Plasma biomarkers associated with adverse outcomes in patients with calcific aortic stenosis.

AIMS: Enhanced risk stratification of patients with aortic stenosis (AS) is necessary to identify patients at high risk for adverse outcomes, and may allow for better management of patient subgroups at high risk of myocardial damage. The objective of this study was to identify plasma biomarkers and multimarker profiles associated with adverse outcomes in AS. METHODS AND RESULTS: We studied 708 patients with calcific AS and measured 49 biomarkers using a Luminex platform. We studied the correlation between biomarkers and the risk of (i) death and (ii) death or heart failure-related hospital admission (DHFA). We also utilized machine-learning methods (a tree-based pipeline optimizer platform) to develop multimarker models associated with the risk of death and DHFA. In this cohort with a median follow-up of 2.8 years, multiple biomarkers were significantly predictive of death in analyses adjusted for clinical confounders, including tumour necrosis factor (TNF)-α [hazard ratio (HR) 1.28, P < 0.0001], TNF receptor 1 (TNFRSF1A; HR 1.38, P < 0.0001), fibroblast growth factor (FGF)-23 (HR 1.22, P < 0.0001), N-terminal pro B-type natriuretic peptide (NT-proBNP) (HR 1.58, P < 0.0001), matrix metalloproteinase-7 (HR 1.24, P = 0.0002), syndecan-1 (HR 1.27, P = 0.0002), suppression of tumorigenicity-2 (ST2) (IL1RL1; HR 1.22, P = 0.0002), interleukin (IL)-8 (CXCL8; HR 1.22, P = 0.0005), pentraxin (PTX)-3 (HR 1.17, P = 0.001), neutrophil gelatinase-associated lipocalin (LCN2; HR 1.18, P < 0.0001), osteoprotegerin (OPG) (TNFRSF11B; HR 1.26, P = 0.0002), and endostatin (COL18A1; HR 1.28, P = 0.0012). Several biomarkers were also significantly predictive of DHFA in adjusted analyses including FGF-23 (HR 1.36, P < 0.0001), TNF-α (HR 1.26, P < 0.0001), TNFR1 (HR 1.34, P < 0.0001), angiopoietin-2 (HR 1.26, P < 0.0001), syndecan-1 (HR 1.23, P = 0.0006), ST2 (HR 1.27, P < 0.0001), IL-8 (HR 1.18, P = 0.0009), PTX-3 (HR 1.18, P = 0.0002), OPG (HR 1.20, P = 0.0013), and NT-proBNP (HR 1.63, P < 0.0001). Machine-learning multimarker models were strongly associated with adverse outcomes (mean 1-year probability of death of 0%, 2%, and 60%; mean 1-year probability of DHFA of 0%, 4%, 97%; P < 0.0001). In these models, IL-6 (a biomarker of inflammation) and FGF-23 (a biomarker of calcification) emerged as the biomarkers of highest importance. CONCLUSIONS: Plasma biomarkers are strongly associated with the risk of adverse outcomes in patients with AS. Biomarkers of inflammation and calcification were most strongly related to prognosis.

Discovery and Optimization of 2H-1λ2-Pyridin-2-one Inhibitors of Mutant Isocitrate Dehydrogenase 1 for the Treatment of Cancer.

Neomorphic mutations in isocitrate dehydrogenase 1 (IDH1) are oncogenic for a number of malignancies, primarily low-grade gliomas and acute myeloid leukemia. We report a medicinal chemistry campaign around a 7,7-dimethyl-7,8-dihydro-2H-1λ2-quinoline-2,5(6H)-dione screening hit against the R132H and R132C mutant forms of isocitrate dehydrogenase (IDH1). Systematic SAR efforts produced a series of potent pyrid-2-one mIDH1 inhibitors, including the atropisomer (+)-119 (NCATS-SM5637, NSC 791985). In an engineered mIDH1-U87-xenograft mouse model, after a single oral dose of 30 mg/kg, 16 h post dose, between 16 and 48 h, (+)-119 showed higher tumoral concentrations that corresponded to lower 2-HG concentrations, when compared with the approved drug AG-120 (ivosidenib).

Substituted diaryl ether compounds as retinoic acid-related orphan Receptor-γt (RORγt) agonists.

The discovery of a series of substituted diarylether compounds as retinoic acid related orphan receptor γt (RORγt) agonists is described. Compound 1 was identified from deck mining as a RORγt agonist. Hit-to-lead optimization led to the identification of lead compound 5, which possesses improved potency (10x). Extensive SAR exploration led to the identification of a potent and selective compound 22, that demonstrated an improved pharmacokinetic profile and a dose-dependent pharmacodynamic response. However, when dosed in a MC38 syngeneic tumor model, no evidence of efficacy was observed. ©2020 Elsevier Science Ltd. All rights reserved.

Plasma Tenascin-C: a prognostic biomarker in heart failure with preserved ejection fraction.

INTRODUCTION: Tenascin-C is a marker of interstitial fibrosis. We assessed whether plasma Tenascin-C differed between heart failure with preserved ejection fraction (HFpEF) and asymptomatic controls and related to clinical outcomes. MATERIALS AND METHODS: Prospective, observational study of 172 age- and sex-matched subjects (HFpEF n = 130; controls n = 42, age 73 ± 9, males 50%) who underwent phenotyping with 20 plasma biomarkers, echocardiography, cardiac MRI and 6-minute-walk-testing. The primary endpoint was the composite of all-cause death/HF hospitalisation. RESULTS: Tenascin-C was higher in HFpEF compared to controls (13.7 [10.8-17.3] vs (11.1 [8.9-12.9] ng/ml, p < 0.0001). Tenascin-C correlated positively with markers of clinical severity (NYHA, E/E', BNP) and plasma biomarkers reflecting interstitial fibrosis (ST-2, Galectin-3, GDF-15, TIMP-1, TIMP-4, MMP-2, MMP-3, MMP-7, MMP-8), cardiomyocyte stress (BNP, NTpro-ANP), inflammation (MPO, hs-CRP, TNFR-1, IL6) and renal dysfunction (urea, cystatin-C, NGAL); p < 0.05 for all. During follow-up (median 1428 days), there were 61 composite events (21 deaths, 40 HF hospitalizations). In multivariable Cox regression analysis, Tenascin-C (adjusted hazard ratio [HR] 1.755, 95% confidence interval [CI] 1.305-2.360; p < 0.0001) and indexed extracellular volume (HR 1.465, CI 1.019-2.106; p = 0.039) were independently associated with adverse outcomes. CONCLUSIONS: In HFpEF, plasma Tenascin-C is higher compared to age- and sex-matched controls and a strong predictor of adverse outcomes. Trial registration: ClinicalTrials.gov: NCT03050593.

Substituted benzyloxytricyclic compounds as retinoic acid-related orphan receptor gamma t (RORγt) agonists.

Substituted benzyloxy aryl compound 2 was identified as an RORγt agonist. Structure based drug design efforts resulted in a potent and selective tricyclic compound 19 which, when administered orally in an MC38 mouse tumor model, demonstrated a desired pharmacokinetic profile as well as a dose-dependent pharmacodynamic response. However, no perceptible efficacy was observed in this tumor model at the doses investigated.

Multiplexed ion beam imaging (MIBI) for characterization of the tumor microenvironment across tumor types.

An ability to characterize the cellular composition and spatial organization of the tumor microenvironment (TME) using multiplexed IHC has been limited by the techniques available. Here we show the applicability of multiplexed ion beam imaging (MIBI) for cell phenotype identification and analysis of spatial relationships across numerous tumor types. Formalin-fixed paraffin-embedded (FFPE) samples from tumor biopsies were simultaneously stained with a panel of 15 antibodies, each labeled with a specific metal isotope. Multi-step processing produced images of the TME that were further segmented into single cells. Frequencies of different cell subsets and the distributions of nearest neighbor distances between them were calculated using this data. A total of 50 tumor specimens from 15 tumor types were characterized for their immune profile and spatial organization. Most samples showed infiltrating cytotoxic T cells and macrophages present amongst tumor cells. Spatial analysis of the TME in two ovarian serous carcinoma images highlighted differences in the degree of mixing between tumor and immune cells across samples. Identification of admixed PD-L1+ macrophages and PD-1+ T cells in an urothelial carcinoma sample allowed for the detailed observations of immune cell subset spatial arrangement. These results illustrate the high-parameter capability of MIBI at a sensitivity and resolution uniquely suited to understanding the complex tumor immune landscape including the spatial relationships of immune and tumor cells and expression of immunoregulatory proteins.

Multiple Plasma Biomarkers for Risk Stratification in Patients With Heart Failure and Preserved Ejection Fraction.

BACKGROUND: Better risk stratification strategies are needed to enhance clinical care and trial design in heart failure with preserved ejection fraction (HFpEF). OBJECTIVES: The purpose of this study was to assess the value of a targeted plasma multi-marker approach to enhance our phenotypic characterization and risk prediction in HFpEF. METHODS: In this study, the authors measured 49 plasma biomarkers from TOPCAT (Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist) trial participants (n = 379) using a Multiplex assay. The relationship between biomarkers and the risk of all-cause death or heart failure-related hospital admission (DHFA) was assessed. A tree-based pipeline optimizer platform was used to generate a multimarker predictive model for DHFA. We validated the model in an independent cohort of HFpEF patients enrolled in the PHFS (Penn Heart Failure Study) (n = 156). RESULTS: Two large, tightly related dominant biomarker clusters were found, which included biomarkers of fibrosis/tissue remodeling, inflammation, renal injury/dysfunction, and liver fibrosis. Other clusters were composed of neurohormonal regulators of mineral metabolism, intermediary metabolism, and biomarkers of myocardial injury. Multiple biomarkers predicted incident DHFA, including 2 biomarkers related to mineral metabolism/calcification (fibroblast growth factor-23 and OPG [osteoprotegerin]), 3 inflammatory biomarkers (tumor necrosis factor-alpha, sTNFRI [soluble tumor necrosis factor-receptor I], and interleukin-6), YKL-40 (related to liver injury and inflammation), 2 biomarkers related to intermediary metabolism and adipocyte biology (fatty acid binding protein-4 and growth differentiation factor-15), angiopoietin-2 (related to angiogenesis), matrix metalloproteinase-7 (related to extracellular matrix turnover), ST-2, and N-terminal pro-B-type natriuretic peptide. A machine-learning-derived model using a combination of biomarkers was strongly predictive of the risk of DHFA (standardized hazard ratio: 2.85; 95% confidence interval: 2.03 to 4.02; p < 0.0001) and markedly improved the risk prediction when added to the MAGGIC (Meta-Analysis Global Group in Chronic Heart Failure Risk Score) risk score. In an independent cohort (PHFS), the model strongly predicted the risk of DHFA (standardized hazard ratio: 2.74; 95% confidence interval: 1.93 to 3.90; p < 0.0001), which was also independent of the MAGGIC risk score. CONCLUSIONS: Various novel circulating biomarkers in key pathophysiological domains are predictive of outcomes in HFpEF, and a multimarker approach coupled with machine-learning represents a promising strategy for enhancing risk stratification in HFpEF.

Circulating and tissue matricellular RNA and protein expression in calcific aortic valve disease.

Aortic valve sclerosis is a highly prevalent, poorly characterized asymptomatic manifestation of calcific aortic valve disease and may represent a therapeutic target for disease mitigation. Human aortic valve cusps and blood were obtained from 333 patients undergoing cardiac surgery (n = 236 for severe aortic stenosis, n = 35 for asymptomatic aortic valve sclerosis, n = 62 for no valvular disease), and a multiplex assay was used to evaluate protein expression across the spectrum of calcific aortic valve disease. A subset of six valvular tissue samples (n = 3 for asymptomatic aortic valve sclerosis, n = 3 for severe aortic stenosis) was used to create RNA sequencing profiles, which were subsequently organized into clinically relevant gene modules. RNA sequencing identified 182 protein-encoding, differentially expressed genes in aortic valve sclerosis vs. aortic stenosis; 85% and 89% of expressed genes overlapped in aortic stenosis and aortic valve sclerosis, respectively, which decreased to 55% and 84% when we targeted highly expressed genes. Bioinformatic analyses identified six differentially expressed genes encoding key extracellular matrix regulators: TBHS2, SPARC, COL1A2, COL1A1, SPP1, and CTGF. Differential expression of key circulating biomarkers of extracellular matrix reorganization was observed in control vs. aortic valve sclerosis (osteopontin), control vs. aortic stenosis (osteoprotegerin), and aortic valve sclerosis vs. aortic stenosis groups (MMP-2), which corresponded to valvular mRNA expression. We demonstrate distinct mRNA and protein expression underlying aortic valve sclerosis and aortic stenosis. We anticipate that extracellular matrix regulators can serve as circulating biomarkers of early calcific aortic valve disease and as novel targets for early disease mitigation, pending prospective clinical investigations.

Clinical Phenogroups in Heart Failure With Preserved Ejection Fraction: Detailed Phenotypes, Prognosis, and Response to Spironolactone.

OBJECTIVES: This study sought to assess if clinical phenogroups differ in comprehensive biomarker profiles, cardiac and arterial structure/function, and responses to spironolactone therapy. BACKGROUND: Previous studies identified distinct subgroups (phenogroups) of patients with heart failure with preserved ejection fraction (HFpEF). METHODS: Among TOPCAT (Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist Trial) participants, we performed latent-class analysis to identify HFpEF phenogroups based on standard clinical features and assessed differences in multiple biomarkers measured from frozen plasma; cardiac and arterial structure/function measured with echocardiography and arterial tonometry; prognosis; and response to spironolactone. RESULTS: Three HFpEF phenogroups were identified. Phenogroup 1 (n = 1,214) exhibited younger age, higher prevalence of smoking, preserved functional class, and the least evidence of left ventricular (LV) hypertrophy and arterial stiffness. Phenogroup 2 (n = 1,329) was older, with normotrophic concentric LV remodeling, atrial fibrillation, left atrial enlargement, large-artery stiffening, and biomarkers of innate immunity and vascular calcification. Phenogroup 3 (n = 899) demonstrated more functional impairment, obesity, diabetes, chronic kidney disease, concentric LV hypertrophy, high renin, and biomarkers of tumor necrosis factor-alpha-mediated inflammation, liver fibrosis, and tissue remodeling. Compared with phenogroup 1, phenogroup 3 exhibited the highest risk of the primary endpoint of cardiovascular death, heart failure hospitalization, or aborted cardiac arrest (hazard ratio [HR]: 3.44; 95% confidence interval [CI]: 2.79 to 4.24); phenogroups 2 and 3 demonstrated similar all-cause mortality (phenotype 2 HR: 2.36; 95% CI: 1.89 to 2.95; phenotype 3 HR: 2.26, 95% CI: 1.77 to 2.87). Spironolactone randomized therapy was associated with a more pronounced reduction in the risk of the primary endpoint in phenogroup 3 (HR: 0.75; 95% CI: 0.59 to 0.95; p for interaction = 0.016). Results were similar after excluding participants from Eastern Europe. CONCLUSIONS: We identified important differences in circulating biomarkers, cardiac/arterial characteristics, prognosis, and response to spironolactone across clinical HFpEF phenogroups. These findings suggest distinct underlying mechanisms across clinically identifiable phenogroups of HFpEF that may benefit from different targeted interventions.

Competing risks and cause-specific mortality in patients with pancreatic neuroendocrine tumors.

BACKGROUND AND OBJECTIVE: Currently, there are no competing risk analyses of cause-specific mortality in patients with pancreatic neuroendocrine tumors. MATERIALS AND METHODS: We estimated a cumulative incidence function for cause-specific mortality. The first nomogram for predicting cause-specific mortality was constructed using a proportional subdistribution hazard model, validated using bootstrap cross-validation, and evaluated with decision curve analysis. RESULTS: Sex, age, positive lymph node status, metastasis, surveillance, epidemiology, and end results historic stage, grade, and surgery strongly predicted cause-specific mortality. The discrimination performance of Fine-Gray models was evaluated using the c-index, which was 0.864. In addition, the calibration plot of the developed nomogram demonstrated good concordance between the predicted and actual outcomes. Decision curve analysis yielded a range of threshold probabilities (0.014-0.779) at which the clinical net benefit of the risk model was greater than that in hypothetical all-screening or no-screening scenarios. CONCLUSION: Our nomogram allows selection of a patient population at high risk for cancer-specific mortality and thus facilitates the design of prevention trials for the affected population.

Renal proteomic analysis of RGC-32 knockout mice reveals the potential mechanism of RGC-32 in regulating cell cycle.

This study aimed to investigate the exact function of RGC-32 in kidney diseases and explore the potential mechanism of RGC-32 in regulating cell cycle. RGC-32 knockout (RGC-32-/-) mice were generated from C57BL/6 embryonic stem cells. Differentially expressed proteins in the kidney were investigated with the isobaric tags for relative and absolute quantification (iTRAQ) technique. Gene ontology analyses (GO), Kyoto encyclopedia of genes and genomes (KEGG) pathway mapping analysis and functional network analysis were also performed. The expressions of Smc3, Smad 2-3, DNA-PK were further confirmed by qPCR. Results showed that 4690 proteins were quantified on the basis of 25165 unique peptides. Comparative proteomic analysis revealed 361 differentially expressed proteins in RGC-32-/- mice (knockout/wild ratio >+/- 1.2 and P<0.05). GO and KEGG pathway mapping analyses showed differentially expressed proteins were involved in spliceosome, fluid shear stress and atherosclerosis protein processing in endoplasmic reticulum, pathways in cancer, viral carcinogenesis, epithelial cell signaling in Helicobacter pylori infection, HTLV-I infection, PI3K-Akt signaling pathway, ubiquitin mediated proteolysis, Parkinson's disease, MAPK signaling pathway, carbon metabolism, Alzheimer's disease, NOD-like receptor signaling pathway, tight junction, Proteoglycans in cancer, phagosome, ribosome, mTOR signaling pathway, and AMPK signaling pathway. Differentially expressed proteins Smc3 (0.821), DNA-PK (0.761), Smad 2-3 (0.631) were involved in cell cycle regulation. mRNA expression of Smad2-3, DNA-PK, and Smc3 was consistent with that from iTRAQ. It is concluded that RGC-32 may affect the expression of many proteins (76 up-regulated and 285 down-regulated) in the kidney, and may regulate the expression of Smc3, DNA-PK and Smad 2-3 to affect the cell cycle.

Discovery and optimization of piperazine-1-thiourea-based human phosphoglycerate dehydrogenase inhibitors.

Proliferating cells, including cancer cells, obtain serine both exogenously and via the metabolism of glucose. By catalyzing the first, rate-limiting step in the synthesis of serine from glucose, phosphoglycerate dehydrogenase (PHGDH) controls flux through the biosynthetic pathway for this important amino acid and represents a putative target in oncology. To discover inhibitors of PHGDH, a coupled biochemical assay was developed and optimized to enable high-throughput screening for inhibitors of human PHGDH. Feedback inhibition was minimized by coupling PHGDH activity to two downstream enzymes (PSAT1 and PSPH), providing a marked improvement in enzymatic turnover. Further coupling of NADH to a diaphorase/resazurin system enabled a red-shifted detection readout, minimizing interference due to compound autofluorescence. With this protocol, over 400,000 small molecules were screened for PHGDH inhibition, and following hit validation and triage work, a piperazine-1-thiourea was identified. Following rounds of medicinal chemistry and SAR exploration, two probes (NCT-502 and NCT-503) were identified. These molecules demonstrated improved target activity and encouraging ADME properties, enabling in vitro assessment of the biological importance of PHGDH, and its role in the fate of serine in PHGDH-dependent cancer cells. This manuscript reports the assay development and medicinal chemistry leading to the development of NCT-502 and -503 reported in Pacold et al. (2016).

Small Molecule Inhibition of the Ubiquitin-specific Protease USP2 Accelerates cyclin D1 Degradation and Leads to Cell Cycle Arrest in Colorectal Cancer and Mantle Cell Lymphoma Models.

Deubiquitinases are important components of the protein degradation regulatory network. We report the discovery of ML364, a small molecule inhibitor of the deubiquitinase USP2 and its use to interrogate the biology of USP2 and its putative substrate cyclin D1. ML364 has an IC50 of 1.1 µm in a biochemical assay using an internally quenched fluorescent di-ubiquitin substrate. Direct binding of ML364 to USP2 was demonstrated using microscale thermophoresis. ML364 induced an increase in cellular cyclin D1 degradation and caused cell cycle arrest as shown in Western blottings and flow cytometry assays utilizing both Mino and HCT116 cancer cell lines. ML364, and not the inactive analog 2, was antiproliferative in cancer cell lines. Consistent with the role of cyclin D1 in DNA damage response, ML364 also caused a decrease in homologous recombination-mediated DNA repair. These effects by a small molecule inhibitor support a key role for USP2 as a regulator of cell cycle, DNA repair, and tumor cell growth.

Small Molecule Inhibitor of NRF2 Selectively Intervenes Therapeutic Resistance in KEAP1-Deficient NSCLC Tumors.

Loss of function mutations in Kelch-like ECH Associated Protein 1 (KEAP1), or gain-of-function mutations in nuclear factor erythroid 2-related factor 2 (NRF2), are common in non-small cell lung cancer (NSCLC) and associated with therapeutic resistance. To discover novel NRF2 inhibitors for targeted therapy, we conducted a quantitative high-throughput screen using a diverse set of ∼400 000 small molecules (Molecular Libraries Small Molecule Repository Library, MLSMR) at the National Center for Advancing Translational Sciences. We identified ML385 as a probe molecule that binds to NRF2 and inhibits its downstream target gene expression. Specifically, ML385 binds to Neh1, the Cap 'N' Collar Basic Leucine Zipper (CNC-bZIP) domain of NRF2, and interferes with the binding of the V-Maf Avian Musculoaponeurotic Fibrosarcoma Oncogene Homologue G (MAFG)-NRF2 protein complex to regulatory DNA binding sequences. In clonogenic assays, when used in combination with platinum-based drugs, doxorubicin or taxol, ML385 substantially enhances cytotoxicity in NSCLC cells, as compared to single agents. ML385 shows specificity and selectivity for NSCLC cells with KEAP1 mutation, leading to gain of NRF2 function. In preclinical models of NSCLC with gain of NRF2 function, ML385 in combination with carboplatin showed significant antitumor activity. We demonstrate the discovery and validation of ML385 as a novel and specific NRF2 inhibitor and conclude that targeting NRF2 may represent a promising strategy for the treatment of advanced NSCLC.

A high-content imaging-based screening pipeline for the systematic identification of anti-progeroid compounds.

Hutchinson-Gilford Progeria Syndrome (HGPS) is an early onset lethal premature aging disorder caused by constitutive production of progerin, a mutant form of the nuclear architectural protein lamin A. The presence of progerin causes extensive morphological, epigenetic and DNA damage related nuclear defects that ultimately disrupt tissue and organismal functions. Hypothesis-driven approaches focused on HGPS affected pathways have been used in attempts to identify druggable targets with anti-progeroid effects. Here, we report an unbiased discovery approach to HGPS by implementation of a high-throughput, high-content imaging based screening method that enables systematic identification of small molecules that prevent the formation of multiple progerin-induced aging defects. Screening a library of 2816 FDA approved drugs, we identified retinoids as a novel class of compounds that reverses aging defects in HGPS patient skin fibroblasts. These findings establish a novel approach to anti-progeroid drug discovery.

Torin2 targets dysregulated pathways in anaplastic thyroid cancer and inhibits tumor growth and metastasis.

Anaplastic thyroid cancer (ATC) is rare but it is one of the most lethal human malignancies with no effective therapy. There is a pressing need to identify new therapeutic agents for ATC. We performed quantitative high-throughput screening (qHTS) in ATC cell lines using a compound library of 3,282 drugs. qHTS identified 100 pan-active agents. Enrichment analysis of qHTS data showed drugs targeting mTOR were one of the most active drug categories, and Torin2 showed the highest efficacy. We found mTOR to be upregulated in ATC. Treatment of multiple ATC cell lines with Torin2 showed significant dose-dependent inhibition of cellular proliferation with caspase-dependent apoptosis and G1/S phase arrest. Torin2 inhibited cellular migration and inhibited the phosphorylation of key effectors of the mTOR-pathway (AKT, 4E-BP1 and 70S6K), as well as claspin and survivin expression, regulators of cell cycle and apoptosis. In our in vivo mouse model of metastatic ATC, Torin2 inhibited tumor growth and metastasis and significantly prolonged overall survival. Our findings suggest that Torin2 is a promising agent for ATC therapy and that it effectively targets upregulated pathways in human ATC.

Inhibition of Survivin with YM155 Induces Durable Tumor Response in Anaplastic Thyroid Cancer.

PURPOSE: Anaplastic thyroid cancer (ATC) is a rare but lethal malignancy without any effective therapy. The aim of this study is to use a high-throughput drug library screening to identify a novel therapeutic agent that targets dysregulated genes/pathways in ATC. EXPERIMENTALDESIGN: We performed quantitative high-throughput screening (qHTS) in ATC cell lines using a compound library of 3,282 drugs. Dysregulated genes in ATC were analyzed using genome-wide expression analysis and immunohistochemistry in human ATC tissue samples and ATC cell lines. In vitro and in vivo studies were performed for determining drug activity, effectiveness of targeting, and the mechanism of action. RESULTS: qHTS identified 100 active compounds in three ATC cell lines. One of the most active agents was the first-in-class survivin inhibitor YM155. Genome-wide expression analysis and immunohistochemistry showed overexpression of survivin in human ATC tissue samples, and survivin was highly expressed in all ATC cell lines tested. YM155 significantly inhibited ATC cellular proliferation. Mechanistically, YM155 inhibited survivin expression in ATC cells. Furthermore, YM155 treatment reduced claspin expression, which was associated with S-phase arrest in ATC cells. In vivo, YM155 significantly inhibited growth and metastases and prolonged survival. CONCLUSIONS: Our data show that YM155 is a promising anticancer agent for ATC and that its target, survivin, is overexpressed in ATC. Our findings support the use of YM155 in clinical trials as a therapeutic option in advanced and metastatic ATC.

Dual inhibition of HDAC and EGFR signaling with CUDC-101 induces potent suppression of tumor growth and metastasis in anaplastic thyroid cancer.

Anaplastic thyroid cancer (ATC) is one of the most lethal human malignancies that currently has no effective therapy. We performed quantitative high-throughput screening (qHTS) in three ATC cell lines using 3,282 clinically approved drugs and drug candidates, and identified 100 active agents. Enrichment analysis of active compounds showed that inhibitors of EGFR and histone deacetylase (HDAC) were most active. Of these, the first-in-class dual inhibitor of EGFR, HER2 and HDACs, CUDC-101, had the highest efficacy and lower IC50 than established drugs. We validated that CUDC-101 inhibited cellular proliferation and resulted in cell death by inducing cell cycle arrest and caspase-dependent apoptosis. CUDC-101 also inhibited cellular migration in vitro. Mechanistically, CUDC-101 inhibited MAPK signaling and histone deacetylation in ATC cell lines with multiple driver mutations present in human ATC. The anticancer effect of CUDC-101 was associated with increased expression of p21 and E-cadherin, and reduced expression of survivin, XIAP, ß-catenin, N-cadherin, and Vimentin. In an in vivo mouse model of metastatic ATC, CUDC-101 inhibited tumor growth and metastases, and significantly prolonged survival. Response to CUDC-101 treatment in vivo was associated with increased histone 3 acetylation and reduced survivin expression. Our findings provide a preclinical basis to evaluate CUDC-101 therapy in ATC.

Quantitative high throughput screening using a primary human three-dimensional organotypic culture predicts in vivo efficacy.

The tumour microenvironment contributes to cancer metastasis and drug resistance. However, most high throughput screening (HTS) assays for drug discovery use cancer cells grown in monolayers. Here we show that a multilayered culture containing primary human fibroblasts, mesothelial cells and extracellular matrix can be adapted into a reliable 384- and 1,536-multi-well HTS assay that reproduces the human ovarian cancer (OvCa) metastatic microenvironment. We validate the identified inhibitors in secondary in vitro and in vivo biological assays using three OvCa cell lines: HeyA8, SKOV3ip1 and Tyk-nu. The active compounds directly inhibit at least two of the three OvCa functions: adhesion, invasion and growth. In vivo, these compounds prevent OvCa adhesion, invasion and metastasis, and improve survival in mouse models. Collectively, these data indicate that a complex three-dimensional culture of the tumour microenvironment can be adapted for quantitative HTS and may improve the disease relevance of assays used for drug screening.