetic tissue models that are well-suited for pre-clinical drug screening. Here, we demonstrate an innovative microfluidic device for the formation, culture, and testing of hepatocyte spheroids, which comprises a large array of patterned microwells for hosting hepatic spheroid culture in a reproducible and organized format in a dynamic fluidic environment. The device allows maintaining and characterizing different spheroid sizes as well as exposing to various drugs in parallel enabling high-throughput experimentation. These liver spheroids exhibit physiologically relevant hepatic functionality, as evidenced by their ability to produce albumin and urea at levels comparable to in vivo conditions and the capability to distinguish the toxic effects of selected drugs. This highlights the effectiveness of the microenvironment provided by the chip in maintaining the functionality of hepatocyte spheroids. These data support the notion that the liver-spheroid chip provides a favorable microenvironment for the maintenance of hepatocyte spheroid functionality.

Development and characterization of a non-human primate model of disseminated synucleinopathy.

The presence of a widespread cortical synucleinopathy is the main neuropathological hallmark underlying clinical entities such as Parkinson's disease with dementia (PDD) and dementia with Lewy bodies (DLB). There currently is a pressing need for the development of non-human primate (NHPs) models of PDD and DLB to further overcome existing limitations in drug discovery. Here we took advantage of a retrogradely-spreading adeno-associated viral vector serotype 9 coding for the alpha-synuclein A53T mutated gene (AAV9-SynA53T) to induce a widespread synucleinopathy of cortical and subcortical territories innervating the putamen. Four weeks post-AAV deliveries animals were sacrificed and a comprehensive biodistribution study was conducted, comprising the quantification of neurons expressing alpha-synuclein, rostrocaudal distribution and their specific location. Intraputaminal deliveries of AAV9-SynA53T lead to a disseminated synucleinopathy throughout ipsi- and contralateral cerebral cortices, together with transduced neurons located in the ipsilateral caudal intralaminar nuclei and in the substantia nigra pars compacta (leading to thalamostriatal and nigrostriatal projections, respectively). Cortical afferent systems were found to be the main contributors to putaminal afferents (superior frontal and precentral gyri in particular). Obtained data extends current models of synucleinopathies in NHPs, providing a reproducible platform enabling the adequate implementation of end-stage preclinical screening of new drugs targeting alpha-synuclein.

Abstract 6625: Development of novel mixed-cell models to capture heterogeneity in castration-resistant prostate cancer

Abstract Heterogeneity is ubiquitous in cancer and treatment responses among patient cohorts are highly variable, leading to drug resistance and disease relapse. Yet, preclinical drug screening is usually performed in cell lines or patient cells, one at a time, without consideration of cancer heterogeneity. Consequentially, positive outcomes obtained in the preclinical stage do not translate well into subsequent clinical successes. Castration-resistant prostate cancer (CRPC) is a highly lethal form of prostate cancer (PC) exhibiting a high degree of genetic and phenotypic heterogeneity with very few therapeutic options. Therefore, we created mixed-cell models depicting heterogeneity in various clinical contexts, where multiple PC cell lines representative of distinct CRPC tumor variants were labeled and combined in co-cultures to mimic the complex molecular landscape of CRPC patient cohorts. Specifically, transcriptomic profiles of PC cell lines were clustered with patient tumor specimens to identify cell lines that are genetically similar to distinct patient clusters representing CRPC tumor subtypes. Since heterogeneity has been linked to the clinical efficacy of combinatorial therapies, we applied these models to evaluate drug combinations. A combination of docetaxel and dasatinib that was previously assessed in a PC trial, was tested in the mixed-cell model and experimental findings concurred with the published clinical results, demonstrating the utility and accuracy of the model. Additionally, a computational model, IDACombo, was employed to nominate novel potentially efficacious drug combinations using monotherapy response data of cancer cell lines, a number of which were successfully validated in the mixed-cell model. More importantly, we demonstrated that while individual cell line screens may result in erroneous conclusions, combination efficacy can be accurately measured in a heterogeneous cell pool emulating a diverse patient cohort. We further explored phenotypic heterogeneity in advanced disease states, by mixing parent and standard-of-care (SOC)-resistant CRPC clonal variants. Drugs with selective potency in the resistant (vs. the parent) clone were computational prioritized and when combined with the SOC and tested in the mixed-cell models, outperformed either monotherapy. Additionally, we investigated the effects of altering the relative proportion of the constituent clones to mimic different stages of acquired therapy resistance. Furthermore, we generated mixed-cell xenograft models by subcutaneously injecting the labeled cell-line mixtures in mice and characterized the harvested tumors to detect and quantify the individual subpopulations. Development of these preclinical models holds enormous promise not only for advancing novel therapeutic strategies for cancer, but also for providing insights into the mechanisms of resistance and recurrence. Citation Format: Sampreeti Jena, Daniel Kim, Adam M. Lee, Weijie Zhang, Scott Dehm, R. Stephanie Huang. Development of novel mixed-cell models to capture heterogeneity in castration-resistant prostate cancer [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 6625.

Abstract 6914: Genomic landscape and stability of preclinical models in NCI's patient-derived models repository

Abstract Background: Patient-derived xenograft (PDX) models serve as a powerful tool for cancer translational research. However, it is unclear to what extent PDX models reflect the genomic intratumoral heterogeneity and genomic aberrations present within the original tumor sample. The National Cancer Institute (NCI) has developed a Patient-Derived Models Repository (PDMR; https://pdmr.cancer.gov/) consisting of PDX, organoids (PDOrg), and tumor cell cultures (PDC) from patients with diverse cancer histologies. We have conducted an in-depth investigation into the genomic stability of PDXs at early passaging and tumor heterogeneity in a large set of preclinical models including rare cancers. Methods: Tumor specimens were used to establish 1114 models from 1034 patients. For whole exome sequencing (WES) and RNASeq analysis, 1059 models with at least 1 PDX sample and 55 models with only a PDC or PDOrg were used. Analyzed specimens represent the original patient specimens, PDX passages P0, P1, P2, and P3+ and in vitro models. 80% of the PDX specimens were within passages P0 to P2. Results: Genomic stability in PDMR models was maintained through early passages (P0 - P2) and across independent lineages in PDMR models based on the following observations: 1) variant allele frequencies (VAF) of somatic driver mutations showed no major deviations (exceeding ±10%) when using the stromal fraction corrected VAF from originator data over PDX passages; 2) the median change in the fraction of genome impacted by copy number alterations (CNA) from the originator specimens through passages P0 - P2 was statistically inconsequential, although there was a significant increase in CNA fraction, from 5.3% at P0 initially to 18% by P3; 3) gene expression profiles of specimens within a given PDX model formed clusters in principal component analysis (PCA) plots and showed high correlation (>99.5% models with a Spearman coefficient of >= 0.8). The majority of the PDC and PDOrg specimens exhibited similar findings when compared to the original tumor samples. Furthermore, the positive percent agreement (PPA) was performed to measure the similarity between the patient's tumor and all available derived PDX specimens, with a median PPA over 90%, indicating a high level of retained heterogeneity within the PDX models. Lastly, 69% of models in NCI PDMR had predictive biomarkers, ranging from OncoKB level of evidence 1-4, which could be used to evaluate targeted therapeutics in preclinical studies. Conclusion: The NCI PDMR has a large and histologically diverse cancer representation. In this analysis, the PDXs exhibited genomic stability within early passages and preserved the majority of tumor heterogeneity observed in the patient specimens. NCI PDMR thus represents a valuable resource for researchers interested in preclinical drug screening or other investigations. Citation Format: Ting-Chia Chang, Biswajit Das, Li Chen, Peter I-Fan Wu, Yvonne A. Evrard, Rini Pauly, Dianne L. Newton, Shahanawaz Jiwani, Sergio Y. Alcoser, Luke H. Stockwin, Corinne E. Camalier, Tomas Forbes, Nikitha Nair, Alyssa Chapman, Lindsay Dutko, Michael Mullendore, Tara Grinnage-Pulley, Kimberly Klarmann, Sarah B. Miller, Chris A. Karlovich, Alice P. Chen, P Mickey Williams, Melinda G. Hollingshead, James H. Doroshow. Genomic landscape and stability of preclinical models in NCI's patient-derived models repository [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 6914.

Abstract 6898: Cholangiocarcinoma patient-derived models in the NCI Patient-Derived Models Repository

Abstract Cholangiocarcinoma (CHOL) is an aggressive rare malignancy arising in the biliary tract with a 5-year relative survival rate of 10% and a 60-70% recurrence rate following surgical intervention. Advances in treatment strategies are hampered by the lack of well annotated and characterized preclinical models. The National Cancer Institute’s Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) has developed a national repository of Patient-Derived Models (PDMs) comprised of patient-derived xenografts (PDXs), in vitro patient-derived tumor cell cultures (PDCs) and cancer associated fibroblasts (CAFs) as well as patient-derived organoids (PDOrg). These PDMs are clinically annotated with molecular information available in an easily accessible database for the extramural community. To date, 94 patient CHOL tumor specimens (resections, biopsies, rapid autopsy) have been received from 55 unique patients with an overall PDX take rate of 36.3% (80 assessable specimens). There are currently 15 CHOL PDX models available for the research community to request with 14 more in final QC. Nine of the 15 public PDX models were generated from unique lesions in two rapid autopsy patients and while histo-morphologically consistent, some genomic heterogeneity is observed between the unique anatomical locations likely due to tumor evolution during metastasis. In addition, 27 in vitro PDOrgs, PDCs, and CAFs have been generated from patient or PDX material matched to most of the existing PDX models to allow for comparative translation research. The genetic landscape of the CHOL PDXs includes oncogenic drivers in NRAS, IDH1, ERBB2, TP53, KRAS and FGFR2 fusions; OncoKB likely oncogenic variants including ARID1A, AXIN1 and BAP1; and CDKN2A deep deletions representing most of the common alterations in CHOL. Early passage preclinical PDX and in vitro models for CHOL, and many other cancer types, with translational relevant features along with associated NextGen sequencing and patient treatment history are available from the NCI PDMR. Availability of preclinical models that can be used to study these cancers and improve preclinical drug screening is of high importance to better understand the biology of these cancers and prioritize novel therapeutics from bench to clinic. Funded by NCI Contract No. HHSN261200800001E Citation Format: Yvonne A. Evrard, Cindy R. Timme, Biswajit Das, Gareth Bliss, Carrie Bonomi, Carley Border, Ting-Chia Chang, Alice Chen, Li Chen, Michelle A. Crespo-Eugeni, Kevin Cooper, Natalie Czarra, Isabella Czernia, Kelly Dougherty, Marion Gibson, Tara Grinnage-Pulley, Shahanawaz Jiwani, Keegan Kalmbach, Chris A. Karlovich, Chelsea McGlynn, Michael Mullendore, Matthew Murphy, Rini Pauly, Kevin Plater, Jessica Steed, Luke Stockwin, Shannon Uzelac, Peter I-Fan Wu, Dianne L. Newton, P. Mickey Williams, Melinda G. Hollingshead, James H. Doroshow. Cholangiocarcinoma patient-derived models in the NCI Patient-Derived Models Repository [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 6898.

Abstract 4268: Engineered hydrogel elucidates contributions of matrix mechanics to pathobiology of adenocarcinoma and identify matrix-activated therapeutic targets

Abstract Dysregulation of the extracellular matrix (ECM) properties disturbs tissue homeostasis and contributes to pathological conditions, such as cancer. Recent studies have demonstrated that ECM stiffening is associated with metaplasia-dysplasia-adenocarcinoma sequence in the esophagus. This underscores a compelling need to develop a physiologically-relevant 3D culture model to enable the study of the independent contribution of matrix stiffness to the initiation and progression of esophageal adenocarcinoma (EAC). Such a model will then serve as a platform for pre-clinical drug screening in the context of matrix properties. In this context, we have engineered a hyaluronic acid-based 3D hydrogel platform that supports the growth and differentiation of patient-derived Barrett’s esophagus (BE) organoids, a precursor to EAC, as well as patient-derived EAC organoids. The engineered biomaterial 3D platform allows control over matrix stiffness to better recapitulate the mechanically dynamic esophageal cancer microenvironment and help identify therapeutic targets in EAC.Our data demonstrates that BE and EAC organoid density, growth and proliferation can be controlled by matrix stiffness. RNA sequencing data show that increased matrix stiffness promotes changes in the transcriptional profiles of BE and EAC organoids, revealing enrichment of pathways associated with tumorigenesis and disease progression. Furthermore, we demonstrate through molecular and functional assays that increased matrix stiffness endows stem-like properties to the EAC organoids via Yap-Sox9 mechano-activation. Finally, targeted therapy studies in our in vitro and in vivo engineered environments revealed that Yap inhibition regressed the effects of increased matrix stiffness in EAC organoids. In summary, our data suggest that matrix mechanics have a significant role in activation of EAC-associated signaling pathways in patient-derived BE and EAC organoids. We also demonstrate that the engineered hydrogel serves as a platform to identify potential therapeutic targets to disrupt the contribution of pro-tumorigenic matrix mechanics in EAC. Together, these studies establish an engineered patient-derived organoid culture platform that can be used to elucidate underlying matrix-mediated mechanisms of the metaplasia-dysplasia-adenocarcinoma sequence and inform the development of novel therapeutics that target ECM stiffness in EAC. FUNDING SOURCES: NCI P01CA098101, U54 CA163004 and NIDDK K01 DK133620. Citation Format: Ricardo Cruz-Acuna, Secunda W. Kariuki, Kensuke Sugiura, Spyros Karaiskos, Eleanor M. Plaster, Claudia Loebel, Gizem Efe, Tatiana Karakasheva, Joel T. Gabre, Jianhua Hu, Jason A. Burdick, Anil K. Rustgi. Engineered hydrogel elucidates contributions of matrix mechanics to pathobiology of adenocarcinoma and identify matrix-activated therapeutic targets [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 4268.

Abstract 4247: Miniaturizing patient-derived organoid screening assays for predictive drug testing

Abstract Colorectal cancer (CRC) ranks as the third leading cause of both cancer incidence and cancer-related mortality. A significant portion of CRC patients diagnosed with de novo metastatic disease face limited benefits from conventional treatment options, often accompanied by substantial side effects. This underscores the pressing need for more effective preclinical models to predict patient responses in clinical settings. Patient-derived organoids (PDOs or HUB Organoids®) represent a pivotal breakthrough in preclinical modeling. These organoids are directly derived from patient tissue, faithfully mirroring the patient's disease. While HUB Organoid Technology is currently applicable for preclinical drug screening, it is essential to expedite the transition from patient diagnosis to the delivery of PDO-based results to directly benefit patients. In a collaborative effort with Yamaha Motor, we have optimized the Yamaha CELL HANDLERTM for the automated transfer of organoids, offering enhanced precision and efficiency in handling a significantly reduced number of organoids per screening plate, compared to conventional methods. Moreover, we have developed an image-based readout system that enables precise quantification of organoid numbers, ensuring high assay quality. Utilizing this developed automated platform, we conducted a proof-of-concept investigation into PDO responses to chemotherapy in comparison to corresponding patient responses. The correlation between PDO and patient responses demonstrated a strong connection, highlighting the potential of the developed automated platform for predictive drug testing. In summary, this work signifies the development of an automated workflow that synergizes patient-representative HUB Organoids® with cutting-edge robotics from Yamaha Motor. The described workflow reduces the number of organoids needed per screening well, streamlining patient response prediction, potentially leading to faster diagnoses, and ultimately optimizing patient outcomes. Citation Format: Yasmine Abouleila, Roel Verkerk, Mayke Doorn, Timo Voskuilen, Gakuro Harada, Masahiko Watanabe, Lidwien Smabers, Hideaki Kyan, Takahiko Kumagai, Yuichi Hikichi, Rene Overmeer, Jeanine Roodhart, Kiyotaka Matsuno, Carla Verissimo, Sylvia Boj. Miniaturizing patient-derived organoid screening assays for predictive drug testing [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 4247.