Patient-specific Drug Responses Research Articles

Abstract 4837: Development of an in vitro 3D glioblastoma model system for patient-specific drug response profiling

Abstract Glioblastoma (GBM) has a median survival of less than 2 years due to intra-tumoral and inter-patient heterogeneity, diffuse infiltration of adjacent brain tissue, and absence of effective therapies. Development of more efficacious therapies will require better GBM models for the testing and identification of novel agents; traditional 2D cell culture lacks biologic and clinical fidelity and orthotopic xenograft models are costly, low throughput, and time consuming. We have developed a complex, patient-specific 3D cultured GBM model to assay drug response that combines high-throughput drug response determination with neurosphere formation and next-generation sequencing (NGS). Neurosphere formation and the presence/quality of glioblastoma stem cells (GSCs) has been validate through limited dilution growth in vivo. Our 3D model system has been validated against the primary patient GBM tissue and/or patient-derived xenografts (PDX) and consists of histology, epigenetic and mRNA expression analysis, and comparison of in vivo drug response. This strategy enabled examination of MGMT methylation in relation to temozolomide response, and possible actionable genetic mutations with candidate targeted therapies. Using our 3D model, we have observed EGFR-amplified GBM sensitivity to the EGFR inhibitor afatanib, and PTEN mutant GBM sensitivity to dual PI3K/mTOR inhibitor dactolisib. These data suggest validation of clinical and molecular correlation with this new in vitro, patient-derived 3D GBM model for drug response profiling. Our data supports the further development and use of complex 3D models, neurosphere formation, and NGS profiling for patient-specific GBM analysis. This model system is currently being considered for preclinical assessment of novel therapies and may be a useful adjunct in future precision medicine applications to improve patient outcomes. Citation Format: Teresa DesRochers, Ashley Clark, Lauren O'Donnell, Qi Guo, Lillia Holmes, Lacey Dobrolecki, Michael Lewis, David Schammel, Jeff Edenfield, Charles Kanos, Fred Nelson, Steve Gardner, Michael Lynn, Philip Hodge, Christopher Corless, Paul Clark, Hal E. Crosswell, John Kuo. Development of an in vitro 3D glioblastoma model system for patient-specific drug response profiling [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 4837. doi:10.1158/1538-7445.AM2017-4837

MP44-17 PATIENT DERIVED XENOGRAFTS AS PRECLINICAL MODELS OF UROLOGICAL MALIGNANCIES

You have accessJournal of UrologyBladder Cancer: Basic Research & Pathophysiology I1 Apr 2017MP44-17 PATIENT DERIVED XENOGRAFTS AS PRECLINICAL MODELS OF UROLOGICAL MALIGNANCIES Sofia Karkampouna, Eugenio Zoni, Federico la Manna, Letizia Astrologo, Lijkele Beimers, Peter Kloen, Joel Grosjean, Irena Klima, Martin Spahn, Marianna Kruithof-de Julio, and George N. Thalmann Sofia KarkampounaSofia Karkampouna More articles by this author , Eugenio ZoniEugenio Zoni More articles by this author , Federico la MannaFederico la Manna More articles by this author , Letizia AstrologoLetizia Astrologo More articles by this author , Lijkele BeimersLijkele Beimers More articles by this author , Peter KloenPeter Kloen More articles by this author , Joel GrosjeanJoel Grosjean More articles by this author , Irena KlimaIrena Klima More articles by this author , Martin SpahnMartin Spahn More articles by this author , Marianna Kruithof-de JulioMarianna Kruithof-de Julio More articles by this author , and George N. ThalmannGeorge N. Thalmann More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.1348AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Prostate and bladder cancer (PCa, BLCa) are highly frequent and metastatic urological malignancies. Relevant models for the study of tumor heterogeneity and drug resistance mechanisms are required. Patient-derived xenografts (PDX) comprise excellent tools for the maintenance of the molecular and functional properties of the original tumor and allow the long-term study and in vivo drug response assays. The objective is to establish PDX models from primary and metastatic PCa and BLCa, which are currently of limited availability, and to develop a platform for standardized characterization and drug response tests of the PDX tumors in vivo and in ex vivo tissue slices system. METHODS PDX are generated by needle biopsy implantation (PCa, BLCa) subcutaneously in immunocompromised NOD SCID gamma mice. Tumors are serially transplanted in vivo. Histopathological and RNA analysis of the different passages of PDX tumors is performed to identify morphological and molecular similarities with the original tumor. As preclinical model, PDX tumors are maintained ex vivo (ten days) and used for drug testing assays based on the standard treatment used for primary types of PCa and BLCa. RESULTS PDX models from primary and metastatic PCa and BLCa (BMURO) maintain morphology similar to the original tumor. Tumors (clinical specimens, PDXs) are tested in ex vivo drug response assays using our developed methodology on whole tissue slice culture system. Histological morphology of Lymph node-PCa tumor slices is affected by exposure to cytostatic agents (cabazitaxel, docetaxel). Bone metastasis BLCa (BMURO) tumor slices treated ex vivo with drug compounds exhibit morphological changes at the lowest concentrations of cisplatin and gemcitabine. Ongoing studies aim to address whether the ex vivo and in vivo PDX drug response recapitulates the individual drug response observed during clinical treatment prior to surgery. CONCLUSIONS Xenograft models are promising tools for the study of personalized treatment and drug resistance mechanisms in PCa and BLCa. The ex vivo drug response assays on PDX tumor slices represent an experimental screening platform of patient-specific drug responses. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e570 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Sofia Karkampouna More articles by this author Eugenio Zoni More articles by this author Federico la Manna More articles by this author Letizia Astrologo More articles by this author Lijkele Beimers More articles by this author Peter Kloen More articles by this author Joel Grosjean More articles by this author Irena Klima More articles by this author Martin Spahn More articles by this author Marianna Kruithof-de Julio More articles by this author George N. Thalmann More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

MiRNA Profiling in Human Induced Pluripotent Stem Cells.

Human iPS cells are capable of differentiation towards all three germ layer lineages. As well as being of use for the study of developmental biology, these cells also provide an excellent resource for disease modeling and cell replacement therapies. iPS cells derived from an individual with a disease type of interest can be differentiated towards the cell type afflicted in that particular disease. Such differentiated cell types can be used to test patient-specific drug responses in vitro, for generation of replacement cells for transplantation, or as a starting material for gene editing to correct disease-causing mutations/deletions. With such a vast array of potential applications, there is a great need to understand the exact mechanisms controlling the maintenance of pluripotency, and the distinct cues signaling these cells to differentiate towards lineages of interest. This chapter focuses on microRNA profiling using TaqMan Human MicroRNA Arrays to examine expression of 754 miRNAs in human iPS cells in the pluripotent state, and iPS derived definitive endoderm.

DDIS-13. IDENTIFICATION OF INDIVIDUALIZED THERAPY OPTIONS IN PATIENTS WITH GLIOBLASTOMA BY HIGH-THROUGHPUT DRUG SCREENING

Glioblastoma (GBM) remains rapidly fatal and identification of new treatments has proven difficult due to patient specific characteristics of the tumor. Patient-derived GBM cell cultures enriched for tumor stem cells under serum-free, growth factor-enriched conditions are able to recapitulate the human disease upon xenotransplantation. We hypothesized that patient-derived GBM cultures display patient specific drug sensitivity patterns. We cultured 12 primary GBMs and evaluated viability and cytotoxicity to 470 anticancer drugs in a 5-point dose-response curve using high-throughput screening. The drug collection consisted of both approved and investigational drugs. Screening results were verified in 5 of the screened samples to 4 effective drugs and to temozolomide, the standard of care, across assays measuring viability, cytotoxicity, sphere-forming capability and invasion. We found that inhibition of survivin by an investigational drug was lethal in all samples and effective across all assays. Furthermore, several FDA approved drugs were potent across many samples such as two proteasome inhibitors, a protein synthesis inhibitor and a RNA-/DNA-synthesis inhibitor. Several investigational drugs in clinical phases were potent in many samples, such as a Chk1/Cdk2–, a combined HDAC-/PIK3- and two HSP90 inhibitors. Interestingly, temozolomide was ineffective in all samples except one. In 9 of the screened samples a patient specific drug response was identified. We were able to reproduce the effect of potent drugs and the resistance to temozolomide in our verification set up measuring viability, cytotoxicity and sphere-forming capability. However, the effect on invasion was limited. The high-throughput screening of patient-derived GBM samples creates a drug sensitivity and resistance profile to each patient and leads to identification of possible new effective treatments. By reproducing the screening results in our verification set up we are able to reliably identify preclinical effective therapeutic options on a patient specific level with the possibility to translate preclinical data into a clinical setting.

High-content screening identifies kinase inhibitors that overcome venetoclax resistance in activated CLL cells

AbstractNovel agents such as the Bcl-2 inhibitor venetoclax (ABT-199) are changing treatment paradigms for chronic lymphocytic leukemia (CLL) but important problems remain. Although some patients exhibit deep and durable responses to venetoclax as a single agent, other patients harbor subpopulations of resistant leukemia cells that mediate disease recurrence. One hypothesis for the origin of resistance to venetoclax is by kinase-mediated survival signals encountered in proliferation centers that may be unique for individual patients. An in vitro microenvironment model was developed with primary CLL cells that could be incorporated into an automated high-content microscopy-based screen of kinase inhibitors (KIs) to identify agents that may improve venetoclax therapy in a personalized manner. Marked interpatient variability was noted for which KIs were effective; nevertheless, sunitinib was identified as the most common clinically available KI effective in overcoming venetoclax resistance. Examination of the underlying mechanisms indicated that venetoclax resistance may be induced by microenvironmental signals that upregulate antiapoptotic Bcl-xl, Mcl-1, and A1, which can be counteracted more efficiently by sunitinib than by ibrutinib or idelalisib. Although patient-specific drug responses are common, for many patients, combination therapy with sunitinib may significantly improve the therapeutic efficacy of venetoclax.

A human pluripotent stem cell model of catecholaminergic polymorphic ventricular tachycardia recapitulates patient-specific drug responses

ABSTRACTAlthough β-blockers can be used to eliminate stress-induced ventricular arrhythmias in patients with catecholaminergic polymorphic ventricular tachycardia (CPVT), this treatment is unsuccessful in ∼25% of cases. Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) generated from these patients have potential for use in investigating the phenomenon, but it remains unknown whether they can recapitulate patient-specific drug responses to β-blockers. This study assessed whether the inadequacy of β-blocker therapy in an individual can be observed in vitro using patient-derived CPVT iPSC-CMs. An individual with CPVT harboring a novel mutation in the type 2 cardiac ryanodine receptor (RyR2) was identified whose persistent ventricular arrhythmias during β-blockade with nadolol were abolished during flecainide treatment. iPSC-CMs generated from this patient and two control individuals expressed comparable levels of excitation-contraction genes, but assessment of the sarcoplasmic reticulum Ca2+ leak and load relationship revealed intracellular Ca2+ homeostasis was altered in the CPVT iPSC-CMs. β-adrenergic stimulation potentiated spontaneous Ca2+ waves and unduly frequent, large and prolonged Ca2+ sparks in CPVT compared with control iPSC-CMs, validating the disease phenotype. Pursuant to the patient's in vivo responses, nadolol treatment during β-adrenergic stimulation achieved negligible reduction of Ca2+ wave frequency and failed to rescue Ca2+ spark defects in CPVT iPSC-CMs. In contrast, flecainide reduced both frequency and amplitude of Ca2+ waves and restored the frequency, width and duration of Ca2+ sparks to baseline levels. By recapitulating the improved response of an individual with CPVT to flecainide compared with β-blocker therapy in vitro, these data provide new evidence that iPSC-CMs can capture basic components of patient-specific drug responses.

Abstract 611: A complex 3D model of glioblastoma for patient-specific drug response profiling

Abstract Approximately 70,000 new cases of brain tumors will be diagnosed this year with glioblastoma (GBM) accounting for about 17% of those cases. Unfortunately the median survival for patients with GBM is only 14.6 months due to the complexity of the tumor, the pattern of diffuse spread within the brain, and the lack of effective therapeutic options. Complex in vitro tumor models developed in 3D better mimic in vivo biology, and, when utilizing patient-derived cells, may offer robust platforms for new drug development and patient-specific drug response profiling. We have previously shown this to be true with both breast and ovarian cancer and we have adopted this approach to modelling GBM ex vivo. We hypothesize that primary derived GBM tissues and stem cells cultured in complex 3D microenvironments can recapitulate the intra-tumor heterogeneity and drug resistance similar to that found in the clinical. To this end, we have developed 3D models of GBM that incorporate tumor cells, endothelial cells, and macrophages within a complex extracellular matrix and cultured them for up to 2 weeks under perfusion flow. We have created these models using both cell lines and primary patient cells and these 3D tissues have been analyzed for changes in viability (PrestoBlue and PicoGreen), marker expression (flow cytometry, Luminex, and protein arrays), macrophage differentiation and invasion (flow cytometry, multiphoton microscopy, and IHC), and methylation patterns (ChIP on chip arrays and methylation specific PCR). Initial optimization work using cell lines has revealed that culturing with endothelial cells and/or macrophages has an effect upon proliferation dependent upon the differentiation state of the macrophages. Additionally, co-culture conditions affect protein secretion and phosphorylation along with patterns of gene methylation. We have also examined how changes in the tumor microenvironment affect these different metrics by examining the role of hypoxic growth conditions. Work using patient cells isolated from primary glioblastoma has focused upon drug response dependent upon the tumor microenvironment and the presence of cancer stem cells utilizing a neurosphere generation assay. We have demonstrated temozolamide resistance in tumors with early relapse after initial chemo-radiation, and sensitivity to EGFR inhibitor afatanib in tumors with EGFR amplication, suggesting clinical and molecular correlation or our ex vivo 3D drug response profiling using patient derived GBM models. Taken together, our data support the further development and use of complex, 3D co-cultures to better mimic GBM in a patient-specific manner. These models are currently being considered for preclinical assessment of novel therapies, including chimeric antigen receptor T cells, and may be a useful adjunct in precision medicine applications to improve patient outcomes. Citation Format: Tessa DesRochers, Lillia Holmes, Lauren O’Donnell, Qi Guo, David Schammel, Jeff Edenfield, Charles C. Kanos, Hal E. Crosswell. A complex 3D model of glioblastoma for patient-specific drug response profiling. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 611.

Validation and Optimization of an Ex Vivo Assay of Intestinal Mucosal Biopsies in Crohn’s Disease: Reflects Inflammation and Drug Effects

Crohn’s disease (CD) is a chronic illness demanding better therapeutics. The marketed biologics only benefit some patients or elicit diminishing effect over time. To complement the known methods in drug development and to obtain patient specific drug responses, we optimized and validated a known human explant method to test drug candidates and pathophysiological conditions in CD intestinal biopsies. Mucosal biopsies from 27 CD patients and 6 healthy individuals were collected to validate an explant assay test where the polarized tissue was cultured on a novel metal mesh disk, slightly immersed in medium imitating an air-liquid interphase. After culture in high oxygen for 24 hours with or without biological treatment in the medium, biopsy integrity and penetration of antibodies was measured by immunohistochemistry (IHC). Nine cytokines were quantified in the conditioned medium as a read-out for degree of inflammation in individual biopsies and used to evaluate treatment efficacy. The biopsies were well-preserved, showing few structural changes. IHC revealed tissue penetration of antibodies demonstrating ability to test therapeutic antibodies. The cytokine release to the medium showed that the assay can distinguish between inflammation states and then validate the known effect of two treatment biologics confirmed by a detection panel of five specific cytokines. Our data also suggest that the assay would be able to indicate which patients are responders to anti-TNF-α therapeutics, and which are non-responders. This study demonstrates this version of an ex vivo culture as a valid and robust assay to assess inflammation in mucosal biopsies and test of the efficacy of novel drug candidates and current treatments on individual patients–potentially for a personalized medicine approach.

A Multidisciplinary Model Predicts Clinical Response in Relapsed Multiple Myeloma

The future of cancer treatment lies in personalized strategies designed to specifically recognize, target, and anticipate dynamic tumor subpopulations within an individual in response to drug. Multiple myeloma (MM) is at present an incurable malignancy of bone marrow resident plasma cells with highly variable survival as a consequence of both disease- and host-specific factors. 20% of MM patients, deemed high-risk (HRMM), have shown little benefit in the era of novel agents, with an OS of less than 2 years. Intuitive treatment strategies fail to account for the complexities and evolutionary dynamics of human tumors in the face of drugs. Intuitive treatment fails to adequately account for MM evolutionary dynamics and remains a critical barrier to successful cure or, at least, long-term disease control. Reasons for therapy failure include, but are not limited to, alternation of dominant clones with each line of therapy as a consequence of Darwinian dynamics, genomic instability leading to of tumor heterogeneity, and tumor microenvironment(TME)- mediated drug resistance. We have developed an integrated computational method accounting for phenotypic tumor heterogeneity. This novel ex vivo drug screen approach, termed EMMA (evolutionary mathematical myeloma advisor), predicts patient-specific drug response in silico from fresh bone marrow biopsies within 5 days. This method utilizes longitudinal non-destructive quantification of rate and dose responses of patient-derived MM cells to drugs in an ex vivo 3D reconstruction of the bone marrow microenvironment to provide real-time personalized predictions of treatment success (percent decrease in disease burden at 90 days). The current automated 384-well plate format allows testing of 31 different drugs or combinations against a single patient sample in 5 days. An evolutionary-based computational model uses the drug sensitivity profile obtained ex vivo to detect sub-populations and their contribution to overall clinical drug response. Each drug dose is imaged once every 30 minutes for 96h. This generates 1,920 data points per drug (or combination). From these data we characterize clonal architecture as it relates to drug sensitivity as phenotypic/functional biomarker for each drug or drug combination in each MM patient sample simultaneously. We have examined the predictive accuracy of EMMA in 26 patients to date. The Pearson correlation between ex vivo model predictions and actual tumor burden changes for the 26 patients examined generated the correlation coefficient r=0.87 (P<0.0001). Further, examination of the model predictions in terms of IMWG standards revealed that 23 out of 26 patients showed agreement between model estimation and actual clinical response (88.5% concordance). The remaining 3 patients diverged by one or two stages of response: one patient presented a very good partial response (VGPR, 98.5% reduction) while the model predicted a partial response (PR, 74.5% tumor reduction); the second patient presented a partial response (PR, 74% tumor reduction) while the model predicted a complete response (CR); and the third patient presented stable disease (SD, 12% tumor reduction) and the model predicted a minimal response (MR, 30% tumor reduction). To this end, EMMA generates patient-specific clinical response predictions to individual drugs or regimens with a high degree of clinical accuracy. Beyond testing for clinical drug response, EMMA may also be used to assess dominant cell signaling pathways. We have screened 5 patients with 25 protein kinase inhibitors (PKI) representing known signaling cascades in MM. Using heatmaps representing area under the curve (AUC) of dose-response surfaces (concentration x exposure time), we have observed both common and patient-specific sensitivities to PKIs. Together, these data demonstrate that the combination of a physiological reconstruction of the TME, a non-destructive and non-invasive cell viability assay, and mathematical models, were key to overcome the major limitations of previous predictive chemosensitivity assays. EMMA has the potential to provide precise clinical insight about treatment efficacy in a timely manner and thus become a decision support tool for oncologists based on the ever-changing clonal architecture in the face of therapy. DisclosuresBaz:Karyopharm: Research Funding; Celgene Corporation: Research Funding; Millennium: Research Funding; Sanofi: Research Funding.

Abstract 15566: Induced Pluripotent Stem Cell-Derived Cardiomyocytes Recapitulate Clinically Observed Refractoriness to Therapeutic β-Blockade in a Patient-Specific Model of Catecholaminergic Polymorphic Ventricular Tachycardia

Introduction: Catecholaminergic polymorphic ventricular tachycardia (CPVT) is an inherited arrhythmia syndrome characterized by diastolic store overload-induced Ca2+ waves during β-adrenergic receptor (β-AR) stimulation. Mysteriously, β-blockers are ineffective at abolishing stress-induced ventricular arrhythmias in ~25% of patients. Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) generated from these CPVT patients offer an attractive system for investigating the phenomenon, but it remains unknown whether iPSC-CMs can recapitulate clinically observed patient-specific drug responses. Hypothesis: This study assessed the hypothesis that patient-specific refractoriness to β-blocker therapy can be observed in vitro using CPVT iPSC-CMs. Methods: We generated iPSC-CMs from a control individual and a CPVT patient insensitive to the widely prescribed β-blocker nadolol, but responsive to flecainide, and compared the efficacy of the two drugs in vitro in diminishing diastolic Ca2+ waves and restoring Ca2+ spark parameters during β-AR stimulation. Results: In CPVT hiPSC-CMs (n = 34), β-AR agonism elicited intense diastolic Ca2+ waves and potentiated unduly frequent, large, and prolonged Ca2+ sparks compared to control iPSC-CMs (n = 12). Pursuant to the patient’s in vivo responses, nadolol-treated CPVT iPSC-CMs (n = 27) demonstrated inadequate improvement of Ca2+ handling defects during β-AR stimulation relative to flecainide-treated CPVT iPSC-CMs (n = 25). Nadolol showed no significant effect on the frequency of diastolic Ca2+ waves, but reduced mean amplitude by 50% (p &lt; 0.0001). In contrast, flecainide reduced both frequency and amplitude by 83% (p &lt; 0.001) and 72% (p &lt; 0.0001), respectively. During nadolol treatment, Ca2+ spark frequency, width, and duration remained significantly altered, while flecainide restored all Ca2+ spark parameters to baseline levels. Conclusions: Clinically observed recalcitrance to β-blocker therapy in individuals with CPVT can be modeled in vitro using patient-derived iPSC-CMs. Furthermore, the efficacy of other drugs such as flecainide can be comparatively evaluated, supporting the use of patient-specific iPSC-CMs as a clinically-relevant implement of precision medicine.

Reprogramming and transdifferentiation for cardiovascular development and regenerative medicine: where do we stand?

Heart disease remains a leading cause of mortality and a major worldwide healthcare burden. Recent advances in stem cell biology have made it feasible to derive large quantities of cardiomyocytes for disease modeling, drug development, and regenerative medicine. The discoveries of reprogramming and transdifferentiation as novel biological processes have significantly contributed to this paradigm. This review surveys the means by which reprogramming and transdifferentiation can be employed to generate induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) and induced cardiomyocytes (iCMs). The application of these patient-specific cardiomyocytes for both in vitro disease modeling and in vivo therapies for various cardiovascular diseases will also be discussed. We propose that, with additional refinement, human disease-specific cardiomyocytes will allow us to significantly advance the understanding of cardiovascular disease mechanisms and accelerate the development of novel therapeutic options.

A Virtual B Cell Lymphoma Model to Predict Effective Combination Therapy

Aberrant activation of the B cell receptor (BCR) signaling network drives survival and proliferation of many B cell malignancies, such as activated B cell like diffuse large B cell lymphoma (ABC-DLBCL). A number of small molecule inhibitors targeting various kinases in the BCR signaling network have been developed. However, clinical application of these targeted agents is facing several challenges such as low response rate and acquired drug resistance. The limited efficacy of single agent targeted therapy is at least partially due to pathway reactivation through crosstalks and compensatory circuits. By simultaneously repressing multiple nodes in the signaling network, combination therapy has the potential to completely extinguish signaling and induce more potent and durable response. The complexity of BCR signaling network makes it difficult to infer which combinations will be effective and synergistic. Given the large number of possible drug combinations, comprehensive experimental screening – including exploration of multiple dosages – is not practically feasible.Computational models of signaling networks that can accurately reconstruct signaling dynamics in silico may represent a useful alternative to experimental screening and trial-and-error experimental investigation. Here, we developed a computational model that integrates signal transduction, tumor growth, and drug kinetics to accurately simulate BCR signaling dynamics and the effect of drug-induced perturbation on signaling output and cell viability. We used this model to predict effective combinatorial therapy in silicoand validated some of these predictions using in vitro experiments.Based on experimentally verified protein-protein interactions, we constructed the first detailed kinetic model of the BCR signaling network covering three major signaling pathways downstream of BCR, namely NFkB, PI3K/AKT and MAPK. The model captured complex crosstalk between these three pathways and multiple feedback loops. Simulated kinase activation time courses under temporal antigen stimulus successfully recapitulated normal BCR signaling dynamics as reported in literature.Using published drug response data in the BCR signaling-dependent ABC-DLBCL cell line TMD8, we trained a tumor growth model which in combination with the kinetic model enabled reliable prediction of viability response of many drug combinations at various dosages. For example, predicted viability response of BTK inhibitor ibrutinib in combination with inhibitors targeting other kinases in the network, e.g. BKM-120 against PI3K, sotrastaurin against PKC-beta closely matched previously published experimental data in TMD8 (r>0.86,p<1e-11).We then sought to identify synergistic drug combinations by simulating viability response at 10x10 virtual dosages for each drug combination and estimating synergism using Bliss independence model. Computational screening predicted dual blockage of LYN and SYK as the most synergistic combination, which we confirmed experimentally by treating TMD8 cells with LYN inhibitor Dasatinib and SYK inhibitor R406 at multiple doses.Finally we sought to use our model to predict biomarkers of sensitivity and resistance to specific treatment strategies. By integrating expression levels of BCR signaling network components assessed by published primary DLBCL RNA-seq data, we simulated patient-specific drug responses and computed the correlation between expression level of specific components with viability response under specific treatments. We found that overexpression of PTP1B, which dephosphorylates BTK substrate PLCg2, predicts relative sensitivity to BTK inhibition. Supporting this prediction, we observed increased PTP1B expression in DLBCL cell lines sensitive to ibrutinib treatment, suggesting PTP1B as potential biomarker for ibrutinib sensitivity.In summary, this study provides a novel approach to computationally optimize combinatorial targeted therapy against aberrant BCR signaling and paves the way for the discovery of effective patient-specific drug combinations. DisclosuresMelnick:Bioreference: Scientific Advisory Board, Scientific Advisory Board Other; Calgene: Consultancy; Janssen: Research Funding; Genentech: Speakers Bureau.

Drug response of captured BT20 cells and evaluation of circulating tumor cells on a silicon nanowire platform.

Research on specific drug responses of circulating tumor cells (CTCs) provides very important information for treatment of cancer patients at a patient-specific level. For this reason, platforms for high capture efficiency of CTCs are essential for clinical evaluation of patient-specific drug responses of CTCs. Recently, nanostructure based platforms have been developed with a high capture efficiency of more than 93% due to high-affinity binding and the 3D nanotopographic features of the nanostructure substrate. In this study, the breast carcinoma cell-line (BT20) cells with an ultra-low abundance range were captured by streptavidin (STR)-functionalized silicon nanowire (SiNW) platforms for evaluation of capture efficiency. A capture efficiency of more than 90% was achieved. Specific drug responses of BT20 cells captured on STR-SiNW platforms were analyzed using tamoxifen or docetaxel as a function of incubation time and dose, and compared with a 96-well plate platform. The drug responses of CTCs on STR-SiNW platforms were more sensitive than a 96-well plate platform. In addition, CTCs were successfully captured and evaluated their size distribution from the blood of breast cancer patients using fluorescence imaging. In conclusion, we suggest that the SiNW platform is adaptable for clinical use in evaluation of CTCs and drug response tests.

Multiscale prediction of patient-specific platelet function under flow

AbstractDuring thrombotic or hemostatic episodes, platelets bind collagen and release ADP and thromboxane A2, recruiting additional platelets to a growing deposit that distorts the flow field. Prediction of clotting function under hemodynamic conditions for a patient's platelet phenotype remains a challenge. A platelet signaling phenotype was obtained for 3 healthy donors using pairwise agonist scanning, in which calcium dye–loaded platelets were exposed to pairwise combinations of ADP, U46619, and convulxin to activate the P2Y1/P2Y12, TP, and GPVI receptors, respectively, with and without the prostacyclin receptor agonist iloprost. A neural network model was trained on each donor's pairwise agonist scanning experiment and then embedded into a multiscale Monte Carlo simulation of donor-specific platelet deposition under flow. The simulations were compared directly with microfluidic experiments of whole blood flowing over collagen at 200 and 1000/s wall shear rate. The simulations predicted the ranked order of drug sensitivity for indomethacin, aspirin, MRS-2179 (a P2Y1 inhibitor), and iloprost. Consistent with measurement and simulation, one donor displayed larger clots and another presented with indomethacin resistance (revealing a novel heterozygote TP-V241G mutation). In silico representations of a subject's platelet phenotype allowed prediction of blood function under flow, essential for identifying patient-specific risks, drug responses, and novel genotypes.

MuteinDB: the mutein database linking substrates, products and enzymatic reactions directly with genetic variants of enzymes

Mutational events as well as the selection of the optimal variant are essential steps in the evolution of living organisms. The same principle is used in laboratory to extend the natural biodiversity to obtain better catalysts for applications in biomanufacturing or for improved biopharmaceuticals. Furthermore, single mutation in genes of drug-metabolizing enzymes can also result in dramatic changes in pharmacokinetics. These changes are a major cause of patient-specific drug responses and are, therefore, the molecular basis for personalized medicine. MuteinDB systematically links laboratory-generated enzyme variants (muteins) and natural isoforms with their biochemical properties including kinetic data of catalyzed reactions. Detailed information about kinetic characteristics of muteins is available in a systematic way and searchable for known mutations and catalyzed reactions as well as their substrates and known products. MuteinDB is broadly applicable to any known protein and their variants and makes mutagenesis and biochemical data searchable and comparable in a simple and easy-to-use manner. For the import of new mutein data, a simple, standardized, spreadsheet-based data format has been defined. To demonstrate the broad applicability of the MuteinDB, first data sets have been incorporated for selected cytochrome P450 enzymes as well as for nitrilases and peroxidases.Database URL: http://www.MuteinDB.org