DDRE-42. TOWARDS PRECISION MEDICINE: AUTOMATED DRUG SCREENING PLATFORM UTILIZING TUMOR-ORGANOIDS TO IDENTIFY PATIENT-SPECIFIC DRUG-RESPONSES IN MENINGIOMA

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi83-vi83
Author(s):  
Gerhard Jungwirth ◽  
Adrian Paul ◽  
Cao Junguo ◽  
Andreas Unterberg ◽  
Amir Abdollahi ◽  
...  

Abstract Tumor-organoids (TO) are mini-tumors generated from tumor tissue preserving its genotype and phenotype by maintaining the cellular heterogeneity and important components of the tumor microenvironment. We recently developed a protocol to reliably establish TOs from meningioma (MGM) in large quantities. The use of TOs in combination with lab automation holds great promise for drug discovery and screening of comprehensive drug libraries. This might help to tailor patient-specific therapy in the future. The aim of our study was to establish an automated drug screening platform utilizing TOs. For this purpose, we established TOs by controlled reaggregation of freshly prepared single cell suspension of MGM tissue samples in the high-throughput format of 384-well plates. The drug screening was performed fully automated by utilizing the robotic liquid handler Hamilton Microlab STAR and a drug library containing 166 FDA-approved oncology agents. Viability was assessed with CellTiterGlo3D. In total, we performed the drug screening with 166 drugs on TOs from 11 patients suffering from MGM (n=8 WHO°I, n=2 WHO°II, n=1 WHO°III). The top five most effective drugs resulted in a decrease of TO viability ranging from 84.6–63.3%. K-means clustering analysis resulted in groupings of drugs with similar modes of action. One cluster consisted of epigenetic drugs while another cluster consisted of several proteasome inhibitors. However, when looking at a patient-individual level, in 11 patients 44 of 166 drugs, were among the top 10 most effective drugs, providing strong evidence for heterogeneous drug-responses in MGM patients. Taken together, we successfully developed an automated drug screening platform pipeline utilizing TOs from MGM to identify patient-specific drug-responses. The observed intra-individual differences of drug responses mandate for a personalized testing of comprehensive drug libraries in TOs to tailor more effective therapies in MGM patients.

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi221-vi222
Author(s):  
Gerhard Jungwirth ◽  
Tao Yu ◽  
Cao Junguo ◽  
Catharina Lotsch ◽  
Andreas Unterberg ◽  
...  

Abstract Tumor-organoids (TOs) are novel, complex three-dimensional ex vivo tissue cultures that under optimal conditions accurately reflect genotype and phenotype of the original tissue with preserved cellular heterogeneity and morphology. They may serve as a new and exciting model for studying cancer biology and directing personalized therapies. The aim of our study was to establish TOs from meningioma (MGM) and to test their usability for large-scale drug screenings. We were capable of forming several hundred TO equal in size by controlled reaggregation of freshly prepared single cell suspension of MGM tissue samples. In total, standardized TOs from 60 patients were formed, including eight grade II and three grade III MGMs. TOs reaggregated within 3 days resulting in a reducted diameter by 50%. Thereafter, TO size remained stable throughout a 14 days observation period. TOs consisted of largely viable cells, whereas dead cells were predominantly found outside of the organoid. H&E stainings confirmed the successful establishment of dense tissue-like structures. Next, we assessed the suitability and reliability of TOs for a robust large-scale drug testing by employing nine highly potent compounds, derived from a drug screening performed on several MGM cell lines. First, we tested if drug responses depend on TO size. Interestingly, drug responses to these drugs remained identical independent of their sizes. Based on a sufficient representation of low abundance cell types such as T-cells and macrophages an overall number of 25.000 cells/TO was selected for further experiments revealing FDA-approved HDAC inhibitors as highly effective drugs in most of the TOs with a mean z-AUC score of -1.33. Taken together, we developed a protocol to generate standardized TO from MGM containing low abundant cell types of the tumor microenvironment in a representative manner. Robust and reliable drug responses suggest patient-derived TOs as a novel drug testing model in meningioma research.


Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1352-1352 ◽  
Author(s):  
Diana Azzam ◽  
Claude-Henry Volmar ◽  
Al-Ali Hassan ◽  
Aymee Perez ◽  
Justin M. Watts ◽  
...  

Abstract Introduction - With rapidly advancing sequencing technology, the extent of genetic diversity in AML has never been more apparent. A Òone size fits allÓ approach can no longer be justified. Sequencing studies have also uncovered several actionable targets, yet no targeted therapies are FDA approved for use in the US. AML therefore, has significant potential for personalized therapeutics. Several challenges exist, however. The masses of data generated by high-throughput technologies are challenging to manage, visualize, and convert to knowledge required to improve outcomes. A cross-disciplinary systems biology effort is required, to visualize inter-connected events within leukemic blasts that ultimately contribute to the disease phenotype and inform on rational selection of therapeutic approaches. In the current study, we outline a complimentary functional and genomic screening approach to identify clinical drug candidates for re-purposing in patients with relapsed refractory AML. Methods - In this proof-of principle study, we optimized an ex vivo high-throughput drug screening platform measuring AML cell survival after exposure to over 200 U.S. FDA approved oncology drugs (including conventional chemotherapeutics, proteasome inhibitors, anti-metabolites, transcriptional inhibitors and targeted kinase inhibitors). This multiplex assay is designed for individual AML patients and tests agents over a 10,000-fold concentration range. We screened patient derived blasts against normal bone marrow mononuclear cells to identify the most effective leukemia selective agents. To compliment this functional ex-vivo screen, we employed a genomics approach using predictive simulation software to generate patient specific avatars which map individual dysregulated and interconnecting signaling pathways. The avatar technology will then identify candidate agents at critical impact points within these pathways. Results - Through phenotype screening of primary cells collected from a highly refractory AML patient (patient # PD001), our ex vivo assay identified a list of drugs based on their ability to effectively and selectively reduce the viability of the patients leukemic blasts in culture. Candidate agents are listed according to selective drug sensitivity scores (sDSS), calculated based on the comparative ability of each drug to reduce viability of primary cells vs normal bone marrow mononuclear cells. The highest sDSS indicates the most selective and effective drugs for each individual patient (Figure 1, patient sample PD001). The patient specific avatar generated for patient PD001 identified a series of dysregulated pathways converging on cell proliferation and viability. Both functional and genomic approaches identified the tyrosine kinase inhibitor ponatinib, as a potentially relevant clinical candidate. Potentially effective combination approaches were also predicted (e.g. ponatinib with rosuvastatin, ponatinib with decitabine). Since our ex vivo assay identified bortezomib (Velcade) as a clinical candidate and since we successfully negotiated off-label use of this agent, we selected Velcade for a therapeutic trial in patient PD001. After three doses of Velcade at 1.5 mg/m2 (Days 1,4 and 8), serial blood counts revealed a dramatic fall in total white count and circulating blasts (96% to 20%) (Figure 2). This is noteworthy since single agent Velcade is generally not capable of producing clinically meaningful responses for patients with refractory AML. Conclusions - Our study justifies continued development of this novel, iterative functional/genomics approach to personalized therapeutics in AML. Our model identifies candidate drugs that can be readily re-purposed for immediate clinical use, whilst at the same time providing insights into underlying mechanism of action, informing on rationally designed combination strategies and biomarker candidates. Figure 1. Ex vivo drug screening results from refractory patient_PD001 identifies the proteasome inhibitor bortezomib (Velcade) as one of the top selective and effective drugs. The higher the sDSS, the more effective and selective the drug is. Figure 1. Ex vivo drug screening results from refractory patient_PD001 identifies the proteasome inhibitor bortezomib (Velcade) as one of the top selective and effective drugs. The higher the sDSS, the more effective and selective the drug is. Figure 2. Clinical follow-up of AML patient-PD001 shows chemosensitivity to bortezomib (Velcade). Arrows arrows indicate dosing. Velcade decreased the percentage of leukemic blasts from 96% to 20%. Figure 2. Clinical follow-up of AML patient-PD001 shows chemosensitivity to bortezomib (Velcade). Arrows arrows indicate dosing. Velcade decreased the percentage of leukemic blasts from 96% to 20%. Disclosures Vega: Seatle Genetics: Honoraria; NIH: Research Funding.


2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii412-iii413
Author(s):  
Bradley Gampel ◽  
Luca Szalontay ◽  
Wenting Zhao ◽  
James Garvin ◽  
Chankrit Sethi ◽  
...  

Abstract Children with relapsed brain tumors are less responsive to treatment. These children often receive therapies without having any robust predictive method of potential benefit. Acute slice culturing(ASC) is a methodology permitting freshly operated tumor to undergo a culturing process preserving the tumor’s micro-environment. With the current study, we investigated the feasibility of obtaining therapeutically meaningful data in a timely manner (3–5 days), performing direct drug testing and single cell sequencing using ASC. Previously, we have combined ex vivo slices of intact, patient-derived Glioblastoma tissue with single-cell RNA-seq for small-scale drug screening and assessment of patient and cell type-specific drug responses. We generated slices from preclinical mouse glioma models and surgical specimens from adult Glioblastoma patients, as well as from children with relapsed Ependymomas, Medulloblastomas, and Gliomas. We demonstrated that these acute slices preserved both the tumor heterogeneity and tumor microenvironment observed in single-cell RNA-seq of cells directly isolated from tumor tissue. Testing drug responses, we then treated tissue slices from the Glioblastoma mouse models and different patients with multiple drugs and combinations. This technique allowed us to identify drug-induced transcriptional responses in specific subpopulations of tumor cells, patient-specific drug sensitivities, and drug effects conserved in both mouse and human tumors. Preliminary data suggests that we can apply this procedure within 5–7 days and provide real-time drug screening/single cell sequencing ASC results to Recurrent/ Progressive pediatric Low-Grade Gliomas, High Grade Gliomas, Ependymomas and Medulloblastomas.


2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi63-vi63
Author(s):  
Wenting Zhao ◽  
Eleonora Spinazzi ◽  
Athanassios Dovas ◽  
Pavan Upadhyayula ◽  
Tamara Marie ◽  
...  

Abstract Glioblastoma (GBM) is the most common and malignant type of primary brain tumor, and more effective treatment options are needed. Both inter- and intratumoral heterogeneity present major challenges to the application of targeted therapies in GBM. Therefore, precision medicine approaches to GBM would benefit significantly from the ability to predict drugs or drug combinations that target specific subpopulations of tumor cells. Model systems, such as adherent cell lines, neurospheres, patient-derived xenografts (PDXs), and patient-derived organoids, have been reported as platforms for drug screening and accessing drug responses. However, these models do not recapitulate the full heterogeneity of GBM tissue, lack key components of the tumor microenvironment or take weeks to months to establish, which limits the predictive power of drug response assays or delays clinical decision-making. To address these limitations, we are combining ex vivo slices of intact, patient-derived GBM tissue with single-cell RNA-seq (scRNA-seq) for small-scale drug screening and assessment of patient- and cell type-specific drug responses. We generated slices from both preclinical mouse glioma models and surgical specimens from GBM patients and showed that acute slices preserved both the tumor heterogeneity and tumor microenvironment observed in scRNA-seq of cells directly isolated from tumor tissue. To test drug responses, we treated tissue slices from GBM mouse models and five different patients with six drugs for 18hr. By performing scRNA-Seq and analyzing transcriptional profiles of treated and untreated control slices, we identified drug-induced transcriptional responses in specific subpopulations of tumor cells, patient-specific drug sensitivities, and drug effects conserved in both mouse and human tumors. The GBM tissue slices were generated immediately following surgical resection, and experiments were completed within 24 hours. With these features, our method is attractive for rapidly accessing cell type- and patient-specific drug responses and has potential for preclinical drug screening and guiding personalized treatment for GBM.


2020 ◽  
Vol 38 (4_suppl) ◽  
pp. 581-581
Author(s):  
Ricardo J. Antonia ◽  
Kan Toriguchi ◽  
Eveliina Karelehto ◽  
Dania Annuar ◽  
Luika Timmerman ◽  
...  

581 Background: Despite standard treatment with gemcitabine and cisplatin, median survival for unresectable Intrahepatic Cholangiocarcinoma (ICC) is < 1 year. Clearly, novel therapeutic strategies are urgently needed. The paucity of targetable mutations in ICC and the as yet unproven benefit of genetically targeted drugs led us to ask whether a reliable clinical benefit may be revealed by patient-specific therapeutic testing in novel models of ICC. Here we describe our ability to establish patient-derived three-dimensional organoid cultures (PDO) that enable individualized identification of active single agents or drug combinations in surrogate models of ICC. Methods: To model patient-specific drug responses, we used the freshly resected ICCs from small samples of single patient tumors to generate PDXs and PDOs, small spheroidal clusters of tumor cells grown in vitro. We have employed a high-throughput drug screening platform using AI-enhanced robotics (Yamaha Motor Corporation) to identify and distribute single, uniformly sized PDOs into 384-well ultra-low adherent plates. This is coupled with a TECAN D300e drug dispenser that rapidly delivers nanoliter volumes of a 34-drug panel, thereby facilitating rapid, reliable drug response analyses. Results: Our data show that PDOs retain characteristic genomic and histological features of the patients’ tumors. Drug responses were specific to each patient tumor, but PDOs from all patients responded to a greater or lesser degree to mTOR inhibition, suggesting that this pathway is important in ICC. The responses of PDO to the mTOR inhibitor Sapanisertib (INK128), was recapitulated in the same patient’s PDX. Further, INK128 was synergistic with gemcitabine in patient 970 PDOs as well as in vivo in PDX also from patient 970. Conclusions: As it is believed that PDX can predict patient responses to drugs, our results suggest that PDO may also predict patient drug responses. The establishment of PDO may allow economical patient-specific, high throughput drug screens that could ultimately inform clinical practice. [Table: see text]


2021 ◽  
Author(s):  
Sara JC Gosline ◽  
Cristina Tognon ◽  
Michael Nestor ◽  
Sunil Joshi ◽  
Rucha Modak ◽  
...  

Acute Myeloid Leukemia (AML) affects 20,000 patients in the US annually with a five-year survival rate of approximately 25%. One reason for the low survival rate is the high prevalence of clonal evolution that gives rise to heterogeneous sub-populations of leukemia. This genetic heterogeneity is difficult to treat using conventional therapies that are generally based on the detection of a single driving mutation. Thus, the use of molecular signatures, consisting of multiple functionally related transcripts or proteins, in making treatment decisions may overcome this hurdle and provide a more effective way to inform drug treatment protocols. Toward this end, the Beat AML research program prospectively collected genomic and transcriptomic data from over 1000 AML patients and carried out ex vivo drug sensitivity assays to identify signatures that could predict patient-specific drug responses. The Clinical Proteomic Tumor Analysis Consortium is in the process of extending this cohort to collect proteomic and phosphoproteomic measurements from a subset of these patient samples to evaluate the hypothesis that proteomic signatures can robustly predict drug response in AML patients. We sought to examine this hypothesis on a sub-cohort of 38 patient samples from Beat AML with proteomic and drug response data and evaluate our ability to identify proteomic signatures that predict drug response with high accuracy. For this initial analysis we built predictive models of patient drug responses across 26 drugs of interest using the proteomics and phosphproteomics data. We found that proteomics-derived signatures provide an accurate and robust signature of drug response in the AML ex vivo samples, as well as related cell lines, with better performance than those signatures derived from mutations or mRNA expression. Furthermore, we found that in specific drug-resistant cell lines, the proteins in our prognostic signatures represented dysregulated signaling pathways compared to parental cell lines, confirming the role of the proteins in the signatures in drug resistance. In conclusion, this pilot study demonstrates strong promise for proteomics-based patient stratification to predict drug sensitivity in AML.


2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Wenting Zhao ◽  
Athanassios Dovas ◽  
Eleonora Francesca Spinazzi ◽  
Hanna Mendes Levitin ◽  
Matei Alexandru Banu ◽  
...  

Abstract Background Preclinical studies require models that recapitulate the cellular diversity of human tumors and provide insight into the drug sensitivities of specific cellular populations. The ideal platform would enable rapid screening of cell type-specific drug sensitivities directly in patient tumor tissue and reveal strategies to overcome intratumoral heterogeneity. Methods We combine multiplexed drug perturbation in acute slice culture from freshly resected tumors with single-cell RNA sequencing (scRNA-seq) to profile transcriptome-wide drug responses in individual patients. We applied this approach to drug perturbations on slices derived from six glioblastoma (GBM) resections to identify conserved drug responses and to one additional GBM resection to identify patient-specific responses. Results We used scRNA-seq to demonstrate that acute slice cultures recapitulate the cellular and molecular features of the originating tumor tissue and the feasibility of drug screening from an individual tumor. Detailed investigation of etoposide, a topoisomerase poison, and the histone deacetylase (HDAC) inhibitor panobinostat in acute slice cultures revealed cell type-specific responses across multiple patients. Etoposide has a conserved impact on proliferating tumor cells, while panobinostat treatment affects both tumor and non-tumor populations, including unexpected effects on the immune microenvironment. Conclusions Acute slice cultures recapitulate the major cellular and molecular features of GBM at the single-cell level. In combination with scRNA-seq, this approach enables cell type-specific analysis of sensitivity to multiple drugs in individual tumors. We anticipate that this approach will facilitate pre-clinical studies that identify effective therapies for solid tumors.


2021 ◽  
Author(s):  
Jesse D Rogers ◽  
Brian A Aguado ◽  
Kelsey Watts ◽  
Kristi S Anseth ◽  
William J Richardson

Aortic valve stenosis (AVS) patients experience pathogenic valve leaflet stiffening due to excessive extracellular matrix (ECM) remodeling. Numerous microenvironmental cues influence pathogenic expression of ECM remodeling genes in tissue-resident valvular myofibroblasts, and the regulation of complex myofibroblast signaling networks depends on patient-specific extracellular factors. Here, we combined a manually curated myofibroblast signaling network with a data-driven transcription factor network to predict patient-specific myofibroblast gene expression signatures and drug responses. Using transcriptomic data from myofibroblasts cultured with AVS patient sera, we produced a large-scale, logic-gated differential equation model in which 11 biochemical and biomechanical signals are transduced via a network of 334 signaling and transcription reactions to accurately predict the expression of 27 fibrosis-related genes. Correlations were found between personalized model-predicted gene expression and AVS patient echocardiography data, suggesting links between fibrosis-related signaling and patient-specific AVS severity. Further, global network perturbation analyses revealed signaling molecules with the most influence over network-wide activity including endothelin 1 (ET1), interleukin 6 (IL6), and transforming growth factor β (TGFβ) along with downstream mediators c-Jun N-terminal kinase (JNK), signal transducer and activator of transcription (STAT), and reactive oxygen species (ROS). Lastly, we performed virtual drug screening to identify patient-specific drug responses, which were experimentally validated via fibrotic gene expression measurements in VICs cultured with AVS patient sera and treated with or without bosentan - a clinically approved ET1 receptor inhibitor. In sum, our work advances the ability of computational approaches to provide a mechanistic basis for clinical decisions including patient stratification and personalized drug screening.


Cells ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 3250
Author(s):  
Ponthip Pratumkaew ◽  
Surapol Issaragrisil ◽  
Sudjit Luanpitpong

The breakthrough in human induced pluripotent stem cells (hiPSCs) has revolutionized the field of biomedical and pharmaceutical research and opened up vast opportunities for drug discovery and regenerative medicine, especially when combined with gene-editing technology. Numerous healthy and patient-derived hiPSCs for human disease modeling have been established, enabling mechanistic studies of pathogenesis, platforms for preclinical drug screening, and the development of novel therapeutic targets/approaches. Additionally, hiPSCs hold great promise for cell-based therapy, serving as an attractive cell source for generating stem/progenitor cells or functional differentiated cells for degenerative diseases, due to their unlimited proliferative capacity, pluripotency, and ethical acceptability. In this review, we provide an overview of hiPSCs and their utility in the study of hematologic disorders through hematopoietic differentiation. We highlight recent hereditary and acquired genetic hematologic disease modeling with patient-specific iPSCs, and discuss their applications as instrumental drug screening tools. The clinical applications of hiPSCs in cell-based therapy, including the next-generation cancer immunotherapy, are provided. Lastly, we discuss the current challenges that need to be addressed to fulfill the validity of hiPSC-based disease modeling and future perspectives of hiPSCs in the field of hematology.


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