Patient Avatars Research Articles

Validation of a multicellular tumor microenvironment system for modeling patient tumor biology and drug response

Lung cancer rates are rising globally and non-small cell lung cancer (NSCLC) has a five year survival rate of only 24%. Unfortunately, the development of drugs to treat cancer is severely hampered by the inefficiency of translating pre-clinical studies into clinical benefit. Thus, we sought to apply a tumor microenvironment system (TMES) to NSCLC. Using microvascular endothelial cells, lung cancer derived fibroblasts, and NSCLC tumor cells in the presence of in vivo tumor-derived hemodynamic flow and transport, we demonstrate that the TMES generates an in-vivo like biological state and predicts drug response to EGFR inhibitors. Transcriptomic and proteomic profiling indicate that the TMES recapitulates the in vivo and patient molecular biological state providing a mechanistic rationale for the predictive nature of the TMES. This work further validates the TMES for modeling patient tumor biology and drug response indicating utility of the TMES as a predictive tool for drug discovery and development and potential for use as a system for patient avatars.

TMOD-34. PATIENT-DERIVED XENOGRAFT AND CELL LINE MODELS FACILITATE NOVEL TREATMENT DISCOVERY IN CENTRAL NERVOUS SYSTEM LYMPHOMAS

Abstract Lymphomas of the central nervous system (CNSL) are rare tumors with few treatment options; however, recent genomic studies have uncovered several druggable targets. To facilitate novel treatment discovery, we sought to establish patient-derived xenograft (PDX) models and cell lines from patients with newly diagnosed or recurrent CNSL. PDX models were attempted from fresh tumor samples from 18 consented patients for whom rich clinical annotation was available. Orthotopic intracranial injections were performed via stereotactic injection. Cell line generation was attempted from both primary tumors (PDCL) and PDX samples (PDXCL). Characterization included histopathology, targeted exome sequencing, low-pass whole-genome sequencing for copy number evaluation, and expression profiling of matched patient tumors and PDXs. Drug response testing was performed using CellTiterGlo. From 18 samples attempted, 8 PDX models were successfully generated: 2 primary CNS diffuse large B-cell lymphoma (DLBCL), 5 secondary CNS DLBCL, and 1 secondary cutaneous T-cell lymphoma (CTCL). Mean time to moribund was 66 days. All 8 PDXs grew successfully as orthotopic models, and 4 also grew in subrenal capsule. Additionally, 6 PDCL and 2 PDXCL were established (> P3). Models faithfully represented primaries, showing nearly identical histopathology, immunoprofiles, and genomic signatures. To support expanded and rapid preclinical use of these models in drug testing we documented that PDX could be explanted to create short-term cell preparations or long-term cell lines with a 100% and 40% success rate, respectively. Proof of principle testing showed that explanted DLBCL PDX cells and cell lines showed sensitivity to copanlisib and venetoclax, which were not efficacious in the CTCL PDX. These findings showcase a diverse collection of CNSL models demonstrating high fidelity to primary tumors at the genomic and phenotypic levels, emphasizing their utility for preclinical studies and as patient avatars to rapidly determine sensitivities to existing and novel regimens prior to initiation of therapy.

A microfluidic platform for cultivating ovarian cancer spheroids and testing their responses to chemotherapies

There is increasing interest in utilizing in vitro cultures as patient avatars to develop personalized treatment for cancer. Typical cultures utilize Matrigel-coated plates and media to promote the proliferation of cancer cells as spheroids or tumor explants. However, standard culture conditions operate in large volumes and require a high concentration of cancer cells to initiate this process. Other limitations include variability in the ability to successfully establish a stable line and inconsistency in the dimensions of these microcancers for in vivo drug response measurements. This paper explored the utility of microfluidics in the cultivation of cancer cell spheroids. Six patient-derived xenograft (PDX) tumors of high-grade serous ovarian cancer were used as the source material to demonstrate that viability and epithelial marker expression in the microfluidic cultures was superior to that of Matrigel or large volume 3D cultures. To further demonstrate the potential for miniaturization and multiplexing, we fabricated multichamber microfluidic devices with integrated microvalves to enable serial seeding of several chambers followed by parallel testing of several drug concentrations. These valve-enabled microfluidic devices permitted the formation of spheroids and testing of seven drug concentrations with as few as 100,000 cancer cells per device. Overall, we demonstrate the feasibility of maintaining difficul-to-culture primary cancer cells and testing drugs in a microfluidic device. This microfluidic platform may be ideal for drug testing and personalized therapy when tumor material is limited, such as following the acquisition of biopsy specimens obtained by fine-needle aspiration.

How to Teach Intramuscular Injection Through Virtual Learning Environment in Covid-19 Pandemic Time for Nursing Students

During the pandemic COVID-19 spread and the temporary lockdown of universities, there has been a globalshift toward online learning. Some universities were not prepared for such circumstances, and they beganattempting to meet this unprecedented task for not missing the academic year. Recently, there has beena project that is currently working on the same issue regarding teaching nursing students how to deliverintramuscular (IM) injection using online in a virtual learning environment. The objective of this studywas to create a simulation in an online course using a three-dimensional (3D) learning management system(LMS) in a virtual learning environment (VLE). That can replace IM injection traditional teaching method.This LMS intended to supplement the existing lab practice to nursing undergraduate students by creating asimulated online clinic with a nurse and patient avatars. Theoretical content in the form of reading materialand related videos was also provided for students’ cognitive base before they start the 3D simulation training.This new course was founded on the Galvis panqueva method that resulted in a product called Online-3DIMI-VLE. Various validation processes undertook for multiple development processes involving nursingcontent specialists and computer multimedia. The pilot results showed that this LMS could replace thetraditional way of teaching and support online learning during the normal education environment as well asin this COVID-19 pandemic time.

Patient-derived organoids and orthotopic xenografts of primary and recurrent gliomas represent relevant patient avatars for precision oncology

Patient-based cancer models are essential tools for studying tumor biology and for the assessment of drug responses in a translational context. We report the establishment a large cohort of unique organoids and patient-derived orthotopic xenografts (PDOX) of various glioma subtypes, including gliomas with mutations in IDH1, and paired longitudinal PDOX from primary and recurrent tumors of the same patient. We show that glioma PDOXs enable long-term propagation of patient tumors and represent clinically relevant patient avatars that retain histopathological, genetic, epigenetic, and transcriptomic features of parental tumors. We find no evidence of mouse-specific clonal evolution in glioma PDOXs. Our cohort captures individual molecular genotypes for precision medicine including mutations in IDH1, ATRX, TP53, MDM2/4, amplification of EGFR, PDGFRA, MET, CDK4/6, MDM2/4, and deletion of CDKN2A/B, PTCH, and PTEN. Matched longitudinal PDOX recapitulate the limited genetic evolution of gliomas observed in patients following treatment. At the histological level, we observe increased vascularization in the rat host as compared to mice. PDOX-derived standardized glioma organoids are amenable to high-throughput drug screens that can be validated in mice. We show clinically relevant responses to temozolomide (TMZ) and to targeted treatments, such as EGFR and CDK4/6 inhibitors in (epi)genetically defined subgroups, according to MGMT promoter and EGFR/CDK status, respectively. Dianhydrogalactitol (VAL-083), a promising bifunctional alkylating agent in the current clinical trial, displayed high therapeutic efficacy, and was able to overcome TMZ resistance in glioblastoma. Our work underscores the clinical relevance of glioma organoids and PDOX models for translational research and personalized treatment studies and represents a unique publicly available resource for precision oncology.

Abstract IA13: Tracking and targeting colorectal cancer evolution

Abstract When metastatic cancers are challenged with targeted agents, almost invariably a subset of cells insensitive to the drug emerges. As a result, in most instances, targeted therapies are only transiently effective in patients. Strategies to prevent or overcome resistance are therefore essential to design the next generation of clinical trials. How can we overcome the near certainty of disease recurrence following treatment with targeted agents? Addressing this question means considering as a target not “only” individual oncogenes but also the evolving nature of human tumors. We used colorectal cancer (CRC) as a model system to test the hypothesis that by understanding tumors’ evolution, the emergence of drug resistance can be controlled. We find that clonal dynamics can be monitored in real time in the blood of patients, and liquid biopsies can be used to intercept the emergence of resistant clones before relapses are clinically manifest. We discovered that a multistep clonal evolution process driven by progressive increases in drug fitness underlies the development of resistance in cells and patient avatars. To have long-term efficacy, the use of targeted therapies must take into account the continuous evolution of cancer cells, that is to say, therapies must adapt to tumor evolution. One possibility is to anticipate the changes the tumors will make. For example, by knowing in advance how CRC cells overcome resistance to EGFR blockade, we devised further rounds of therapy. These findings became the bases of clinical trials aimed at targeting cancer evolution and exploiting liquid biopsies to monitor the emergence of drug resistance and to design further lines of therapies. Citation Format: Alberto Bardelli. Tracking and targeting colorectal cancer evolution [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr IA13.

Physiomimetic Models of Adenomyosis.

Adenomyosis remains an enigmatic disease in the clinical and research communities. The high prevalence, diversity of morphological and symptomatic presentations, array of potential etiological explanations, and variable response to existing interventions suggest that different subgroups of patients with distinguishable mechanistic drivers of disease may exist. These factors, combined with the weak links to genetic predisposition, make the entire spectrum of the human condition challenging to model in animals. Here, after an overview of current approaches, a vision for applying physiomimetic modeling to adenomyosis is presented. Physiomimetics combines a system's biology analysis of patient populations to generate hypotheses about mechanistic bases for stratification with in vitro patient avatars to test these hypotheses. A substantial foundation for three-dimensional (3D) tissue engineering of adenomyosis lesions exists in several disparate areas: epithelial organoid technology; synthetic biomaterials matrices for epithelial–stromal coculture; smooth muscle 3D tissue engineering; and microvascular tissue engineering. These approaches can potentially be combined with microfluidic platform technologies to model the lesion microenvironment and can potentially be coupled to other microorgan systems to examine systemic effects. In vitro patient-derived models are constructed to answer specific questions leading to target identification and validation in a manner that informs preclinical research and ultimately clinical trial design.

Zebrafish patient avatars in cancer biology and precision cancer therapy.

In precision oncology, two major strategies are being pursued for predicting clinically relevant tumour behaviours, such as treatment response and emergence of drug resistance: inference based on genomic, transcriptomic, epigenomic and/or proteomic analysis of patient samples, and phenotypic assays in personalized cancer avatars. The latter approach has historically relied on in vivo mouse xenografts and in vitro organoids or 2D cell cultures. Recent progress in rapid combinatorial genetic modelling, the development of a genetically immunocompromised strain for xenotransplantation of human patient samples in adult zebrafish and the first clinical trial using xenotransplantation in zebrafish larvae for phenotypic testing of drug response bring this tiny vertebrate to the forefront of the precision medicine arena. In this Review, we discuss advances in transgenic and transplantation-based zebrafish cancer avatars, and how these models compare with and complement mouse xenografts and human organoids. We also outline the unique opportunities that these different models present for prediction studies and current challenges they face for future clinical deployment.

Assembly and Maintenance of Sarcomere Thin Filaments and Associated Diseases.

Sarcomere assembly and maintenance are essential physiological processes required for cardiac and skeletal muscle function and organism mobility. Over decades of research, components of the sarcomere and factors involved in the formation and maintenance of this contractile unit have been identified. Although we have a general understanding of sarcomere assembly and maintenance, much less is known about the development of the thin filaments and associated factors within the sarcomere. In the last decade, advancements in medical intervention and genome sequencing have uncovered patients with novel mutations in sarcomere thin filaments. Pairing this sequencing with reverse genetics and the ability to generate patient avatars in model organisms has begun to deepen our understanding of sarcomere thin filament development. In this review, we provide a summary of recent findings regarding sarcomere assembly, maintenance, and disease with respect to thin filaments, building on the previous knowledge in the field. We highlight debated and unknown areas within these processes to clearly define open research questions.

Abstract LB-299: A comprehensive platform of patient-derived xenografts and matched cell lines mirrors the genomic landscape of colorectal cancer

Abstract Preclinical models that accurately reflect patients’ tumor with regards to histopathology, genomics, and therapeutic response represent a compelling need to fuel the progress of effective cancer treatments. Patient-derived tumor xenografts (PDXs) have significantly accelerated this process, but, although they closely mirror structural and molecular features of the tumor of origin, they still retain important restrictions related to maintenance costs and large-scale screening. To overcome this issue, we have established a novel platform of 2D-cell lines (xeno-cell lines, XL) derived from PDXs of colorectal cancer (CRC) from which patient’s germline gDNA was available. We have characterized XL-cells at multiple levels to confirm their proximity to the PDXs of origin and to assess their suitability as patient avatars in vitro to interrogate functional networks in colorectal cancer. All XL-cells showed an epithelial-like morphology and phenotype, as also confirmed by EMT biomarker transcriptomic analysis. Whole exome and RNA-seq analyses showed that genomic features were consistently preserved between PDXs and matched cell models. Expression analysis revealed the XL-line collection as a significant representative of all CRC subtypes (CMS and CRIS subgroups). Furthermore, genomic analysis allowed the identification of molecular biomarkers of response and resistance to targeted therapies, including EGFR and HER2 blockade. In particular, molecular determinants of resistance to dual-HER2 blockade previously reported in the Heracles-A trial were validated in XL-cells. In conclusion, the XL-cell line and PDX platform represents a unique and comprehensive preclinical tool to validate gene function e to identify novel pharmacological vulnerabilities in colorectal cancer. Citation Format: Luca Lazzari, Giorgio Corti, Claudio Isella, Monica Montone, Pamela Arcella, Eugenia Zanella, Luca Novara, Fabiane Barbosa, Andrea Cassingena, Carlotta Cancelliere, Enzo Medico, Andrea Sartore-Bianchi, Salvatore Siena, Andrea Bertotti, Livio Trusolino, Federica Di Nicolantonio, Michael Linnebacher, Alberto Bardelli, Sabrina Arena. A comprehensive platform of patient-derived xenografts and matched cell lines mirrors the genomic landscape of colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-299.

Abstract 1059: A case study: OncoRat is a viable patient avatar for a NSCLC patient with a Y1248H Met activating mutation

Abstract Human cancer xenografts in rodents can provide predictive data on the success of candidate drugs in clinical trials and have been a pivotal tool in moving new drugs from the bench to the clinic. However, currently available immunodeficient mouse models have shown some limitation and variability in tumor take rates and growth kinetics in cancer cell lines. In addition, commercially available human cancer cell lines aren’t representative of the genomic and molecular diversity of cancers found in patients. Patient Derived Xenograft (PDX), in which tumor tissue is transplanted directly into rodents after biopsy from the patient, better represents that molecular signature, heterogeneity, and pathology of the original tumor. Therefore, in vivo efficacy studies with PDX models could be highly predictive for treatment sensitivity. Despite the many advantages of PDXs for preclinical research, PDX mouse models are hindered by low engraftment rates and slow tumor growth kinetics. The loss of patient tumor heterogeneity and stromal cells as the PDX is passaged multiple times to generate sufficient tumor tissue to inoculate a cohort of animals for efficacy studies is also a disadvantage in the immunodeficient mouse models. To address these limitations, we have introduced the OncoRat®; built on the SRGTM Platform, a Sprague-Dawley Rag2/Il2rg double knockout rat that lacks mature B cells, T cells, and circulating NK cells. We have demonstrated that the OncoRat has improved tumor take rate and growth kinetics for non-small cell lung cancer (NSCLC) PDXs. The NSLSC PDXs in the OncoRat have a much larger tumor volume, over 20,000 mm3 in the first passage (P0) in the rat, which provides an ample source of tissue for characterization and/or subsequent passage (P1) into OncoRat for drug efficacy studies. This leads to fewer animals used for study and faster timelines to drug efficacy data, resulting in a reduction in cost. In addition, we have used genomic analysis for guidance in planning in vivo efficacy studies. One of our NSCLC PDX models harbors a novel mutation in the MET pathway, suggesting this tumor would not be responsive to standard of care treatment. An efficacy study we performed in the OncoRat suggests that this particular tumor would respond well to Type II MET inhibitors, such as Cabonzantinib. This proof of concept study demonstrates that genomic and molecular analysis can provide insight into treatment outcomes and that PDX models in the OncoRat could serve as patient avatars for predicting treatment outcomes. Citation Format: Fallon K. Noto, Bisoye Towobola Adedeji, Sam Moody, Chris Brenzel, Jack Crawford, Goutham Narla, Tseten Yeshi Jamling. A case study: OncoRat is a viable patient avatar for a NSCLC patient with a Y1248H Met activating mutation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1059.

Virtual Standardized Patient Simulation: Case Development and Pilot Application to High-Value Care.

High-value care (HVC) suggests that good history taking and physical examination should lead to risk stratification that drives the use or withholding of diagnostic testing. This study describes the development of a series of virtual standardized patient (VSP) cases and provides preliminary evidence that supports their ability to provide experiential learning in HVC. This pilot study used VSPs, or natural language processing-based patient avatars, within the USC Standard Patient platform. Faculty consensus was used to develop the cases, including the optimal diagnostic testing strategies, treatment options, and scored content areas. First-year resident physician learners experienced two 90-minute didactic sessions before completing the cases in a computer laboratory, using typed text to interview the avatar for history taking, then completing physical examination, differential diagnosis, diagnostic testing, and treatment modules for each case. Learners chose a primary and 2 alternative "possible" diagnoses from a list of 6 to 7 choices, diagnostic testing options from an extensive list, and treatments from a brief list ranging from 6 to 9 choices. For the history-taking module, both faculty and the platform scored the learners, and faculty assessed the appropriateness of avatar responses. Four randomly selected learner-avatar interview transcripts for each case were double rated by faculty for interrater reliability calculations. Intraclass correlations were calculated for interrater reliability, and Spearman ρ was used to determine the correlation between the platform and faculty ranking of learners' history-taking scores. Eight VSP cases were experienced by 14 learners. Investigators reviewed 112 transcripts (4646 learner query-avatar responses). Interrater reliability means were 0.87 for learner query scoring and 0.83 for avatar response. Mean learner success for history taking was scored by the faculty at 57% and by the platform at 51% (ρ correlation of learner rankings = 0.80, P = 0.02). The mean avatar appropriate response rate was 85.6% for all cases. Learners chose the correct diagnosis within their 3 choices 82% of the time, ordered a median (interquartile range) of 2 (2) unnecessary tests and completed 56% of optimal treatments. Our avatar appropriate response rate was similar to past work using similar platforms. The simulations give detailed insights into the thoroughness of learner history taking and testing choices and with further refinement should support learning in HVC.

Yeast Models of Phosphomannomutase 2 Deficiency, a Congenital Disorder of Glycosylation.

Phosphomannomutase 2 Deficiency (PMM2-CDG) is the most common monogenic congenital disorder of glycosylation (CDG) affecting at least 800 patients globally. PMM2 orthologs are present in model organisms, including the budding yeast Saccharomyces cerevisiae gene SEC53. Here we describe conserved genotype-phenotype relationships across yeast and human patients between five PMM2 loss-of-function missense mutations and their orthologous SEC53 mutations. These alleles range in severity from folding defective (hypomorph) to dimerization defective (severe hypomorph) to catalytic dead (null). We included the first and second most common missense mutations – R141H, F119L respectively– and the most common compound heterozygote genotype – PMM2R141H/F119L – observed in PMM2-CDG patients. Each mutation described is expressed in haploid as well as homozygous and heterozygous diploid yeast cells at varying protein expression levels as either SEC53 protein variants or PMM2 protein variants. We developed a 384-well-plate, growth-based assay for use in a screen of the 2,560-compound Microsource Spectrum library of approved drugs, experimental drugs, tool compounds and natural products. We identified three compounds that suppress growth defects of SEC53 variants, F126L and V238M, based on the biochemical defect of the allele, protein abundance or ploidy. The rare PMM2 E139K protein variant is fully functional in yeast cells, suggesting that its pathogenicity in humans is due to the underlying DNA mutation that results in skipping of exon 5 and a nonfunctional truncated protein. Together, these results demonstrate that yeast models can be used to characterize known and novel PMM2 patient alleles in quantitative growth and enzymatic activity assays, and used as patient avatars for PMM2-CDG drug screens yielding compounds that could be rapidly cross-validated in zebrafish, rodent and human organoid models.

Cancer cell lines as patient avatars for drug response prediction.

Patient-derived cancer cell lines could address two major challenges in oncology: real-time drug response prediction and the creation of massive knowledge banks. A new study showcases the power of this approach for precision oncology.

PO-050 A molecularly annotated platform of pdx-derived cell lines mirrors the genomic landscape of colorectal cancer

IntroductionProgress in the development of effective cancer treatments is limited by the availability of tumour models that accurately reflect patient tumour with regards to histopathology, genomic landscape, and therapeutic response. To accomplish these needs, patient-derived tumour xenografts (PDX) were developed in recent years. Although they closely mirror structural and molecular features of the tumour of origin, PDXs still retain important restrictions related to maintenance costs and large-scale screening. To overcome this issue, we have established a novel platform of 2D cell lines (xeno-cell lines, XL) derived from PDXs of colorectal cancer (CRC) from which patient’s germline gDNA was available. We have characterised XL-cells at multiple levels to assess their suitability as patient avatars to interrogate functional networks in colorectal cancer.Material and methodsExome and expression analysis were performed on the entire xeno-cell line collection. Biomarkers of response and resistance to anti-HER therapy have been annotated in cell lines and pharmacological analysis to validate drug targets has been accordingly completed.Results and discussionsAll XL-cells showed an epithelial-like morphology and phenotype, as also confirmed by EMT biomarker analysis. Genetic features (mutation and copy number profiles) were consistently preserved between PDXs and matched cell models, and expression analysis revealed XL-line collection as a significant representative of all CRC subtypes (CMS and CRIS subgroups). Whole exome and RNA-seq analyses allowed the identification of molecular biomarkers of response and resistance to targeted therapies, including EGFR and HER2 blockade. Genotype-driven responses observed in vitro in XL-cells were confirmed in vivo in the corresponding PDX.ConclusionThe XL-cell line platform represents a valuable preclinical tool for functional gene validation and proof of concept studies of novel therapeutics in colorectal cancer.

Abstract IA18: Cancer evolution as a therapeutic target

Abstract When metastatic cancers are challenged with targeted agents, almost invariably a subset of cells insensitive to the drug emerges. As a result, in most instances, targeted therapies are only transiently effective in patients. Strategies to prevent or overcome resistance are therefore essential to design the next generation of clinical trials. How can we overcome the near-certainty of disease recurrence following treatment with targeted agents? Addressing this question means considering as a target not only individual oncogenes but also the evolving nature of human tumors. We used colorectal cancer (CRC) as a model system to test the hypothesis that by understanding tumor's evolution, the emergence of drug resistance can be controlled. We find that clonal dynamics can be monitored in real time in the blood of patients, and liquid biopsies can be used to intercept the emergence of resistant clones before relapses are clinically manifest. We discovered that a multistep clonal evolution process driven by progressive increases in drug fitness underlies the development of resistance in cells and patient avatars. To have long-term efficacy, the use of targeted therapies must take into account the continuous evolution of cancer cells, that is to say, therapies must adapt to tumor evolution. One possibility is to anticipate the changes the tumors will make. For example, by knowing in advance how CRC cells overcome resistance to EGFR blockade, we devised further rounds of therapy. Another approach is to unleash the ability of the immune system to recognize drug-resistant cells. We tested this possibility in syngeneic mouse models of CRC sensitive to targeted therapies. Our findings indicate that manipulation of the mutational loads can trigger prolonged therapeutic responses that are not observed when cancer cells are challenged with targeted drugs alone. We postulate that rationally combined targeted and immunotherapies can restrain tumor evolution and can limit the emergence of drug resistance, thus leading to long-term responses. Citation Format: Alberto Bardelli. Cancer evolution as a therapeutic target [abstract]. In: Proceedings of the AACR International Conference held in cooperation with the Latin American Cooperative Oncology Group (LACOG) on Translational Cancer Medicine; May 4-6, 2017; São Paulo, Brazil. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(1_Suppl):Abstract nr IA18.

Microchamber Cultures of Bladder Cancer: A Platform for Characterizing Drug Responsiveness and Resistance in PDX and Primary Cancer Cells

Precision cancer medicine seeks to target the underlying genetic alterations of cancer; however, it has been challenging to use genetic profiles of individual patients in identifying the most appropriate anti-cancer drugs. This spurred the development of patient avatars; for example, patient-derived xenografts (PDXs) established in mice and used for drug exposure studies. However, PDXs are associated with high cost, long development time and low efficiency of engraftment. Herein we explored the use of microfluidic devices or microchambers as simple and low-cost means of maintaining bladder cancer cells over extended periods of times in order to study patterns of drug responsiveness and resistance. When placed into 75 µm tall microfluidic chambers, cancer cells grew as ellipsoids reaching millimeter-scale dimeters over the course of 30 days in culture. We cultured three PDX and three clinical patient specimens with 100% success rate. The turn-around time for a typical efficacy study using microchambers was less than 10 days. Importantly, PDX-derived ellipsoids in microchambers retained patterns of drug responsiveness and resistance observed in PDX mice and also exhibited in vivo-like heterogeneity of tumor responses. Overall, this study establishes microfluidic cultures of difficult-to-maintain primary cancer cells as a useful tool for precision cancer medicine.

Abstract SY21-03: Cancer evolution as a therapeutic target

Abstract When metastatic cancers are challenged with targeted agents, almost invariably a subset of cells insensitive to the drug emerges. As a result, in most instances targeted therapies are only transiently effective in patients. Strategies to prevent or overcome resistance are therefore essential to design the next generation of clinical trials. How can we overcome the near-certainty of disease recurrence following treatment with targeted agents? Addressing this question means considering as a target not “only” individual oncogenes but also the evolving nature of human tumors. We used colorectal cancer (CRC) as a model system to test the hypothesis that by understanding tumor’s evolution, the emergence of drug resistance can be controlled. We find that clonal dynamics can be monitored in real time in the blood of patients, and liquid biopsies can be used to intercept the emergence of resistant clones before relapses are clinically manifest. We discovered that a multistep clonal evolution process driven by progressive increases in drug fitness underlies the development of resistance in cells and patient avatars. To have long-term efficacy, the use of targeted therapies must take into account the continuous evolution of cancer cells; that is to say, therapies must adapt to tumor evolution. One possibility is to anticipate the changes the tumors will make. For example, by knowing in advance how CRC cells overcome resistance to EGFR blockade, we devised further rounds of therapy. Another approach is to unleash the ability of the immune system to recognize drug-resistant cells. We tested this possibility in syngeneic mouse models of CRC sensitive to targeted therapies. Our findings indicate that manipulation of the mutational loads can trigger prolonged therapeutic responses that are not observed when cancer cells are challenged with targeted drugs alone. We postulate that rationally combined targeted therapies and immunotherapies can restrain tumor evolution and can limit the emergence of drug resistance, thus leading to long-term responses. Citation Format: Alberto Bardelli. Cancer evolution as a therapeutic target [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr SY21-03. doi:10.1158/1538-7445.AM2017-SY21-03

Abstract 4935: Development of a human pancreatic tumor microenvironment system (TMeS) for evaluation of novel therapeutics

Abstract The development of drugs to treat cancer is severely hampered by the inefficiency of translating pre-clinical in vitro and mouse studies into clinical benefit. Over 90% of drugs that progress through pre-clinical studies fail in human trials. Therefore, there is a critical need to improve the accuracy of evaluating pre-clinical drug efficacy through the development of more physiologically relevant human models. This is especially the case for pancreatic cancer, the 4th leading cause of cancer deaths with a 5-year survival rate of <6%, where new therapies are desperately needed. The tumor microenvironment (TME) of PDAC contains numerous cell types including vascular endothelial cells, stellate cells and fibroblasts, as well as a complex extracellular matrix (ECM), all of which contribute to the growth and survival of cancer cells, as well as posing potential targets for therapeutic intervention. Thus, a more complete and nuanced understanding of the PDAC TME is required for the rational development of effective therapies. To address this problem, an in vitro tumor microenvironment system (TMeS) was engineered to incorporate tumor capillary hemodynamics and biological transport with co-cultured human microvascular endothelial cells, along with pancreatic tumor and stellate cells. We demonstrate that significant tumor cell transcriptomic changes occur in the TMeS that correlate with the in vivo xenograft transcriptome, including alterations in cell cycle regulation, oncogene signaling, and metabolism. PDAC tumor cells from two patients were inhibited by the human Cmax dose of gemcitabine to levels paralleling the patients’ clinical responses. Previous work demonstrated that the FAK inhibitor, PF-562,271, worked only on in vivo xenografts and not on 2D in vitro PDAC cultures and here we show that PF-562,271 effectively inhibited PDAC growth in the TMeS indicating in vivo-like drug responses. In sum, the TMeS recapitulates the in vivo xenograft transcriptional program and responds to both established and experimental small molecule inhibitor chemotherapeutics at concentrations that correspond to human therapeutic plasma levels. Therefore, this model provides a unique platform to rigorously test the contributions of the cellular and molecular components of the TME through manipulating individual constituents in a controlled fashion that is not possible in vivo. Moreover, the TMeS can be used for the rapid evaluation of novel precision therapies. Finally, this system is amenable to using patient tumor material directly, enabling the potential use of the TMeS for patient avatars. Citation Format: Daniel G. Gioeli, Chelsi Snow, Michael Simmers, Robert Figler, J. Thomase Parsons, Stephen Hoang, Todd Bauer, Brian Wamhoff. Development of a human pancreatic tumor microenvironment system (TMeS) for evaluation of novel therapeutics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4935. doi:10.1158/1538-7445.AM2017-4935

Explicating the Effectiveness of Virtual Clinical Reality Simulation Education In Enhancing the Competence of Undergraduate Nursing Students

Introduction:Benner’s Theory of Novice to Expert has yet to be used in application to Virtual Clinical Education. Little evidence is available that discusses the benefits of Virtual Clinical Education (VCE) to undergraduate students. This presentation will describe the benefits of Virtual Clinical Education through the application of Benner’s Novice to Expert theory in relating how theoretically such a learning activity may enhance the clinical performance and level of skill acquisition of undergraduate nursing students.Objectives:After scrupulously examining Benner’s theory of Novice to Expert, research must be conducted in how virtual clinical simulation enhance the performance of undergraduate students. Therefore, the research questions based on this theory are as follows: In undergraduate nursing students enrolled in the domain of medical surgical nursing courses, how does participation in virtual clinical education affect such students’ perception of their ability to recognize aspects and attributes of a clinical situation, as well as, maxims and salient parts of such situations? Does participation in virtual clinical education develop perceived of competency and experience? Does student engagement in virtual clinical educations as a learning activity allow them to perceive themselves as having reached the advanced beginner, competent, or proficient level of medical surgical nursing performance? This study will aim to describe the medical surgical student nurse’s conscious experience of virtual clinical education by exploring the aforementioned research questions. The meaning, structure, and essence of the lived experience of taking on the role of a nurse avatar during a virtual clinical education will be explored. The goal of the researcher is to gain access to the student nurse’s life or inner world and subjective experience.Results:Subjects perceived themselves to be an advanced beginner as a result of the VCE experiences. The highest levels of medical surgical nursing performance perceived were competent and proficient in two separate students. Students found the virtual environmental features of patient charts, patient avatars, medication administration records, and electronic health records to assist them in learning how to implement nursing care. It is said to supplement lectures in a dynamic case study format that is “more interesting than just reading information”. Students perceived it prepared them better for clinical experiences. Students are enabled to study the patient thoroughly and in a non-intimidating environment. An unexpected finding was that students reported they felt they would be better able to navigate patient charts and electronic health records as a result of the VCE experiences.Students explained that the virtual clinical education experience would be useful if provided to students from the beginning of the semester so that they can integrate their experiences into true clinical practice. Virtual clinical education also is perceived to cause more effective transfer of knowledge in relation to critical thinking. Students perceive the simulated virtual clinical environment to induce less anxiety so they were provided “more time to think” so as to identify salient points of patient conditions. Students find the environment to be realistic possessing “all the aspects of the clinical experience minus the live bodies and interactions with patient, families, and the clinical team”.Conclusion:Virtual clinical reality simulation is perceived by students to be a useful tool to facilitate their transfer of theoretical knowledge to practical knowledge. Nurse educators can attempt to cultivate the awareness of nursing students by presenting them with complex ill-defined, authentic tasks during virtual simulation scenarios. As a result, there is a shift that occurs so that students are able to retrieve relevant information and clinical reasoning occurs. This enables students to “perform skills in a real world problem solving context” (Onda, 2012, p. 279). Educators must strike a balance between teaching the cognitive base and enabling students with opportunities to put such knowledge to use, as situated learning theory encourages. As a result, clinical reasoning skills will be able to evolve. When virtual clinical simulation is used within nursing clinical education, a shift of nursing education’s paradigm from teaching to learning will truly occur (Onda, 2012).