Patient Avatars Research Articles

Comparison of Glioblastoma Cell Culture Platforms Based on Transcriptional Similarity with Paired Tissue.

No standardized in vitro cell culture models for glioblastoma (GBM) have yet been established, excluding the traditional two-dimensional culture. GBM tumorspheres (TSs) have been highlighted as a good model platform for testing drug effects and characterizing specific features of GBM, but a detailed evaluation of their suitability and comparative performance is lacking. Here, we isolated GBM TSs and extracellular matrices (ECM) from tissues obtained from newly diagnosed IDH1 wild-type GBM patients and cultured GBM TSs on five different culture platforms: (1) ordinary TS culture liquid media (LM), (2) collagen-based three-dimensional (3D) matrix, (3) patient typical ECM-based 3D matrix, (4) patient tumor ECM-based 3D matrix, and (5) mouse brain. For evaluation, we obtained transcriptome data from all cultured GBM TSs using microarrays. The LM platform exhibited the most similar transcriptional program to paired tissues based on GBM genes, stemness- and invasiveness-related genes, transcription factor activity, and canonical signaling pathways. GBM TSs can be cultured via an easy-to-handle and cost- and time-efficient LM platform while preserving the transcriptional program of the originating tissues without supplementing the ECM or embedding it into the mouse brain. In addition to applications in basic cancer research, GBM TSs cultured in LM may also serve as patient avatars in drug screening and pre-clinical evaluation of targeted therapy and as standardized and clinically relevant models for precision medicine.

Abstract 228: Patient-derived gbm organoids reflect tumour heterogeneity and treatment sensitivity in patients

Abstract Glioblastoma (GBM) is the most common and incurable adult primary brain tumour. Treatment resistance and relapse is the primary cause of death in GBM. Tumour heterogeneity is one of the significant determinants of treatment failure. Patient-derived cancer organoids have been shown to maintain genetic and phenotypic tumour features and recapitulate intratumoral heterogeneity. Here, we report the development and molecular characterisation of patient-derived GBM organoid (PGO) models to study treatment response to existing and new treatment combinations. GBM biopsies were dissociated, suspended in Cultrex, and cultured in a brain stem cell medium. PGOs were characterised by whole-exome (WES) single-cell karyotype (scKaryoSeq) and RNA sequencing. The IC-50 and viability of PGO upon temozolomide (TMZ) and small molecule inhibitors were determined. Gene expression profiling was performed before and after TMZ treatment. Single-cell spatial heterogeneity was determined using Multiplex Immunostaining of PGO and matched patient samples. PGOs were established with a success rate of 80% (n=31). WES analysis between PGOs from the same patient at multiple time points (1-3 months) showed high maintenance of Single Nucleotide Variants (92.3%-97.7%). In PGOs key somatic oncogene variants and copy number variations were retained compared to the primary tumour (58%-90%). scKaryoseq (N=7) of different clinical GBM subtypes showed a high degree of genetic heterogeneity, with some PGO having up to 10 subclones. Single-cell phenotypic landscaping of patient biopsies showed mixed cellular states maintained after long-term culture in the matched PGO. PGOs showed a differential response to TMZ, corresponding with MGMT methylation and patient mutation status. RNAseq of PGO revealed TMZ-responsive genes, including upregulation of the prognostic JUN kinase pathway. Combination treatment of a JUN kinase inhibitor and TMZ showed a synergistic effect. In addition, PGOs were screened for their sensitivity to clinically approved brain-penetrable small molecule inhibitors targeting key GBM driver pathways. Combining small molecular inhibitors of MEK/PI-3/CDK4/EGFR kinase strongly reduced cell viability and activation of cell death pathways. phosphoKinome screens detected compensatory pathway activation upon kinase inhibition (MEK/CDK4 inhibitor) in several PGO. Data will show novel kinase interaction pathways that increase drug sensitivity in PGO. These data show that PGOs can be used as a stable phenotypic and genetic representative of the patient's tumour and have the potential to function as patient avatars for adaptive treatment selection and actionable drug target discovery. Citation Format: Marc A. Vooijs, Linde Hoosemans, Jolanda Piepers, Maikel Verduin, Maxime Vanmechelen, Mike Van Heumen, Frederik De Smet, Ann Hoeben. Patient-derived gbm organoids reflect tumour heterogeneity and treatment sensitivity in patients [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 228.

Abstract IA021: Digital patient avatars predict cancer evolution and personalised therapeutic strategies

Abstract Tumour heterogeneity manifested by genetic diversity and interchangeable cell states poses considerable challenges for the design of therapeutic strategies to combat cancer. While many strategies have been proposed to address this problem, using combination treatments and sequential delivery of therapies, the scope of combinations and sequencing order of therapies is enormous and is beyond the capacity of exhaustive testing through experimental models. We therefore propose using computational models to rapidly identify effective therapeutic interventions supported by convincing mechanistic explanations. Digital cancer avatars are computational programs representing oncogenic signalling networks and mapping molecular interactions to cell phenotype, which can be interrogated in silico. These computational programs specify how molecular interactions and perturbations produce cellular responses, such as cell proliferation, cell survival or cell death, and as such are well-suited to provide novel mechanistic insights into cellular behaviours as well as to identify therapeutic strategies for targeting them. In this talk, I will demonstrate the utility of bespoke computational models for triple-negative breast cancer, non-small cell lung cancer and melanoma to study how genomic changes drive tumour evolution and therapeutic response, and how these models are used to identify personalised combination treatments to overcome resistance. I will also present an in silico method applied to these models, to screen tens of millions combinations for effective sequential treatments by mapping the evolution of a tumour in response to a single-agent treatment and determining the optimal second-line treatment that will overcome resistance. Together these studies demonstrate the utility of digital avatars to improve our understanding of the mechanisms driving tumour progression and pave the way for personalised therapeutic strategies for improved cancer patient outcomes. Citation Format: Jasmin Fisher. Digital patient avatars predict cancer evolution and personalised therapeutic strategies [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA021.

Virtual reality in teaching using mentally ill patient avatars

Medical interaction and exploration techniques are the most important tools that medical students have to acquire in the subject of psychiatry and psychotherapy. The new digital technologies currently available, such as virtual reality (VR), as important supplements can contribute to asignificant improvement in the teaching of psychiatric-psychopathological learning content as well as, in particular, the technique of ascertaining the psychiatric history and diagnosis. Evaluation of the Bochum Avatar Exploration Project (AVEX) as part of the curricular course in medical studies at the Ruhr University Bochum for its possibilities to convey learning content and techniques of anamnesis and diagnosis in the subject of psychiatry and psychotherapy. In AVEX, atotal of 87medical students in the clinical study section have so far been able to enter into a dialogue with "mentally ill" avatars and gain experience with VR technology as alearning and teaching method in the subject of psychiatry and psychotherapy. Despite the limited possibilities for interaction with the digital avatars, it is possible to achieve asubstantial transfer of learning content in psychiatry; however, the students must be well supported by the lecturers. The AVEX project already shows promising possibilities for supplementing the teaching of medical students, even if the fit of questions and replies in dialogue with the virtual avatars still needs to be improved. As advances in the linguistic communication of emotions and the visual effects of the avatar representation can be predicted, the significance of this technology will continue to increase.

The problem with patient avatars and emotions

The problem with patient avatars and emotions

Development and evaluation of a software system for medical students to teach and practice anamnestic interviews with virtual patient avatars

Background and ObjectivesTaking a medical history is a core competence of the diagnostic process. At the beginning of their study medical students need to learn and practice the necessary techniques, initially focusing on good structuring and completeness. For this purpose, an interactive software system (ViPATalk) was developed in which the student can train to pose questions to virtual patient avatars in free conversation. At the end, the student receives feedback on the completeness of the questioning and an explanation of the essential items. The use of this software was compared to the traditional format of student role play in a randomized trial. MethodsThe central component of ViPATalk is a chatbot based on the AI language AIML, which generates an appropriate answer based on keywords in the student's question. To enable a realistic use, the student can enter the question via microphone (speech-to-text) and the answer generated by the chatbot is presented as a short video sequence, where the avatar is generated from a real image. Here, the transition between the sequences is seamless, resulting in a continuous movement of the avatar during the conversation. ResultsThe learning success by practicing with ViPATalk was tested in an anamnestic interview with actors as simulated patients. The completeness of the conversation was evaluated with regard to numerous aspects and also certain behaviors during the conversation. These results were compared with those after practicing using peer role play. ConclusionsIt was found that practicing with ViPATalk was mostly equivalent to the students' role play. In the subsequent survey of the students, the wish was expressed that the ViPATalk software should also be used as an online tool for self-study and that there should be more cases for practicing.

IMMU-08. EOSINOPHILS ARE IMPORTANT MODULATORS OF AN IMMUNE-RESPONSIVE TUMOR-MICROENVIRONMENT IN GLIOBLASTOMA

Abstract Eosinophils, bone marrow-derived granulocytes involved in allergic asthma and autoimmunity, have attracted increasing attention due to their assumed role in effective responses to immune checkpoint blockade in some extracranial tumors. However, the role of this rare type of immune cells in immunologically cold tumors such as glioblastoma (GBM) has not been studied so far. When quantifying immune infiltrates and levels of 30 immune-relevant cytokines in 60 matched pairs of human primary and recurrent GBM, strongest correlations (r= 0.71-0.93) were observed for the eosinophil-associated cytokines Eotaxin and Il-5 as well as for TNFa, IFNg and Il2 which are important cytokines for cytotoxic T cell responses. A combined score of these cytokines (Eo score) turned out to be an independent prognostic marker for improved overall survival of GBM patients. Furthermore, multicolor immunofluorescent staining revealed that Eo score high GBM are significantly higher infiltrated by effector T cells and show a significantly lower infiltration with anti-inflammatory M2-like tumor-associated macrophages / microglia cells (M2-TAM) in recurrent GBM. Flowcytometry analysis of GBM-derived single cell suspensions confirmed a positive correlation of higher eosinophil numbers with higher numbers of tumor-infiltrating T cells, while an inverse relation between eosinophils and monocytes could be demonstrated in the TCGA data set. Spatial transcriptomic data of human GBM confirmed that areas with a higher eosinophil infiltration showed higher numbers of T cells and pro-inflammatory M1-TAM, lower numbers of M2-TAM and a remarkable vessel normalization. Finally, in a newly developed patient-derived GBM organoid model we could corroborate the functional impact of eosinophils on the tumor-microenvironment. An increase of eosinophil numbers in these patient avatars resulted in a significantly decreased number of M2-TAM. Altogether, tumor-infiltrating eosinophils seem to be a novel type of immune-modulator in GBM and may enhance immune responses by shaping the tumor niche from an immunosuppressive to an immunepermissive microenvironment.

Changes in satisfaction and anxiety about radiotherapy for pediatric cancer by two-step audio-visual instruction.

Although radiotherapy is an essential component of pediatric cancer treatment, inadequate radiotherapy information for childhood cancer and unusual treatment situations can negatively affect parental perceptions and emotions. This study aims to investigate the effect of two-step audio-visual instruction system effects introduced by our institution on parent satisfaction and anxiety when initiating radiotherapy. The two-step audio-visual instruction system comprised instructive animation using patient avatars and a live video system. The live video system has a 55-inch-wide monitor, and a no-latency sound module. Parents in the radiotherapy division can view the patient in the treatment room through the live video system. This prospective study compared satisfaction and anxiety about radiotherapy introduction before and after two-step audio-visual instruction. We enrolled 20 parents whose child underwent radiotherapy, and they completed a set of questionnaires-Client Satisfaction Questionnaire, State-Trait Anxiety Inventory, and original questionnaires about radiotherapy. Satisfaction scores improved significantly after two-step audio visual instruction (25.5±3.4) compared with those before the instruction (27.7±3.1) (p = <0.01). Anxiety scores also decreased significantly after the instruction (50±9) compared with those before the instruction (54±11) (p=0.004). However, anxiety-related personality trait scores did not change drastically before and after viewing (48±8.5 vs. 49±7.5) (p=0.419). This single-arm prospective study indicates that two-step audio-visual instruction for radiotherapy is effective in improving parents' anxiety about radiotherapy introductions. However, large-scale and comparative studies are warranted to generalize the benefit of two-step audio visual instruction.

The challenge of making the right choice: patient avatars in the era of cancer immunotherapies.

Immunotherapies are a key therapeutic strategy to fight cancer. Diverse approaches are used to activate tumor-directed immunity and to overcome tumor immune escape. The dynamic interplay between tumor cells and their tumor(immune)microenvironment (T(I)ME) poses a major challenge to create appropriate model systems. However, those model systems are needed to gain novel insights into tumor (immune) biology and a prerequisite to accurately develop and test immunotherapeutic approaches which can be successfully translated into clinical application. Several model systems have been established and advanced into so-called patient avatars to mimic the patient´s tumor biology. All models have their advantages but also disadvantages underscoring the necessity to pay attention in defining the rationale and requirements for which the patient avatar will be used. Here, we briefly outline the current state of tumor model systems used for tumor (immune)biological analysis as well as evaluation of immunotherapeutic agents. Finally, we provide a recommendation for further development to make patient avatars a complementary tool for testing and predicting immunotherapeutic strategies for personalization of tumor therapies.

Refractory colorectal cancer patient derived MicroOrganoSpheres (MOS) to enable correlation of targeted therapy combination response with clinical outcomes.

e15574 Background: Metastatic colorectal cancer (CRC) patients who have become resistant to standard-of-care (SOC) treatments are often put on targeted therapies, including experimental drugs still in clinical trials. However, patients with targeted mutations still often do not respond to the targeted therapies alone, hence it remains a critically unmet need to explore potential combinatorial regimens that will enhance the efficacy. Methods: We performed a high-throughput screen using MicroOrganoSpheres (MOS) derived from metastatic refractory patients to correlate with clinical outcomes and explore alternative combinations that might benefit the patients. Biopsies from metastatic CRC patients who became resistant to SOC and were about to receive targeted therapies in clinical trials were molecularly profiled and implanted into immunodeficient mice to generate patient-derived xenografts (PDX). Results: MOS were derived and established from PDX using droplet-based microfluidics for high-throughput 3D screening. These MOS-based refractory patient avatars contain either targetable mutations including KRAS G12C and BRAF 600E or no such mutations. Response of the MOS to dose-titrated single and combination drug treatments including the available targeted therapies were measured by a fully automated robotic dispensing and imaging pipeline and quantified by AI-based live imaging analytical algorithm to generate robust drug response curves, which were used to derive IC50 and EC50. We tested both FDA-approved and experimental targeted therapies as single agent or in combination in 5-dose titrations. Longitudinal tracking of each MOS with Live/dead fluorescence dye signals was obtained for 5 days. MOS drug response curves and IC50s show correlation with clinical outcomes. This comprehensive dataset enabled us to assess the potential benefit of different combinations, help deconvolute the efficacy and synergy of individual drugs, and provide insight into patients who fail to response to targeted therapies despite possessing the targeted mutations. As the MOS diagnostic assay can be completed from a patient biopsy within 10 days and is currently in a registered, multi-site clinical trial (ClinicalTrials.gov # NCT05189171), this study provides proof-of-principle for a potential clinical MOS-based assay to guide refractory patients to the optimal combination regimen containing targeted therapy. Conclusions: Refractory patients may benefit from a MOS-based high-throughput screen assay to select the optimal combination regimen containing targeted therapy.

Patient-derived MicroOrganoSpheres (MOS) and precision clinical decision-making for patients with multiple myeloma.

8047 Background: There are many multiple myeloma (MM) treatments and nearly all patients undergo continual cycles of treatment, response, and resistance. Selecting an effective therapeutic strategy is of critical importance; but there is currently a lack of patient-derived MM models that can enable functional precision medicine to help real-time clinical decision-making to guide individual patient treatment. Methods: We show a method to rapidly establish MM patient-derived MicroOrganoSheres (MOS), which are microscale, droplet-sized patient avatars that sustain the native tumor niche, including both stromal and immune compartments. We generated first-of-its-kind data showing that MM MOS predicted patient treatment outcomes and have the potential to guide clinical treatment decisions. We further developed high-throughput drug screen to demonstrate MM MOS response to FDA-approved single and combination therapies and developed MOS assays to predict patient responses to immunotherapies including bispecific and phagocytosis-inducing antibodies. Results: MM MOS established from patient bone marrow (BM) biopsies preserved CD138/CD38 tumor cells, stromal (e.g., osteoblast) cells, and all major immune cell populations (T, NK, B, macrophage, dendritic, and myeloid-derived suppressor cells) for 11 days in culture. We performed single and combo drug testing on MOS derived from 7 MM patients within 10 days of biopsy collection. Patients went on receiving treatments and their responses were assessed using International Myeloma Working Group response criteria. The MOS assay predicted responses of both treatment-naïve and refractory patient to standard-of-care regimens, including combinations of proteasome inhibitors (bortezomib, carfilzomib), immunomodulatory agents (lenalidomide) and DCEP. Moreover, the BM biopsy-derived MOS enabled high-throughput drug testing of single agents and combinations in 9-dose titrations, providing clinicians the ability to evaluate alternative treatment options. Furthermore, because MOS retain the immune compartments of the original tumor niche, we were able to evaluate patients’ response to bispecific T cell engagers and developed a phagocytosis assay to measure anti-tumor phagocytosis activity, which showed efficacy in both single-agent and combo settings. Multi-modal profiling and an AI image analysis pipeline provided robust measurements that confirmed the unique phenotypic profile of each patient sample, highlighting the critical unmet need to guide each patient to the optimal treatment. Conclusions: Based on this groundbreaking feasibility study, a subsequent clinical trial of 40 patients is current under IRB review to further validate the clinical power of MM MOS to predict patient outcome and to demonstrate utility as a viable functional precision medicine approach to inform treatment decisions in the clinic.

Improving capacity to identify, assess, and manage adolescents engaging in non-suicidal self-injury using patient avatars

Purpose We developed and evaluated a training comprising a didactic and virtual practice session with human-guided patient avatars to increase pediatric residents’ competence to identify and assess non-suicidal self-injury (NSSI) and suicide risk. Methods Thirty pediatric residents at three children’s hospitals in Florida participated in the training and completed pre-, one-month post-, and three-months post-training surveys. One-way repeated measures ANOVA with post-hoc comparisons determined changes in confidence, comfort, behavioral intentions, attitudes, knowledge, and behavior over time. Qualitative responses provided feedback on the training, especially the novel practice session with adolescent patient avatars. Results Three-months post-training residents expressed significantly greater confidence in talking to adolescents who self-injure, applying the SOARS method to assess self-injury, and assessing functions/reasons for self-injury; reported feeling significantly more comfortable asking about self-injury, well-equipped to handle the emotional aspects of self-injury, and comfortable treating adolescents who self-injure; reported greater behavioral intentions to talk to adolescents about self-injury, assess an adolescent’s stage of change for stopping self-injury, and provide brief interventions for adolescents who self-injure; and used SOARS to evaluate current NSSI with a greater proportion of adolescent patients. Qualitative feedback expressed positive perceptions, especially related to the virtual-reality role-play session. Conclusions Incorporating an interactive, human-guided virtual experience using role-playing and feedback with patient avatars represents a viable option comparable to using typical standardized patients to expand the scalability of NSSI trainings for pediatric residents, especially when they occur virtually.

Abstract 3412: Patient-derived MicroOrganoSpheres (MOS) enable precision clinical decision-making for multiple myeloma patients

Abstract There are many equipoised multiple myeloma (MM) treatments and nearly all relapse patients undergo cycles of treatment, response, and relapse management. Selecting the right agents and right drug combination is thus of critical importance and an area of unmet need. We currently lack patient-derived MM models that can enable functional precision medicine to help real-time clinical decision-making to guide individual patient treatment. We have created a method to grow MM patient avatars in MicroOrganoSheres (MOS), microscale droplet ECM that sustain the original tumor microenvironment (TME) including both stromal and immune compartments. MOS enable reliable testing of available drug combinations and experimental drugs within 10 days of bone marrow (BM) biopsy, making it feasible to guide treatment decisions in the clinic. In the current study, BMB-derived MM MOS were generated via droplet microfluidics and cultured in vitro, followed by live MOS staining and flow cytometry. Drug screen was performed on MOS with FDA-approved single agents and combinations. Responses of tumorspheres within MOS to drug treatments were quantified by AI-based live imaging algorithms to generate robust drug response curves and derive IC50 and EC50. We successfully established from all 6 MM BM biopsies, MOS conserved CD138/CD38 tumor cell, stromal (e.g., osteoblast) cells, and all major immune cell populations, including T, NK, B, macrophage, dendritic, and myeloid-derived suppressor cells till at least 11 days after the drug assays were completed. The vast number of MOS generated from a single BM biopsy enabled high-throughput drug screening within 10 days. We tested standard-of-care drugs and their combinations applicable to the patient in 9-dose titrations. Live/dead dye fluorescence signal was obtained after 5 days drug dosing and analyzed using Xilis AI analysis pipeline. We generated MOS drug response curve and IC50s from each biopsy. Drug responses from the first 6 MM patient MOS correlates well with their clinical outcome. Furthermore, this MOS platform enabled us to evaluate experimental therapies currently in Phase I-III clinical trials, which revealed responsive patients and insights into optimal combinations that will further improve efficacy. Based on this groundbreaking study, a clinical trial including 40 patients is starting in a month to further validate the predictability of the MM MOS assay for therapeutic decision-making in the clinic. Citation Format: Rui Xi, Xiaobei Wang, Robert Moseley, Renuka Raman, Ray Zhang, Shaima Jaibbar, Shaun Steele, Shengi Ding, Yubing Kang, Xiling Shen. Patient-derived MicroOrganoSpheres (MOS) enable precision clinical decision-making for multiple myeloma patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3412.

Abstract 183: Evaluating targeted therapy combination for refractory colorectal cancer using MicroOrganoSpheres (MOS)

Abstract Metastatic colorectal cancer (CRC) patients who have become resistant to standard-of-care (SOC) treatments are often put on targeted therapies, including experimental drugs still in clinical trials. However, patients with targeted mutations still often do not respond to the targeted therapies alone, hence it remains a critically unmet need to explore potential combinatorial regimens that will enhance the efficacy. We performed a high-throughput screen using MicroOrganoSpheres (MOS) derived from metastatic refractory patients to correlate with clinical outcomes and explore alternative combinations that might benefit the patients. Biopsies from metastatic CRC patients who became resistant to SOC and were about to receive targeted therapies in clinical trials were molecularly profiled and implanted into immunodeficient mice to generate patient-derived xenografts (PDX). MOS were derived and established from PDX using droplet-based microfluidics for high-throughput 3D screening. These MOS-based refractory patient avatars contain either targetable mutations including KRAS G12C and BRAF 600E or no such mutations. Response of the MOS to dose-titrated single and combination drug treatments including the available targeted therapies were measured by a fully automated robotic dispensing and imaging pipeline and quantified by AI-based live imaging analytical algorithm to generate robust drug response curves, which were used to derive IC50 and EC50. We tested both FDA-approved and experimental targeted therapies as single agent or in combination in 5-dose titrations. Longitudinal tracking of each MOS with Live/dead fluorescence dye signals was obtained for 5 days. MOS drug response curves and IC50s show correlation with clinical outcomes. Furthermore, this comprehensive dataset enabled us to assess the potential benefit of different combinations, help deconvolute the efficacy and synergy of individual drugs, and provide insight into patients who fail to response to targeted therapies despite possessing the targeted mutations. As the MOS diagnostic assay can be completed from a patient biopsy within 10 days and is currently in a registered, multi-site clinical trial (ClinicalTrials.gov # NCT05189171), this study provides proof-of-principle for a potential clinical MOS-based assay to guide refractory patients to the optimal combination regimen containing targeted therapy. Citation Format: Shengli Ding, Preeti Kanikarla Marie, Ray Zhang, Alan Bohn, Robert Moseley Moseley, Nicholas Baro, Dan Brown, Kelly Pittman, Marcin Paduch, David Hsu, Scott Kopetz, Xiling Shen. Evaluating targeted therapy combination for refractory colorectal cancer using MicroOrganoSpheres (MOS) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 183.

Identifying targeted therapy combination for refractory colorectal cancer using micro-organospheres.

27 Background: Metastatic colorectal cancer (CRC) patients who have become resistant to standard-of-care (SOC) treatments are often put on targeted therapies. However, patients with targeted mutations still often do not respond to the targeted therapies alone, hence it remains a critically unmet need to explore potential combinatorial regimens that will enhance the efficacy. Using micro-organospheres (MOS) derived from metastatic refractory patients who received targeted therapies, we performed a high-throughput combo screen and compared the response of these patient tumor avatars with their clinical responses. Methods: Biopsies from metastatic CRC patients who became resistant to SOC and were about to receive targeted therapies in clinical trials were molecularly profiled and implanted into immunodeficient mice to generate patient-derived xenografts (PDX). MOS were derived and established from PDX using droplet-based microfluidics for high-throughput 3D screening. Response of the MOS patient avatars to dose-titrated single and combination drug treatments including the available targeted therapies were measured by a fully automated robotic dispensing and imaging pipeline and quantified by AI-based live imaging analytical algorithm to generate drug response curves with IC50 and EC50. Results: MOS were successfully established in all PDX derived from refractory patients with targetable mutations including KRAS G12C and BRAF 600E as well as patients without targetable mutations. We tested both FDA-approved and experimental targeted therapies as single agent or in combination in 5-dose titrations. Longitudinal tracking of each MOS with Live/dead fluorescence dye signals was obtained for 5 days. MOS drug response curves and IC50s show correlation with clinical outcomes. Furthermore, this comprehensive dataset enabled us to assess the potential benefit of different combinations, help deconvolute the efficacy and synergy of individual drugs, and provide insight into patients who fail to response to targeted therapies despite possessing the targeted mutations. As the MOSdiagnostic assay can be completed from a patient biopsy within 10 days and is currently in a registered, multi-site clinical trial (ClinicalTrials.gov # NCT05189171), this study provides proof-of-principle for a potential clinical MOS-based assay to guide refractory patients to the optimal combination regimen. Conclusions: Refractory patients may benefit from a MOS-based high-throughput screen assay to select the optimal combination regimen containing targeted therapy.

MODL-04. ESTABLISHMENT OF A RELIABLE GLIOBLASTOMA TUMOR-ORGANOID PLATFORM ENABLES AUTOMATED HIGH-THROUGHPUT DRUG SCREENING ADVANCING PERSONALIZED MEDICINE

Abstract Patient-derived tumor organoids (TOs) generated from tumor tissues within a few days are promising new models since under optimal conditions they preserve genotype, phenotype, the tumor microenvironment and the cellular heterogeneity of the parental tumor. This exciting new technology could provide representative avatars of the patient tumor in large numbers and thus can be exploited for drug discovery and drug screening purposes more efficiently than conventional cell lines or xenografted mouse models. We established standardized TOs from fresh glioblastoma (GBM) tissue after enzymatic dissociation into single cell suspensions and seeding cells into anti-adhesive 384-well plates. Over 1000 standardized TOs were generated per patient with a success rate of over 90%. Morphologically, TOs formed after two days. Size was stable over 10 days, with a slow outgrowth in some cases. A steady increase of the ATP signal over time indicated proliferative activity in TOs. Immunofluorescent stainings for tumor cells (GFAP), immune cells (macrophages and T-cells), and extracellular matrix (Tensascin C) confirmed a strong resemblance of TOs to their corresponding parental tumor, which was further substantiated by RNA-seq and DNA-methylation. Next, automated robot-based high-throughput drug screening (aHTS) on TOs was performed using a drug library of 166 FDA-approved antineoplastic drugs. Cell viability was assessed by CellTiter-Glo3D. In total, aHTS on TOs from 11 GBM patients including two recurrent GBMs showed a strong heterogeneity of drug responses. The top ten best-performing drugs consisted of 35 compounds targeting 14 different modes of action. Proteasome and HDAC-inhibitors demonstrated the highest efficacy. Respective targets were validated by knockdown experiments in GBM cells. Altogether, our data corroborate the future use of standardized GBM TOs as patient avatars for personalized drug testing by utilizing an automated high-throughput drug screening platform to better account for inter-patient-individual drug responses.

BRAIN Surgical Tissue for Advanced Tumour models in Precision medicine: Developing the BRAIN-STAT pathway

AimsThere are approximately four thousand neuro-oncology procedures in the UK per annum. Many of these result in tissue and biofluid specimens that are surplus to diagnostic requirement and can be collected as standard of clinical care. However, developing technologies and treatments for precision medicine require access to a range of individualised biospecimens paired with deep clinical phenotyping data. Here, we present Brain Surgical Tissue for Advanced Tumour Models (BRAINSTAT) programme, an infrastructure that has been established between Queen Elizabeth Hospital, Birmingham and the University of Birmingham, to collect, structure and store these resources and also maximise their value for research over the long-term. Using this approach our aim is to provide high-quality, annotated resources to help develop novel treatments for patients with brain tumours.MethodBRAINSTAT infrastructure allows:Prospective consentBiospecimens, including tumour tissue (brain and other primary in the case of metastasis), cyst fluid, dura, skin, CSF, blood (matched “germ-line” and for circulating cell free tumour DNA analysis), urine and saliva can be collected. Consent for long term follow-up, is either via clinic or NHS digital. More limited consent for non-oncological neurosurgical cohorts (e.g. epilepsy or vascular) and healthy volunteers allow healthy access-tissue and biofluids to be collected.B. Rapid transfer of fresh surgical tissue samples:Strong collaborative links and close physical proximity between operating theatre and laboratory allows rapid transfer of biospecimens minimising transit time.C. Standardised annotation across disciplinesThe RedCAP database system allows granular control over data-access, and each specialist research team is provided access only to the sub-sections relevant to them. All users must have Good Clinical Practice certification and GDPR training, prior to access of the BRAINSTAT database.ResultsBetween 25/11/2019-16/03/2020 and 27/07/2020-16/11/2020, 65 patients were consented for BRAINSTAT at the weekly neurosurgical oncology clinic. (Recruitment gaps due to the SARS-COVID 19 pandemic). Pathological diagnosis of surplus tissue collected included: 37 high grade glioma, 3 low grade glioma and 16 brain metastasis including: (6 lung, 6 breast, 2 colorectal, 1 oesophageal, 1 endometrial). Meningioma (5 WHO I; 1 WHO III) 1 patient undergoing anterior temporal lobectomy for hippocampal sclerosis contributed access tissue from the lateral neocortex. 1 patient had a non- neoplastic, non-diagnostic sample. All patients had matched “germ-line” blood samples.Median time from resection to arrival in the laboratory was 10 minutes (range 4-31). Standardised operating protocols to optimise this have been developed.Glioblastoma and breast-brain metastasis tumourspheres and cerebral organoids are currently being validated.ConclusionDespite the challenges of the pandemic we have established a viable tissue pipeline from neurosurgical operating theatre to our university laboratories. We are developing clinically annotated human brain tumour cell lines, stem cells and 3D organoid models, principally for commonly encountered brain tumours such as glioma and metastasis.The research sets the foundation for a multitude of downstream applications including:- Building more complex organoid cultures e.g. by including other cell types such as healthy brain cells and endothelial cells allowing future experiments to more accurately model tumour growth.- Developing high-throughput, patient-specific drug screens of novel drugs and drug combinations using these 3D tumour models aiming to more effectively treat tumour proliferation and spread. These patient avatars will help inform and test more “stratified” personal medical treatments and will provide opportunities to allow earlier intervention with the aim of improving survival, coupled with a better quality of life.

P70.04 Results From a Patient Avatar Program Utilizing Murine Xenografts and Organoids After Neoadjuvant Therapy for Operable NSCLC

Patient-derived xenografts (PDX) and organoids (PDO) are well described methods of propagating patient tumors. While propagation of such models are well established in treatment naïve patients after surgical resection, little is known of the prognostic utility of such methods in the context of patients who have undergone neoadjuvant therapy with conventional therapy (chemotherapy +/- radiation), immune checkpoint blockade (ICB) or tyrosine kinase inhibitor (TKI) for patients with operable non-small cell lung cancer (NSCLC). This study aims to evaluate PDX and PDO propagation rates after surgical resection from patients treated with a variety of conventional and emerging ICB neoadjuvant treatment regimens, as well as correlation with extent of pathological response. All trials of PDX and PDO implantation performed at the McGill University, Goodman Cancer Research Centre since 2017 from samples of lung cancer patients treated at the Montreal General Hospital were reviewed. After intraoperative specimen evaluation by a clinical pathologist, tumor pieces of 5 mm3 were taken for live banking PDX and PDO procedures. A retrospective chart review was then performed to obtain patient demographic and treatment data. A total of 80 PDX implantation and 28 PDO culture trials were performed, with respective take rates of 25% and 82%. Overall, 35/80 PDX trials (20 chemotherapy only, 2 chemotherapy +/- ICB, 2 chemoradiation, 10 ICB, and 1 TKI) and 23/28 PDO trials (11 chemotherapy only, 3 chemotherapy +/- ICB, 1 chemoradiation, 7 ICB, and 1 TKI) were from patients who received neoadjuvant treatment. In these patients, our take rates were 17% for PDX and 78% for PDO. 5 neoadjuvant-treated patients had a major pathological response (MPR) and 2 patients, a pathological complete response (pCR). Of those with MPR, 1/5 sample was successfully propagated in PDXs, and another 1/5 sample failed to propagate in PDXs, but grew organoids. Interestingly, 0/10 patients who received neoadjuvant ICB grew in PDXs versus 3/10 where PDOs were successfully propagated. PDX and PDO models offer tangible opportunities to create living patient avatars. Our study suggests that PDX and PDO propagation is possible after a variety of neoadjuvant treatment regimens, though we were unable to propagate PDX from ICB-treated patients. Furthermore, MPR did not preclude subsequent tumor propagation in PDX or PDO. The clinical relevance of these findings and biology underlying our findings remains to be further explored.

Smart Decentralization of Personal Health Records with Physician Apps and Helper Agents on Blockchain: Platform Design and Implementation Study.

BackgroundThe Health Avatar Platform provides a mobile health environment with interconnected patient Avatars, physician apps, and intelligent agents (termed IoA3) for data privacy and participatory medicine; however, its fully decentralized architecture has come at the expense of decentralized data management and data provenance.ObjectiveThe introduction of blockchain and smart contract technologies to the legacy Health Avatar Platform with a clinical metadata registry remarkably strengthens decentralized health data integrity and immutable transaction traceability at the corresponding data-element level in a privacy-preserving fashion. A crypto-economy ecosystem was built to facilitate secure and traceable exchanges of sensitive health data.MethodsThe Health Avatar Platform decentralizes patient data in appropriate locations (ie, on patients’ smartphones and on physicians’ smart devices). We implemented an Ethereum-based hash chain for all transactions and smart contract–based processes to guarantee decentralized data integrity and to generate block data containing transaction metadata on-chain. Parameters of all types of data communications were enumerated and incorporated into 3 smart contracts, in this case, a health data transaction manager, a transaction status manager, and an application programming interface transaction manager. The actual decentralized health data are managed in an off-chain manner on appropriate smart devices and authenticated by hashed metadata on-chain.ResultsMetadata of each data transaction are captured in a Health Avatar Platform blockchain node by the smart contracts. We provide workflow diagrams each of the 3 use cases of data push (from a physician app or an intelligent agents to a patient Avatar), data pull (request to a patient Avatar by other entities), and data backup transactions. Each transaction can be finely managed at the corresponding data-element level rather than at the resource or document levels. Hash-chained metadata support data element–level verification of data integrity in subsequent transactions. Smart contracts can incentivize transactions for data sharing and intelligent digital health care services.ConclusionsHealth Avatar Platform and interconnected patient Avatars, physician apps, and intelligent agents provide a decentralized blockchain ecosystem for health data that enables trusted and finely tuned data sharing and facilitates health value-creating transactions with smart contracts.

Rapid Curricular Innovations During COVID-19 Clinical Suspension: Maintaining Student Engagement with Simulation Experiences.

Health care education programs were faced with the need to quickly adapt to a new reality during the coronavirus disease 2019 pandemic. Students were temporarily suspended from campus and clinical sites, requiring prompt changes in structure to their didactic and clinical learning. This article describes the rapid adjustments that one midwifery and women's health nurse practitioner education program created using both synchronous and asynchronous simulation experiences to promote student learning and ongoing engagement. Flexibility and reflexivity were needed by faculty and students alike in the face of the multiple changes wrought by the pandemic. Curricular changes were made simultaneously in many courses. Objective structured clinical examinations simulate telehealth experiences that assess knowledge, clinical reasoning, and professional behaviors via a scripted scenario and an actor patient. On-call simulations mimic telephone triage and provide students the opportunity to build listening, assessment, and management skills for prenatal and intrapartum scenarios. Students are provided equipment and virtual instruction in an intrauterine device insertion session, which promotes skill acquisition and self-confidence. Trigger films are used to visualize real-life or scripted clinical encounters, leading to discussion and decision-making, particularly in the affective domain. Bilateral learning tools, similar to case studies, provide students an opportunity to demonstrate their knowledge and critical thinking with a mechanism for faculty feedback. Web-based virtual clinical encounter learning tools using patient avatars prompt additional student learning. Suturing skills introduced in live remote group sessions are augmented with video-guided individual practice. This article describes each of these adapted and innovative simulation methods and shares lessons learned during their development and implementation.