Area Under The Dose-response Curve Research Articles

Inhibition of NF-κB Activation Improves Non-Nitric Oxide-Mediated Cutaneous Microvascular Function in Reproductive-Aged Healthy Women

PURPOSE: The human cutaneous circulation is used as an in vivo bioassay to examine mechanisms of systemic vascular function and dysfunction in health and disease. In cohorts of patients with accelerated cardiovascular disease risk, systemic interventions to investigate inflammatory mechanisms [e.g., oral salsalate; nuclear factor kappa-B (NF-κB) inhibitor] have been used to elucidate mechanisms underlying microvascular dysfunction. In healthy control subjects, inhibition of inflammatory mechanisms modestly reduces microvascular function. We hypothesize that inhibition of NF-κB activation may impair nitric oxide (NO)-mediated cutaneous microvascular function in reproductive-aged healthy women. METHODS: In a randomized, single-blind, placebo-controlled design, oral salsalate (1500mg/b.i.d./5 days) was used to assess the impact of systemic inflammation on cutaneous microvascular function. Two intradermal microdialysis fibers were placed into the ventral forearm skin of eleven healthy women [Mean (SEM): 34 (2) yrs]. Laser-Doppler flowmetry was used to measure cutaneous blood flow while increasing concentrations of acetylcholine (10−10 to 10−1 M; endothelium-dependent vasodilator) were perfused with a control (lactated Ringer’s) or a NO synthase inhibitor (15 mM NG-nitro-L-arginine methyl ester). Following the dose-response protocol, maximal cutaneous vasodilation was induced by increasing local skin temperature to 43°C and perfusing 28 mM sodium nitroprusside. Cutaneous vascular conductance (CVC) was calculated as the quotient of red blood cell flux over mean arterial pressure and normalized as a percentage of the site-specific maximum (%CVCmax). The NO-dependent contribution was calculated as the difference between the area under the dose-response curve (AUC) of the control and the NO synthase-inhibited sites. RESULTS: There was an overall main effect of salsalate treatment ( p < 0.001). Both the control and NO synthase-inhibited sites shifted upwards following salsalate treatment (Placebo - Control: 45.78 (8.81)% vs NO synthase inhibited: 33.62 (8.10)%; Salsalate - Control: 56.30 (8.48)% vs NO synthase inhibited: 41.57 (7.85)%; both p < 0.05). There was no change in the NO-dependent contribution between treatments (Placebo: 164.30 (35.40) AU vs Salsalate: 180.30 (51.17) AU; p=0.7028).CONCLUSION: Inhibition of NF-κB activation improved cutaneous microvascular function in reproductive-aged healthy women. This improvement was mediated via non-nitric oxide-dependent mechanisms. Supported by NIH Grant R01 HL161000 (LMA) and Diversity Supplement R01 HL161000-02S2 (VGC). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Novel Insights in TKI Resistance in BCR:: ABL1-Positive B-Cell Acute Lymphoblastic Leukemia Beyond Kinase Domain Mutations

Background and Aim Despite the introduction of tyrosine kinase inhibitors (TKIs), approximately 30% of newly diagnosed pediatric and adult BCR:: ABL1-positive B-cell acute lymphoblastic leukemia (B-ALL) patients experience relapsed or refractory disease (Biondi et al, Lancet Haematology 2018; Bassan et al, Journal of Clinical Oncology 2010). ABL1 kinase domain mutations, hindering TKI binding, explain part of the relapses and are acquired during TKI therapy but are rarely detected in newly diagnosed BCR:: ABL1-positive B-ALL patients (Baer et al, Haematologica 2022). Intrinsic TKI resistance mechanisms in BCR:: ABL1-positive B-ALL present prior to TKI treatment are less well documented. Therefore, we aimed to identify potential biomarkers for TKI sensitivity at diagnosis using primary patient samples and newly generated cell lines made from patient-derived xenografts (PDX cell lines). Patients and Methods Leukemic cells from diagnosis of BCR:: ABL1-positive B-ALL patients without ABL1-kinase domain mutations were used to measure cell survival in an ex vivo co-culture assay after imatinib (1.95-125 μM), dasatinib (1.95-125 nM), or bosutinib (0.016-2 μM) exposure. TKI sensitivity was assessed using the area under the dose-response curve (AUC), with <80 arbitrary units (AU) classified as imatinib-sensitive, 80-120 AU as intermediate, and >120 AU as resistant. Multiplex ligation-dependent probe amplification, whole exome sequencing, and RNA sequencing were performed on diagnostic material if available. ABL1 phosphorylation and expression levels were measured using (phospho)flow cytometry in patient-derived xenografts from diagnostic samples and (PDX) cell lines. Results We determined ex vivo sensitivity to imatinib, dasatinib, and bosutinib in 32 pediatric and 19 adult BCR:: ABL1-positive B-ALL patient samples. We observed a substantial variability in ex vivo imatinib response in pediatric and adult patient samples (median AUC: 98 AU; range: 16 to 281 AU). The sensitivity towards imatinib strongly correlated with the sensitivity towards second-generation TKIs dasatinib and bosutinib (rho = 0.84; p < 0.001 and rho= 0.89; p <0.001). Moreover, imatinib's AUC of samples derived from newly diagnosed patients who relapsed after TKI treatment was higher compared with those derived from patients who did not suffer from a relapse (median AUC 123 vs 84 AU; p = 0.03). We observed that an increase in ex vivo imatinib resistance was correlated with a decreased amount of phosphorylated ABL1 protein (rho=-0.92; p=0.0013) and total ABL1 protein (rho=-0.82; p=0.01) in untreated, newly diagnosed samples. Ex vivo exposure to imatinib reduced the ABL1 phosphorylation levels in both sensitive and resistant samples but resistant cells exhibited lower levels of (p)ABL1 protein, indicating reduced dependence on BCR-ABL1 signaling. The ex vivo imatinib resistance in samples carrying deletions in B-cell development genes IKZF1 and/or PAX5 was higher than in samples without these deletions (median AUC: 122 versus 80 AU; p=0.01). In addition, one imatinib-resistant patient had a p.His1038Arg mutation in ZEB2, which is recurrent in B-ALL and this gene has also been described as B-cell development gene (Studd et al, Blood Cancer Journal 2021). Interestingly, another resistant patient had a mutation in SETD2,a gene previously associated with ex vivo TKI resistance in chronic myeloid leukemia cell lines (Sheng et al, Cell Proliferation 2019). Other secondary lesions included SH2B3 inactivation lesions and CRLF2 rearrangements. These lesions were present in intermediately sensitive and resistant BCR:: ABL1-positive samples and are expected to lead to increased JAK/STAT signaling, potentially serving as a resistance mechanism for TKI. Conclusion Our study revealed that the amount of total and phosphorylated ABL1 protein was correlated with ex vivo TKI sensitivity. Newly diagnosed TKI-resistant BCR:: ABL1 samples were further characterized by somatic lesions in B-cell development genes including IKZF1. These results link the known poor prognostic value of IKZF1 deletions in BCR:: ABL1-positive B-ALL patients (van der Veer et al. Blood 2014; Fedullo et al, Haematologica 2019) with intrinsic mechanisms of TKI resistance other than tyrosine kinase domain mutations.

A Methodological Framework to Discover Pharmacogenomic Interactions Based on Random Forests.

The identification of genomic alterations in tumor tissues, including somatic mutations, deletions, and gene amplifications, produces large amounts of data, which can be correlated with a diversity of therapeutic responses. We aimed to provide a methodological framework to discover pharmacogenomic interactions based on Random Forests. We matched two databases from the Cancer Cell Line Encyclopaedia (CCLE) project, and the Genomics of Drug Sensitivity in Cancer (GDSC) project. For a total of 648 shared cell lines, we considered 48,270 gene alterations from CCLE as input features and the area under the dose-response curve (AUC) for 265 drugs from GDSC as the outcomes. A three-step reduction to 501 alterations was performed, selecting known driver genes and excluding very frequent/infrequent alterations and redundant ones. For each model, we used the concordance correlation coefficient (CCC) for assessing the predictive performance, and permutation importance for assessing the contribution of each alteration. In a reasonable computational time (56 min), we identified 12 compounds whose response was at least fairly sensitive (CCC > 20) to the alteration profiles. Some diversities were found in the sets of influential alterations, providing clues to discover significant drug-gene interactions. The proposed methodological framework can be helpful for mining pharmacogenomic interactions.

Human Lung Adenocarcinoma-Derived Organoid Models for Drug Screening

SummaryLung cancer is an extremely heterogeneous disease, and its treatment remains one of the most challenging tasks in medicine. Few existing laboratory lung cancer models can faithfully recapitulate the diversity of the disease and predict therapy response. Here, we establish 12 patient-derived organoids from the most common lung cancer subtype, lung adenocarcinoma (LADC). Extensive gene and histopathology profiling show that the tumor organoids retain the histological architectures, genomic landscapes, and gene expression profiles of their parental tumors. Patient-derived lung cancer organoids are amenable for biomarker identification and high-throughput drug screening in vitro. This study should enable the generation of patient-derived lung cancer organoid lines, which can be used to further the understanding of lung cancer pathophysiology and to assess drug response in personalized medicine.

Abstract 36: Virtual screening with deep learning using cancer cell line dose-response data

Abstract Current high-throughput ligand and structural virtual screening methods typically rely on the identification of a specific functional target for the screen; however, the relationship between cancer genetic phenotype and the specific functional target is not fully understood at the onset of drug development. Cancer cell line (CCL) screening panels are continually used to study the relationship between cellular genetic and ligand structure. We propose combining the speed of machine learning-based virtual screening techniques with the greater than four million in vitro cancer cell line data points generated from the NCI-60, GDSC, and CTRP cancer cell line screens. Using deep neural networks, we train a regression neural network on an integrated dataset of CCL to predict area under the dose-response curve (AUC). Molecules are characterized using the Mordred descriptor package and with a message-passing network on the structure of the molecule, and cell lines are represented by LINCS100 RNA-seq and SNP quantification data. We present two validation styles using our model on random unseen training drugs and by unseen scaffolds. On unseen drugs, the enrichment factor is 42% for the top 1% predictions and BEDROC score is 0.25, based on binning active compounds as the bottom 2% of the overall AUC distribution from the NCI-60. Using the model as a screening tool in inference mode, we scored 1 million compounds from Enamine REAL lead-like compounds on all NCI60 and CCLE cell lines, though the entire screening results will be forthcoming (>450M compounds screened). Initial results show compounds screened by the model have a higher rate of bioactivity just based on the PubChem listings. We verify the robustness of the virtual screen by presenting common functional groups across highly scored drugs and finding stability across small perturbations both to the featurization and molecular structure. For molecules listed in PubChem, the top 10% of predicted compounds had 10x the bioactivity ranking than the bottom 10% of predictions from our model. We present a new high-throughput method for cancer drug virtual screening using CCL dose response. Our method utilizes aggregated data from in vitro CCL panels to train the dose-response model and is a multiclass model across all common CCLs. While we believe this technique is valuable for the community as a tool for integrating experimental cancer cell line data into existing virtual screening infrastructure, we acknowledge verification with in vitro testing outside the model validation data needs to be addressed in future work. Citation Format: Austin Clyde, Arvind Ramanathan, Rick Stevens. Virtual screening with deep learning using cancer cell line dose-response data [abstract]. In: Proceedings of the AACR Special Conference on Advancing Precision Medicine Drug Development: Incorporation of Real-World Data and Other Novel Strategies; Jan 9-12, 2020; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(12_Suppl_1):Abstract nr 36.

High-Throughput Functional Drug Screening and Genomic Analysis to Guide Individualized Therapy for Relapsed/Refractory Multiple Myeloma

Background: The response to treatment for patients with relapsed/refractory multiple myeloma (MM) is highly variable. This may in part be related to the broad genomic heterogeneity that has been reported across individual patients. We hypothesize that in vitro functional drug screening and correlated genomic analyses of patient tumor cells is feasible and may improve clinical treatment response. To address this, we developed a custom high-throughput drug sensitivity (HTS) assay enabling simultaneous testing of 170 chemotherapy drugs and targeted inhibitors, as well as correlative gene expression and mutational analysis by next-generation sequencing. We report on the feasibility of this approach in a clinical trial enrolling patients with relapsed/refractory MM (NCT03389347). Patients and Methods: Twenty patients with relapsed/refractory MM or secondary plasma cell leukemia were enrolled in the study and 15 (9 female, 6 male) had a sufficient number of plasma cells for HTS. The average number of prior treatment regimens among the tested patients was 5.8 (range 3-11) and all had previously received a proteasome inhibitor and immunomodulatory drug and 8 had prior autologous stem cell transplants. Nine patients had stage III disease by the Revised International Staging System (R-ISS) and 4 had stage II disease. Eight patients exhibited high-risk cytogenetics, including 4 patients with del(17p), 5 patients with t(4;14), and 2 patients with t(14;16). The sources of plasma cells utilized for the HTS assay included bone marrow aspirate or core biopsies, soft tissue biopsies of plasmacytomas, and blood samples from patients with circulating plasma cells. Additional blood and bone marrow samples were obtained for RNA sequencing, whole-exome sequencing, and targeted sequencing of circulating tumor DNA. The CLIA approved HTS assay was performed at the Quellos HTS Core at the University of Washington using CD138+plasma cells isolated by magnetic bead separation. Tumor cells were tested against a panel of 170 drugs that includes conventional agents and targeted inhibitors, some FDA approved and others investigational. Cell viability was assessed at 72 hours by a luminescent cell viability assay (Cell Titer Glo, Promega) and drug response was determined using the concentration of experimental compound required to achieve 50% in vitro response inhibition (IC50) and area under the dose-response curve (AUC). Results: We report that the HTS assay can be completed in a median of 5 days from sampling (range 4-6 days), establishing feasibility. The mean percentage of bone marrow plasma cells among patients who could be tested was 56% compared to 5% for patients who had insufficient cells. We observed heterogeneity in patient genomic profiles and in vitro drug responses. The drugs with the highest in vitro response include those commonly used in MM such as bortezomib, ixazomib, carfilzomib, and panobinostat, as well as those under investigation including venetoclax and selinexor. Sensitivity was observed for drugs that have not been investigated for the treatment of MM including alvocidib and omacetaxine. Progression on prior therapy was not consistently predictive of in vitro drug responses and could be a consequence of some myeloma cells retaining sensitivity. Correlative genomic analyses were associated with in vitro drug responses for a subset of compounds. Among the 8 patients who received individualized therapy guided by the assay, 6 had an evaluable response and 5 (83%) achieved effective disease control (stable disease or better). Updated clinical treatment outcomes will be reported at the ASH conference. Conclusions: In this study, we successfully demonstrate the feasibility of a CLIA approved HTS assay capable of delivering actionable results in time to inform individualized treatment decisions for patients with MM. Correlative gene expression and mutational analysis are associated with in vitro drug response. Finally, we demonstrate that some of the patients who received treatment guided by the results of the HTS assay achieved a clinical response. These data suggest that using functional drug screening to predict sensitivity or resistance to both approved and experimental agents warrants further testing. Validation of the HTS assay in a larger population of MM patients holds the potential to improve treatment outcomes. Disclosures Cowan: Cellectar: Consultancy; Janssen: Consultancy, Research Funding; Abbvie: Research Funding; Celgene: Consultancy, Research Funding; Juno: Research Funding; Sanofi: Consultancy. Green:Celgene: Consultancy; Cellectar Biosciences: Research Funding; GSK: Consultancy; Juno Therapeutics: Consultancy, Patents & Royalties, Research Funding; Seattle Genetics: Research Funding. Libby:Alnylam: Consultancy; Abbvie: Consultancy; Pharmacyclics and Janssen: Consultancy; Akcea: Consultancy. Silbermann:Janssen, Sanofi: Other: Consultant/Advisor. Becker:The France Foundation: Honoraria; Accordant Health Services/Caremark: Consultancy; AbbVie, Amgen, Bristol-Myers Squibb, Glycomimetics, Invivoscribe, JW Pharmaceuticals, Novartis, Trovagene: Research Funding. OffLabel Disclosure: We will discuss in-vitro sensitivity testing of drugs that have not been approved for the treatment of multiple myeloma.

Abstract 4732: CDK4/6 inhibition with lerociclib (G1T38) enhances response to PI3K or ERK inhibitors in high-throughput, ex vivo pancreatic PDX screens

Abstract Introduction: In pancreatic ductal adenocarcinoma (PDAC), mutations in KRAS and deletion or promoter methylation of the CDKN2A gene - resulting in deregulation of the p16/CDK4/CDK6/RB axis - each occur in over 90% of cases. Therefore, combination therapy approaches targeting KRAS effectors and CDK4/6 may be a promising treatment strategy in a majority of PDAC patients. Lerociclib (G1T38) is an oral and selective CDK4/6 inhibitor in clinical development as a potential backbone therapy for multiple combination regimens in cancer. Here, we used a powerful and reliable ex vivo drug screening platform, the live tissue sensitivity assay (LTSA), to evaluate the ability of lerociclib to synergize with inhibitors of KRAS effectors across a panel of 24 well-characterized PDAC patient-derived xenografts (PDXs). Methods: PDX tumors were sectioned into uniform tissue slices at 200 µm thickness and arrayed in 96-well plates. For each PDX model, tumor tissue slices were treated with 0.3 µM, 1 µM, and 3 µM of lerociclib, alone and in combination with identical concentrations of a PI3K (pictilisib), mTOR (AZD2014), MEK (trametinib), ERK (ulixertinib), BRAF (vemurafenib) or EGFR (erlotinib) inhibitor for 72 hours. The viabilities of individual tissue slices were measured with PrestoBlue® reagent. A quantitative drug response analysis approach was implemented in which “responder” PDXs were defined as those exhibiting a statistically significant reduction in area under the dose-response curve (AUC) for the combination treatment compared to the most efficacious single agent. Statistical significance was defined as p < 0.05 using Student’s t-test. Results: Treatment of 24 PDAC PDXs using the LTSA revealed a range of sensitivities to each inhibitor as a single agent. When KRAS effectors and CDK4/6 were inhibited in tandem, statistically significant (p < 0.05) enhancements of efficacy were observed when lerociclib was added to pictilisib (21% of PDX models tested), ulixertinib (15%), vemurafenib (10%), erlotinib (5%), trametinib (4%), or AZD2014 (4%). These ex vivo data narrowed the focus of follow-up in vivo work; studies of PDX models in mice treated with lerociclib +/- pictilisib or ulixertinib are ongoing to validate these results. Moreover, differential gene expression and mutational analysis for responders versus non-responders identified through the PDAC PDX LTSA platform are underway, to elucidate molecular factors that predict tumor response or enrich for populations that are sensitive to CDK4/6 and PI3K/ERK inhibitors. Conclusion: The LTSA platform was used to evaluate drug combinations in viable, PDX tumor tissue. We found that lerociclib significantly enhances the response to PI3K or ERK inhibition in a substantial proportion of the tested PDAC PDXs as measured by AUC analysis in the LTSA platform, supporting future clinical evaluation of these combinations. Citation Format: Bingbing Dai, Daniel M. Freed, Jessica A. Sorrentino, Jithesh Jose Augustine, Tara G. Hughes, Ya'an Kang, Patrick J. Roberts, Jason B. Fleming, Michael P. Kim. CDK4/6 inhibition with lerociclib (G1T38) enhances response to PI3K or ERK inhibitors in high-throughput, ex vivo pancreatic PDX screens [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 4732.

Biological evaluation of isoflavonoids from Genista halacsyi using estrogen-target cells: Activities of glucosides compared to aglycones.

The purpose of this study was to evaluate the response of estrogen target cells to a series of isoflavone glucosides and aglycones from Genista halacsyi Heldr. The methanolic extract of aerial parts of this plant was processed using fast centrifugal partition chromatography, resulting in isolation of four archetypal isoflavones (genistein, daidzein, isoprunetin, 8-C-β-D-glucopyranosyl-genistein) and ten derivatives thereof. 7-O-β-D-glucopyranosyl-genistein and 7,4΄-di-O-β-D-glucopyranosyl-genistein were among the most abundant constituents of the isolate. All fourteen, except genistein, displayed low binding affinity for estrogen receptors (ER). Models of binding to ERα could account for the low binding affinity of monoglucosides. Genistein and its glucosides displayed full efficacy in inducing alkaline phosphatase (AlkP) in Ishikawa cells, proliferation of MCF-7 cells and ER-dependent gene expression in reporter cells at low concentrations (around 0.3 μM). ICI182,780 fully antagonized these effects. The AlkP-inducing efficacy of the fourteen isoflavonoids was more strongly correlated with their transcriptional efficacy through ERα. O-monoglucosides displayed higher area under the dose-response curve (AUC) of AlkP response relative to the AUC of ERα-transcriptional response compared to the respective aglycones. In addition, 7-O-β-D-glucopyranosyl-genistein and 7,4΄-di-O-β-D-glucopyranosyl-genistein displayed estradiol-like efficacy in promoting differentiation of MC3T3-E1 cells to osteoblasts, while genistein was not convincingly effective in this respect. Moreover, 7,4΄-di-O-β-D-glucopyranosyl-genistein suppressed lipopolysaccharide-induced tumor necrosis factor mRNA expression in RAW 264.7 cells, while 7-O-β-D-glucopyranosyl-genistein was not convincingly effective and genistein was ineffective. However, genistein and its O-glucosides were ineffective in inhibiting differentiation of RAW 264.7 cells to osteoclasts and in protecting glutamate-challenged HT22 hippocampal neurons from oxidative stress-induced cell death. These findings suggest that 7-O-β-D-glucopyranosyl-genistein and 7,4΄-di-O-β-D-glucopyranosyl-genistein display higher estrogen-like and/or anti-inflammatory activity compared to the aglycone. The possibility of using preparations rich in O-β-D-glucopyranosides of genistein to substitute for low-dose estrogen in formulations for menopausal symptoms is discussed.

Comparative Analysis of Independent Ex Vivo functional Drug Screens Identifies Predictive Biomarkers of BCL-2 Inhibitor Response in AML

Introduction:Therapeutic options for patients with AML were recently expanded with FDA approval of four drugs in 2017. As their efficacy is limited in some patient subpopulations and relapse ultimately ensues, there remains an urgent need for additional treatment options tailored to well-defined patient subpopulations to achieve durable responses. Two comprehensive profiling efforts were launched to address this need-the multi-center Beat AML initiative, led by the Oregon Health & Science University (OHSU) and the AML Individualized Systems Medicine program at the Institute for Molecular Medicine Finland (FIMM).Methods:We performed a comparative analysis of the two large-scale data sets in which patient samples were subjected to whole-exome sequencing, RNA-seq, and ex vivo functional drug sensitivity screens: OHSU (121 patients and 160 drugs) and FIMM (39 patients and 480 drugs). We predicted ex vivo drug response [quantified as area under the dose-response curve (AUC)] using gene expression signatures selected with standard regression and a novel Bayesian model designed to analyze multiple data sets simultaneously. We restricted analysis to the 95 drugs in common between the two data sets.Results:The ex vivo responses (AUCs) of most drugs were positively correlated (OHSU: median Pearson correlation r across all pairwise drug comparisons=0.27; FIMM: median r=0.33). Consistently, a samples's ex vivo response to an individual drug was often correlated with the patient's Average ex vivo Drug Sensitivity (ADS), i.e., the average response across the 95 drugs (OHSU: median r across 95 drugs=0.41; FIMM: median r=0.58). Patients with a complete response to standard induction therapy had a higher ADS than those that were refractory (p=0.01). Further, patients whose ADS was in the top quartile had improved overall survival relative to those having an ADS in the bottom quartile (p<0.05). Standard regression models (LASSO and Ridge) trained on ADS and gene expression in the OHSU data set had improved ex vivo response prediction performance as assessed in the independent FIMM validation data set relative to those trained on gene expression alone (LASSO: p=2.9x10-4; Ridge: p=4.4x10-3). Overall, ex vivo drug response was relatively well predicted (LASSO: mean r across 95 drugs=0.62; Ridge: mean r=0.62).The BCL-2 inhibitor venetoclax was the only drug whose response was negatively correlated with ADS in both data sets. We hypothesized that, whereas the predictive performance of many other drugs was likely dependent on ADS, the predictive performance of venetoclax (LASSO: r=0.53, p=0.01; Ridge: r=0.63, p=1.3x10-3) reflected specific gene expression biomarkers. To identify biomarkers associated with venetoclax sensitivity, we developed an integrative Bayesian machine learning method that jointly modeled both data sets, revealing several candidate biomarkers positively (BCL2 and FLT3) or negatively (CD14, MAFB, and LRP1) correlated with venetoclax response. We assessed these biomarkers in an independent data set that profiled ex vivo response to the BCL-2/BCL-XL inhibitor navitoclax in 29 AML patients (Lee et al.). All five biomarkers were validated in the Lee data set (Fig 1).Conclusions:The two independent ex vivo functional screens were highly concordant, demonstrating the reproducibility of the assays and the opportunity for their use in the clinic. Joint analysis of the two data sets robustly identified biomarkers of drug response for BCL-2 inhibitors. Two of these biomarkers, BCL2 and the previously-reported CD14, serve as positive controls credentialing our approach. CD14, MAFB, and LRP1 are involved in monocyte differentiation. The inverse correlation of their expression with venetoclax and navitoclax response is consistent with prior reports showing that monocytic cells are resistant to BCL-2 inhibition (Kuusanmäki et al.). These biomarker panels may enable better selection of patient populations likely to respond to BCL-2 inhibition than would any one biomarker in isolation.

Multiparametric Analysis of Oncology Drug Screening with Aqueous Two-Phase Tumor Spheroids.

Spheroids present a biologically relevant three-dimensional model of avascular tumors and a unique tool for discovery of anticancer drugs. Despite being used in research laboratories for several decades, spheroids are not routinely used in the mainstream drug discovery pipeline primarily due to the difficulty of mass-producing uniformly sized spheroids and intense labor involved in handling, drug treatment, and analyzing spheroids. We overcome this barrier using a polymeric aqueous two-phase microtechnology to robotically microprint spheroids of well-defined size in standard 384-microwell plates. We use different cancer cells and show that resulting spheroids grow over time and display characteristic features of solid tumors. We demonstrate the feasibility of robotic, high-throughput screening of 25 standard chemotherapeutics and molecular inhibitors against tumor spheroids of three different cancer cell lines. This screening uses over 7000 spheroids to elicit high quality dose-dependent drug responses from spheroids. To quantitatively compare performance of different drugs, we employ a multiparametric scoring system using half-maximum inhibitory concentration (IC50), maximum inhibition (Emax), and area under the dose-response curve (AUC) to take into account both potency and efficacy parameters. This approach allows us to identify several compounds that effectively inhibit growth of spheroids and compromise cellular viability, and distinguish them from moderately effective and ineffective drugs. Using protein expression analysis, we demonstrate that spheroids generated with the aqueous two-phase microtechnology reliably resolve molecular targets of drug compounds. Incorporating this low-cost and convenient-to-use tumor spheroid technology in preclinical drug discovery will make compound screening with realistic tumor models a routine laboratory technique prior to expensive and tedious animal tests to dramatically improve testing throughput and efficiency and reduce costs of drug discovery.

Microprinted tumor spheroids enable anti-cancer drug screening.

Spheroids present a biologically relevant model of avascular tumors and a unique tool for discovery of anti-cancer drugs. Despite being used in research laboratories for several decades, spheroids are not routinely used for drug discovery primarily due to the difficulty of mass-producing uniformly-sized spheroids and intense labor involved in handling, drug treatment, and analyzing them. We overcome this barrier using a novel technology to robotically microprint spheroids in standard 384-well plates. An aqueous drop containing cancer cells is dispensed into a bath of a second, immiscible aqueous phase. The drop maintains cells in close proximity to aggregate into a single spheroid. Using U-87 MG brain cancer cells, we show that this approach produces spheroids of well-defined size with ~10% deviation from their mean diameter. We demonstrate the feasibility of robotic, high throughput compound screening against tumor spheroids using a collection of 25 standard chemotherapeutics and molecular inhibitors against U-87 MG spheroids. Each drug is used in a wide range of concentrations. Viability of cancer cells in drug-treated spheroids is measured using a PrestoBlue assay. Morphological changes are used as a secondary measure for analysis of drug effect. We identify several compounds that effectively inhibit growth of spheroids. To generate a scoring system for effectiveness of drugs, we use half-maximum inhibitory concentration (IC50), maximum inhibition (Emax), and area under the dose-response curve (AUC) to present a multi-parametric approach that takes into account both potency and efficacy of drugs. Our robotic technology offers a low cost and convenient platform for screening large collections of chemical compounds against realistic tumor models prior to expensive and tedious in vivo tests, dramatically improving testing throughput and efficiency, and reducing costs.

Abstract 616: High throughput robotic drug screening against microprinted tumor spheroids

Abstract Cancer cell spheroids present a biologically relevant model of avascular tumors and a unique tool for anti-cancer drug discovery. Despite being used in research laboratories for several decades, spheroids are not routinely used in the mainstream drug discovery pipeline primarily due to the difficulty of mass-producing uniformly sized spheroids and intense labor involved in handling, drug treatment, and analyzing of spheroids. We overcome this barrier using a novel technology to robotically microprint spheroids in standard 384-microwell plates. An aqueous drop containing cancer cells is dispensed into a bath of a second, immiscible aqueous phase to allow generation of a single spheroid. Using several cancer cells, we establish that this approach results in spheroids of well-defined size with less than 8% deviation from the mean diameter in 384-microwell plates. We demonstrate the feasibility of robotic, high throughput compound screening against tumor spheroids using of a collection of 25 standard chemotherapeutics and molecular inhibitors against three different cancer cells, HT-29 colon cancer cells, U-87 MG brain cancer cells, and MDA-MB-157 breast cancer cells. Dose-dependent experiments are done with each drug at a wide range of concentrations. After six days of incubation, viability of cancer cells in drug-treated spheroids is measured using a PrestoBlue assay that we have optimized for three-dimensional cell cultures. Post-treatment morphological changes are used as a secondary measure for analysis. This screening identifies specific MEK inhibitors including Trametinib and Selumetinib that potently inhibit growth of HT-29 spheroids at nanomolar concentrations, whereas several PI3K inhibitors such as pictilisib significantly block proliferation of U-87 MG spheroids at micromolar concentrations. Spheroids of MDA-MB-157 cells show resistance to most of the drugs. We identify few compounds such as a Survivin inhibitor, YM155, and doxorubicin that disintegrate spheroids and induce significant cell death in all three cells. To generate a scoring system, we use half-maximum inhibitory concentration (IC50), maximum inhibition (Emax), and area under the dose-response curve (AUC) to present a multi-parametric approach that takes into account both potency and efficacy parameters for evaluating drug responses in tumor spheroids. In conclusion, our robotic technology offers a low cost and convenient platform for high throughput screening of large collections of chemical compounds against tumor spheroids. Incorporation of this technology in drug discovery applications will make drug testing and screening with realistic tumor models a routine laboratory technique prior to expensive and tedious in vivo analyses, dramatically improving testing throughput and efficiency and reducing costs. Citation Format: Pradip Thakuri, Gary Luker, Hossein Tavana. High throughput robotic drug screening against microprinted tumor spheroids. [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 616.

Accessory Cells From Diverse Tissue Microenvironments Alter Tumor Cell Responses to Multitargeted Kinase Inhibitors: Therapeutic Implications From a Large-Scale Systematic Evaluation.

Abstract 2469 Introduction:Kinases are integral components of diverse signaling cascades which can mediate microenvironment-derived resistance of tumor cells to apoptosis. We thus hypothesized that tumor cell-microenvironment interactions alter the anti-tumor activity of multi-targeted kinase inhibitors and could contibute to discordant efficacy results in conventional preclinical models which do not account for these interactions vs. in clinical studies. Methods:We evaluated 6 multi-targeted kinase inhibitors initially developed to target IGF1R (XL-228), Akt/p70S6K (EXEL-6075), B-/C-RAF(EXEL-0094), CHK1/2 (XL844), met/VEGFR2(EXEL-6323) and JAK2 (XL019). Compounds were tested (0–20 μM, 48 hrs) against luciferase-expressing human multiple myeloma (MM) (n=8), mantle cell lymphoma (n=2) and breast cancer (n=1) cell lines. For each of these treatments, tumor cells were cultured in isolation or co-cultured with immortalized human bone marrow stromal cells (BMSCs, n=2); lung fibroblasts; hepatocytes; or brain astrocytes. Tumor cell viability was quantified by tumor cell compartment-specific bioluminescence imaging (CS-BLI). For each compound and tumor cell line, the area under the dose-response curve (AUC) was calculated as % of the AUC that corresponds to 100% tumor cell viability at all doses, to provide cumulative measure of drug activity across the range of tested drug concentrations. Differences in % AUCs in presence vs. absence of accessory cells were compared by 2-tailed paired t-test. The average value and skewness of distribution for log(10)IC50 of enzymatic activity for each kinase and inhibitor tested were calculated for quantitative comparison of multi-targeted nature of these compounds. Results:Co-culture of most tumor cell lines with accessory cells triggered resistance for 5 of 6 compounds tested, as evidenced by statistically significant (p<0.001 for all tests) increases in %AUC with vs. without co-culture with accessory cells (average %AUC differences of 4.7%, 23.4%, 6.2%, 9.7% and 10.8% for IGF1R, Akt/p70S6K, B-/C-RAF, CHK1/2; and met/VEGFR2 inhibitors, respectively, with corresponding 95% C.I. of 2.0–7.5%, 18.2–28.6%, 2.0–10.4%, 5.3–14.1%, and 3.9–17.6%). In contrast, co-culture with accessory cells increased the response of most tumor cell lines to JAK2 inhibitor (average AUC decrease of 13.8%, 95%CI 1.9–16.4, p<0.001). Results were consistent and statistically significant when analysis was restricted to MM cell lines only. For some inhibitors, heterogeneous responses of different tumor cells to accessory cells were noted. For example, for met/VEGFR2 and CHK1/2 inhibitors, 58.0% (40/69) and 60.0% (36/60) of experimental conditions, respectively, showed co-culture-induced resistance, while 31.9% (22/69) and 18.0% (11/60) of cocultures, respectively, showed sensitization to these inhibitors. High frequency of sensitization was observed in co-cultures of a bortezomib/Dex-resistant subline of MM1S cells treated with met/VEGFR2 inhibitor (63.6%, 7/11 of co-cultures tested), and in co-cultures with BMSCs treated with CHK1/2 inhibitor (29.6% of co-cultures tested). The degree of sensitization or resistance by accessory cells (%AUC difference with vs. without co-culture) did not correlate with quantitative measures of multi-targeted nature for each inhibitor. Conclusions:Accessory cells from different tissues significantly modulated tumor cell responses to diverse multi-targeted kinase inhibitors. Co-cultures enhanced the anti-tumor activity of JAK2 inhibitor, but decreased the activity of the other compounds tested. These different responses did not correlate with how multitargeted each inhibitor was. The sensitization to the JAK inhibitor may specifically reflect increased dependency on JAK signaling for tumor cells when they interact with accessory cells. Accessory cell-induced resistance to some kinase inhibitors (e.g. IGF1R, Akt, CHK1–2) may account for observed differences in their preclinical vs. clinical efficacy. These results provide a rationale for preclinical testing of compounds against large panels of tumor cell lines and clinically-relevant accessory cell types to help develop therapeutics against tumors localized in specific tissue microenvironmental niches. Disclosures:McMillin:Axios Biosciences: Equity Ownership. Mitsiades:Millennium Pharmaceuticals: Honoraria; Celgene: Honoraria; Novartis Pharmaceuticals: Honoraria; Bristol-Myers Squibb: Honoraria; Merck &Co.: Honoraria; Centocor: Honoraria; Arno Therapeutics: Honoraria; Amgen: Research Funding; AVEO Pharma: Research Funding; OSI: Research Funding; EMD Serono: Research Funding; Sunesis: Research Funding; Johnson & Johnson: Research Funding; PharmaMar: Licensing royalties Other; Axios Biosciences: Uncompensated Role as advisor, Uncompensated Role as advisor Other.

Comparing Statistical Methods for Quantifying Drug Sensitivity Based onIn VitroDose–Response Assays

In vitro chemosensitivity assays are invaluable for assessing chemotherapeutic agents' effects on cancer cells. Yet the dose-response curves generated by those assays, usually approximated by four-parameter logistic (4PL) models, are oftentimes difficult to interpret, with no clear indication of which metric should be used to compare them. Here, five commonly used metrics, absolute and relative half-maximal inhibitory concentration (IC(50)), area under the dose-response curve (AUC) based on trapezoidal rule and a parametric approach, and the effect at the maximal concentrations (E(max)), were compared in both simulations and real-life scenarios to evaluate their use with 4PL curves. Despite the fact that IC(50) is the most widely used metric to analyze dose-response curves, this study demonstrated that it was not the most reliable of the metrics tested. Fitted AUC showed the best overall performance in both the simulation and real-life scenarios; trapezoidal AUC showed similar performance to fitted AUC in most cases.

Abstract 4114: Evaluation of ERCC1 expression and in vitro drug response to cisplatin based on human NSCLC cell lines and primary cultures of human lung cancers

Abstract Introduction: In vitro experimentation has been suggested as a rapid tool for identifying and evaluating biomarkers associated with drug response. Excision repair cross-complementation 1 (ERCC1) enzyme plays a rate-limiting role in the nucleotide excision repair pathway and its up regulation has been associated with resistance to platinum agents. Recent studies have suggested that low expression levels of ERCC1 are related to a better survival benefit from cisplatin-based chemotherapy among patients with advanced non-small cell lung carcinoma (NSCLC). This study evaluates the relationship between ERCC1 expression and in vitro drug response to cisplatin using an in vitro chemoresponse assay, ChemoFx® Drug Response Marker (DRM), in human NSCLC cell lines and primary cultures of human lung cancers. Methods: The ChemoFx® DRM was performed on 13 immortalized human NSCLC cell lines (NCI-H520, HOP_92, HOP-62, A549, Calu-3, HCC827, OK, NCI-H460, NCI-H596, NCI-H1666, EKVX, NCI-H358, and NCI-H1975) and 30 primary cultures established from de-identified lung cancer surgical specimens. Cells were treated with a 10-dose range of cisplatin for 72 hours before DAPI-nuclear staining and counting. Response Index scores (RI scores), which are derived from an area under the dose-response curve (AUC), were calculated on the resulting dose-response curves. Protein expression of ERCC1 was evaluated with In-Cell Western analysis. Pearson correlation coefficient was used to show the association between ERCC1 expression and in vitro drug response. Result: Increased ERCC1 expression was significantly associated with cisplatin resistance in the 13 immortalized NSCLC cell lines (r=−0.72, p=0.004). A similar trend was observed across 30 primary cultures of human lung cancers, but the association did not reach the level of significance (r=−0.22, p=0.24). Conclusion: Clinical observation of a negative correlation between ERCC1 expression level and improved survival benefit from cisplatin-based chemotherapy was mirrored by in vitro ChemoFx® DRM analysis with strong correlation in immortalized human NSCLC cell lines and in primary cultures from human lung cancers with a correlation trend. This result suggests the value of in vitro chemoresponse assay in identification and evaluation of biomarkers and their association with chemotherapeutic response. The less significant correlation in human lung cancer primary cultures indicated that ERCC1 alone may not be sufficient for clinical prediction of response in human lung cancers across different pathological subtypes and stages, and additional biomarkers may be involved. These results suggest the value of in vitro chemo response assay, in helping to determine cisplatin response in human lung cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4114. doi:10.1158/1538-7445.AM2011-4114

Abstract 118: Analysis of biological pathways associated with epirubicin and/or cyclophosphamide response by pathway enrichment analysis in human breast cancers

Abstract Recently, a number of different approaches for improving cancer treatment have been developed. One scientific approach is to understand the biochemical pathways and coding genes involved in cancer causation, while other approaches look to distinguish the biochemical pathways involved in drug response. Many chemotherapeutic drugs have been developed targeting different cellular properties, and even more targeted therapies impacting specific oncogenic pathways are on the horizon. Pathways implicated in drug response have been studied to determine why some tumors might respond to a given chemotherapy while others do not. Understanding these pathways may provide potential for improving therapeutic efficacy. Pathway analysis methods have been proposed to discover pathways of interests using gene expression profiling. In this study, the biological pathways associated with response to Epirubicin (E), Cyclophosphamide (C) or the combination of the two drugs (combo EC) were evaluated in both breast cancer cell lines and patients. Thirty immortalized breast cancer cell lines were evaluated for response to these drugs using ChemoFx®. Area under the dose-response curve (AUC) was calculated to measure the chemosensitivity. We applied pathway enrichment to detect specific biochemical pathways associated with these drugs based on biological pathway databases (Kyoto Encyclopedia of Genes and Biocarta), breast cancer cell lines’ drug responses and public microarray data. Comparison of pathways associated with single drug E, C, and combo EC revealed that there are pathways associated with drug combination but not significantly associated with single drugs. These drug response-associated pathways offer great potential for new biomarker identification and drug targeting discovery. In addition, EC associated pathways in breast cancer patients were identified using public microarray data and the associated patient clinical outcomes. Of importance, four biological pathways related to adherens junction, leukocyte transendothelial migration, regulation of actin cytoskeleton and ribosomal protein were identified as EC response-associated pathways in both breast cancer cell lines and patients. These common EC response-associated pathways indicate the potential possibility to use cell line in vitro drug responses to predict patient chemotherapy outcomes. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 118.

Vitamin C improves endothelial function in healthy estrogen-deficient postmenopausal women

Objective: Estrogen deficiency is associated with increased cardiovascular risk and endothelial dysfunction. Improvements in endothelial function with antioxidants, including vitamin C, have been reported. We aimed to determine the acute effect of vitamin C on endothelial function in healthy women with established menopause. Subjects: Subjects (aged 47-59 years) were at least 1 year postmenopause. Ten (serum estradiol < 50 pmol/l) were not receiving hormone replacement therapy, while eight hysterectomized subjects received subcutaneous estradiol. Design: Forearm blood flow (FBF; strain-gauge plethysmography) responses to intrabrachial artery infusions of incremental doses of acetylcholine (endothelium-dependent vasodilation) and sodium nitroprusside (endothelium-independent vasodilation) were determined at baseline, and following 1.5 g vitamin C given intravenously. Results: At baseline, estrogen-treated subjects had a lower index of insulin resistance (homeostasis model assessment, HOMA) and lower fibrinogen than those of estrogendeficient subjects. There was a trend towards higher baseline FBF and larger baseline FBF response to acetylcholine in estrogen-treated subjects. FBF responses to acetylcholine were significantly enhanced after vitamin C in estrogen-deficient subjects (area under the dose-response curve (AUC): estrogen-deficient 9.9 ± 2.6 vs. 15.1 ± 3.2 (mean ± SEM), p = 0.02; estrogen-treated 17.0 ± 2.9 vs. 21.0 ± 3.2, p = 0.07). Resting FBF and response to sodium nitroprusside were unchanged in either group by vitamin C. Plasminogen activator inhibitor-1 levels fell after vitamin C in the estrogen-deficient group (17.0 ± 1.6 vs. 14.7 ± 0.9 IU/ml, p = 0.03). Conclusions: These results indicate that endothelial function may be improved acutely by antioxidant treatment in postmenopausal women with established estrogen deficiency.

Vitamin C improves endothelial function in healthy estrogen-deficient postmenopausal women

Objective: Estrogen deficiency is associated with increased cardiovascular risk and endothelial dysfunction. Improvements in endothelial function with antioxidants, including vitamin C, have beenreported. We aimed to determine the acute effect of vitamin C on endothelial function in healthy women with established menopause.Subjects: Subjects (aged 47-59 years) were at least 1 year postmenopause.Ten (serum estradiol < 50 pmol/l) were not receiving hormone replacement therapy, while eight hysterectomized subjects received subcutaneous estradiol.Design: Forearm blood flow (FBF; strain-gaugeplethysmography) responses to intrabrachial artery infusions of incremental doses of acetylcholine (endothelium-dependent vasodilation) and sodium nitroprusside (endothelium-independent vasodilation) weredetermined at baseline, and following 1.5 g vitamin C given intravenously.Results: At baseline, estrogen-treated subjects had a lower index of insulin resistance (homeostasis model assessment,HOMA) and lower fibrinogen than those of estrogendeficient subjects. There was a trend towards higher baseline FBF and larger baseline FBF response to acetylcholine in estrogen-treated subjects. FBF responsesto acetylcholine were significantly enhanced after vitamin C in estrogen-deficient subjects (area under the dose-response curve (AUC): estrogen-deficient 9.9 ± 2.6 vs. 15.1 ± 3.2 (mean ±SEM), p = 0.02; estrogen-treated 17.0 ± 2.9 vs. 21.0 ± 3.2, p = 0.07). Resting FBF and response to sodium nitroprusside were unchanged in either group by vitamin C. Plasminogenactivator inhibitor-1 levels fell after vitamin C in the estrogen-deficient group (17.0 ± 1.6 vs. 14.7 ± 0.9 IU/ml, p = 0.03).Conclusions: These results indicate that endothelialfunction may be improved acutely by antioxidant treatment in postmenopausal women with established estrogen deficiency.