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PDF - 60K, Linear correlation observed between tumor growth inhibition (% T/C) or tumor regression and the fraction of time over the in vivo S473P-Akt IC80 in different cancer cell line-derived tumor xenografts implanted in nude mice (represented as dots) and nude rats (represented as triangles) following NVP-BYL719 treatment (R2=0.77, p

Somatic PIK3CA mutations are frequently found in solid tumors, raising the hypothesis that selective inhibition of PI3Kα may have robust efficacy in PIK3CA-mutant cancers while sparing patients the side-effects associated with broader inhibition of the class I phosphoinositide 3-kinase (PI3K) family. Here, we report the biologic properties of the 2-aminothiazole derivative NVP-BYL719, a selective inhibitor of PI3Kα and its most common oncogenic mutant forms. The compound selectivity combined with excellent drug-like properties translates to dose- and time-dependent inhibition of PI3Kα signaling in vivo, resulting in robust therapeutic efficacy and tolerability in PIK3CA-dependent tumors. Novel targeted therapeutics such as NVP-BYL719, designed to modulate aberrant functions elicited by cancer-specific genetic alterations upon which the disease depends, require well-defined patient stratification strategies in order to maximize their therapeutic impact and benefit for the patients. Here, we also describe the application of the Cancer Cell Line Encyclopedia as a preclinical platform to refine the patient stratification strategy for NVP-BYL719 and found that PIK3CA mutation was the foremost positive predictor of sensitivity while revealing additional positive and negative associations such as PIK3CA amplification and PTEN mutation, respectively. These patient selection determinants are being assayed in the ongoing NVP-BYL719 clinical trials. Mol Cancer Ther; 13(5); 1117–29. ©2014 AACR.

PDF - 129K, Legends for Supplementary Figures 1 through 4 and Supplementary Tables 1 through 7. Supplementary Table 1. Determination of NVP-BYL719 in vitro effects on human protein kinases. Supplementary Table 2. Activity profile of NVP-BYL719 in the Invitrogen Kinase panel. Supplementary Table 3. Activity profile of NVP-BYL719 in the Ambit Kinase panel. Supplementary Table 4. NVP-BYL719 Kd (nmol/L) determination in the Ambit Kinase panel for the hits found to be inhibited >90%. Supplementary Table 5. NVP-BYL719 anti-tumor effects in diverse cancer cell line-derived xenograft models. Supplementary Table 6. CCLE cell lines responsive to NVP-BYL719. Supplementary Table 7 Anti-tumor effect of NVP-BYL719 in patient-derived xenograft models carrying PIK3CA genetic alterations.

PDF - 71K, Rat1-myr-p110alpha (blue), beta (green) or delta (red) cells were treated with increasing concentrations of NVP-BYL719 for 30 minutes. Levels of S473P-Akt in cell extracts were quantified by Reverse Phase Protein Array as described in (18) and plotted as percentage of untreated control cells. The graph illustrates n=3 independent experiments. IC50s (plus/minus) SD and IC80s (plus/minus) SD of n=3 independent experiments are reported..

PDF - 92K, NVP-BYL719 does not inhibit mTOR and PIKKs involved in DNA damage-repair processes. A. TSC1 -/- MEFs cells were grown in a 96-well format and treated for 1 h with increased concentrations of RAD001 or NVP-BYL719 (from 0.5 nmol/L to 10 ?mol/L in 1 third dilution steps) and immediately fixed. S235/236P-RPS6 levels were measured and IC50 determined with the Excel module XLfit. Background (no primary Ab incubated); BL, Baseline. B: TSC1 -/- MEFs cells were treated with increasing concentrations of NVP-BYL719 as indicated or RAD001 at 500 nmol/L or an equivalent DMSO concentration for 30 minutes. Levels of S235/236P-RPS6 and total RPS6 in protein- normalized lysates were detected by Western blot analyzis using an activation-state specific antibody, followed by incubation with species- specific HRP-labeled secondary antibody and signal development by ECL. C: 24 h post seeding, A549 cells were treated at the same time with Actinomycin D (Act D) at a concentration of 5 ?mol/L (an agent used to induce DNA damage), and with increasing concentrations of NVP-BYL719 as indicated or with the vehicle control (DMSO) for 1 h. Levels of S15P-p53 and tubulin in protein-normalized lysates were detected by Western blot analysis using an activation-state specific antibody, followed by incubation with species- specific HRP-labeled secondary antibody and signal development by ECL. D: 24 h post seeding, U2OS cells were pre-treated for 1 h with increased concentrations of NVP-BYL719 or KU55933 a specific small molecular mass inhibitor of ATM (Supplementary reference 1) at a concentration of 10 ?mol/L or with the vehicle control (DMSO). The cells were then irradiated with 15 Gy and re-incubated at 37 degrees C for 1 h and then lysed. Levels of S1981P-ATM in protein- normalized lysates were detected by Western blot analysis using an activation-state specific antibody, followed by incubation with species- specific HRP-labeled secondary antibody and signal development by ECL.

PDF - 37K, NVP-BYL719 was tested at 10 different concentrations (from 0.5 nmol/L to 10 μmol/L in 1 third dilution steps) against CLK2 (A) and LRRK2 (B). SelectScreenTM Kinase Profiling Service uses XLfit from IDBS to determine the IC50 values (IC50 CLK2=621 nmol/L; IC50 LRRK2=3'220 nmol/L). The dose response curve is curve fit to model number 205 (sigmoidal dose-response model).

Technological advances in passive digital phenotyping present the opportunity to quantify neurological diseases using new approaches that may complement clinical assessments. Here, we studied multiple sclerosis (MS) as a model neurological disease for investigating physiometric and environmental signals. The objective of this study was to assess the feasibility and correlation of wearable biosensors with traditional clinical measures of disability both in clinic and in free-living in MS patients. This is a single site observational cohort study conducted at an academic neurological center specializing in MS. A cohort of 25 MS patients with varying disability scores were recruited. Patients were monitored in clinic while wearing biosensors at nine body locations at three separate visits. Biosensor-derived features including aspects of gait (stance time, turn angle, mean turn velocity) and balance were collected, along with standardized disability scores assessed by a neurologist. Participants also wore up to three sensors on the wrist, ankle, and sternum for 8 weeks as they went about their daily lives. The primary outcomes were feasibility, adherence, as well as correlation of biosensor-derived metrics with traditional neurologist-assessed clinical measures of disability. We used machine-learning algorithms to extract multiple features of motion and dexterity and correlated these measures with more traditional measures of neurological disability, including the expanded disability status scale (EDSS) and the MS functional composite-4 (MSFC-4). In free-living, sleep measures were additionally collected. Twenty-three subjects completed the first two of three in-clinic study visits and the 8-week free-living biosensor period. Several biosensor-derived features significantly correlated with EDSS and MSFC-4 scores derived at visit two, including mobility stance time with MSFC-4 z-score (Spearman correlation −0.546; p = 0.0070), several aspects of turning including turn angle (0.437; p = 0.0372), and maximum angular velocity (0.653; p = 0.0007). Similar correlations were observed at subsequent clinic visits, and in the free-living setting. We also found other passively collected signals, including measures of sleep, that correlated with disease severity. These findings demonstrate the feasibility of applying passive biosensor measurement techniques to monitor disability in MS patients both in clinic and in the free-living setting.

Rapid diagnosis and treatment of acute neurological illnesses such as stroke, hemorrhage, and hydrocephalus are critical to achieving positive outcomes and preserving neurologic function-'time is brain'1-5. Although these disorders are often recognizable by their symptoms, the critical means of their diagnosis is rapid imaging6-10. Computer-aided surveillance of acute neurologic events in cranial imaging has the potential to triage radiology workflow, thus decreasing time to treatment and improving outcomes. Substantial clinical work has focused on computer-assisted diagnosis (CAD), whereas technical work in volumetric image analysis has focused primarily on segmentation. 3D convolutional neural networks (3D-CNNs) have primarily been used for supervised classification on 3D modeling and light detection and ranging (LiDAR) data11-15. Here, we demonstrate a 3D-CNN architecture that performs weakly supervised classification to screen head CT images for acute neurologic events. Features were automatically learned from a clinical radiology dataset comprising 37,236 head CTs and were annotated with a semisupervised natural-language processing (NLP) framework16. We demonstrate the effectiveness of our approach to triage radiology workflow and accelerate the time to diagnosis from minutes to seconds through a randomized, double-blinded, prospective trial in a simulated clinical environment.

Purpose To compare different methods for generating features from radiology reports and to develop a method to automatically identify findings in these reports. Materials and Methods In this study, 96 303 head computed tomography (CT) reports were obtained. The linguistic complexity of these reports was compared with that of alternative corpora. Head CT reports were preprocessed, and machine-analyzable features were constructed by using bag-of-words (BOW), word embedding, and Latent Dirichlet allocation-based approaches. Ultimately, 1004 head CT reports were manually labeled for findings of interest by physicians, and a subset of these were deemed critical findings. Lasso logistic regression was used to train models for physician-assigned labels on 602 of 1004 head CT reports (60%) using the constructed features, and the performance of these models was validated on a held-out 402 of 1004 reports (40%). Models were scored by area under the receiver operating characteristic curve (AUC), and aggregate AUC statistics were reported for (a) all labels, (b) critical labels, and (c) the presence of any critical finding in a report. Sensitivity, specificity, accuracy, and F1 score were reported for the best performing model's (a) predictions of all labels and (b) identification of reports containing critical findings. Results The best-performing model (BOW with unigrams, bigrams, and trigrams plus average word embeddings vector) had a held-out AUC of 0.966 for identifying the presence of any critical head CT finding and an average 0.957 AUC across all head CT findings. Sensitivity and specificity for identifying the presence of any critical finding were 92.59% (175 of 189) and 89.67% (191 of 213), respectively. Average sensitivity and specificity across all findings were 90.25% (1898 of 2103) and 91.72% (18 351 of 20 007), respectively. Simpler BOW methods achieved results competitive with those of more sophisticated approaches, with an average AUC for presence of any critical finding of 0.951 for unigram BOW versus 0.966 for the best-performing model. The Yule I of the head CT corpus was 34, markedly lower than that of the Reuters corpus (at 103) or I2B2 discharge summaries (at 271), indicating lower linguistic complexity. Conclusion Automated methods can be used to identify findings in radiology reports. The success of this approach benefits from the standardized language of these reports. With this method, a large labeled corpus can be generated for applications such as deep learning.

Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous framework with which to study genetic variants, candidate targets, and small-molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes, including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from individuals of various lineages and ethnicities. Integration of these data with functional characterizations such as drug-sensitivity, short hairpin RNA knockdown and CRISPR-Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource for the acceleration of cancer research using model cancer cell lines.

Like classical chemotherapy regimens used to treat cancer, targeted therapies will also rely upon polypharmacology, but tools are still lacking to predict which combinations of molecularly targeted drugs may be most efficacious. In this study, we used image-based proliferation and apoptosis assays in colorectal cancer cell lines to systematically investigate the efficacy of combinations of two to six drugs that target critical oncogenic pathways. Drug pairs targeting key signaling pathways resulted in synergies across a broad spectrum of genetic backgrounds but often yielded only cytostatic responses. Enhanced cytotoxicity was observed when additional processes including apoptosis and cell cycle were targeted as part of the combination. In some cases, where cell lines were resistant to paired and tripled drugs, increased expression of antiapoptotic proteins was observed, requiring a fourth-order combination to induce cytotoxicity. Our results illustrate how high-order drug combinations are needed to kill drug-resistant cancer cells, and they also show how systematic drug combination screening together with a molecular understanding of drug responses may help define optimal cocktails to overcome aggressive cancers. Cancer Res; 76(23); 6950–63. ©2016 AACR.

Motivation Radiologists have used algorithms for Computer-Aided Diagnosis (CAD) for decades. These algorithms use machine learning with engineered features, and there have been mixed findings on whether they improve radiologists’ interpretations. Deep learning offers superior performance but requires more training data and has not been evaluated in joint algorithm-radiologist decision systems. Results We developed the Computer-Aided Note and Diagnosis Interface (CANDI) for collaboratively annotating radiographs and evaluating how algorithms alter human interpretation. The annotation app collects classification, segmentation, and image captioning training data, and the evaluation app randomizes the availability of CAD tools to facilitate clinical trials on radiologist enhancement. Availability and implementation Demonstrations and source code are hosted at (https://candi.nextgenhealthcare.org), and (https://github.com/mbadge/candi), respectively, under GPL-3 license. Supplementary information Supplementary material is available at Bioinformatics online.

Large cancer cell line collections broadly capture the genomic diversity of human cancers and provide valuable insight into anti-cancer drug response. Here we show substantial agreement and biological consilience between drug sensitivity measurements and their associated genomic predictors from two publicly available large-scale pharmacogenomics resources: The Cancer Cell Line Encyclopedia and the Genomics of Drug Sensitivity in Cancer databases.

Profiling candidate therapeutics with limited cancer models during preclinical development hinders predictions of clinical efficacy and identifying factors that underlie heterogeneous patient responses for patient-selection strategies. We established ∼1,000 patient-derived tumor xenograft models (PDXs) with a diverse set of driver mutations. With these PDXs, we performed in vivo compound screens using a 1 × 1 × 1 experimental design (PDX clinical trial or PCT) to assess the population responses to 62 treatments across six indications. We demonstrate both the reproducibility and the clinical translatability of this approach by identifying associations between a genotype and drug response, and established mechanisms of resistance. In addition, our results suggest that PCTs may represent a more accurate approach than cell line models for assessing the clinical potential of some therapeutic modalities. We therefore propose that this experimental paradigm could potentially improve preclinical evaluation of treatment modalities and enhance our ability to predict clinical trial responses.

Inhibitors of double minute 2 protein (MDM2)-tumor protein 53 (TP53) interaction are predicted to be effective in tumors in which the TP53 gene is wild type, by preventing TP53 protein degradation. One such setting is represented by the frequent CDKN2A deletion in human cancer that, through inactivation of p14ARF, activates MDM2 protein, which in turn degrades TP53 tumor suppressor. Here we used piggyBac (PB) transposon insertional mutagenesis to anticipate resistance mechanisms occurring during treatment with the MDM2-TP53 inhibitor HDM201. Constitutive PB mutagenesis in Arf-/- mice provided a collection of spontaneous tumors with characterized insertional genetic landscapes. Tumors were allografted in large cohorts of mice to assess the pharmacologic effects of HDM201. Sixteen out of 21 allograft models were sensitive to HDM201 but ultimately relapsed under treatment. A comparison of tumors with acquired resistance to HDM201 and untreated tumors identified 87 genes that were differentially and significantly targeted by the PB transposon. Resistant tumors displayed a complex clonality pattern suggesting the emergence of several resistant subclones. Among the most frequent alterations conferring resistance, we observed somatic and insertional loss-of-function mutations in transformation-related protein 53 (Trp53) in 54% of tumors and transposon-mediated gain-of-function alterations in B-cell lymphoma-extra large (Bcl-xL), Mdm4, and two TP53 family members, resulting in expression of the TP53 dominant negative truncations ΔNTrp63 and ΔNTrp73. Enhanced BCL-xL and MDM4 protein expression was confirmed in resistant tumors, as well as in HDM201-resistant patient-derived tumor xenografts. Interestingly, concomitant inhibition of MDM2 and BCL-xL demonstrated significant synergy in p53 wild-type cell lines in vitro. Collectively, our findings identify several potential mechanisms by which TP53 wild-type tumors may escape MDM2-targeted therapy.

SummaryActivation of the phosphoinositide 3-kinase (PI3K) pathway occurs frequently in breast cancer. However, clinical results of single-agent PI3K inhibitors have been modest to date. A combinatorial drug screen on multiple PIK3CA mutant cancers with decreased sensitivity to PI3K inhibitors revealed that combined CDK 4/6-PI3K inhibition synergistically reduces cell viability. Laboratory studies revealed that sensitive cancers suppress RB phosphorylation upon treatment with single-agent PI3K inhibitors but cancers with reduced sensitivity fail to do so. Similarly, patients’ tumors that responded to the PI3K inhibitor BYL719 demonstrated suppression of pRB, while nonresponding tumors showed sustained or increased levels of pRB. Importantly, the combination of PI3K and CDK 4/6 inhibitors overcomes intrinsic and adaptive resistance leading to tumor regressions in PIK3CA mutant xenografts.

Flux balance analysis (FBA) is an increasingly useful approach for modeling the behavior of metabolic systems. However, standard FBA modeling of genetic knockouts can not predict drug combination synergies observed between serial metabolic targets, even though such synergies give rise to some of the most widely used antibiotic treatments. Here we extend FBA modeling to simulate responses to chemical inhibitors at varying concentrations, by diverting enzymatic flux to a waste reaction. This flux diversion yields very similar qualitative predictions to prior methods for single target activity. However, we find very different predictions for combinations, where flux diversion, which mimics the kinetics of competitive metabolic inhibitors, can explain serial target synergies between metabolic enzyme inhibitors that we confirmed in Escherichia coli cultures. FBA flux diversion opens the possibility for more accurate genome-scale predictions of drug synergies, which can be used to suggest treatments for infections and other diseases.

The systematic translation of cancer genomic data into knowledge of tumour biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacological annotation is available. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Together, our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of 'personalized' therapeutic regimens.

Cystic fibrosis (CF) is an inherited, life-threatening disease caused by mutations in the gene encoding cystic fibrosis transmembrane conductance regulator (CFTR), an ABC transporter-class protein and ion channel that transports ions across epithelial cell membranes. The most common mutation leads to the deletion of a single phenylalanine, and the resulting protein, F508del-CFTR, shows reduced trafficking to the membrane and defective channel gating. The ideal therapeutic approach would address both of these defects and restore channel function at the same time. We describe here the application of a combination high-throughput screening to search for synergistic modulators of F508del-CFTR. With the adapted Fischer rat thyroid-yellow fluorescent protein halide flux assay to the combination high-throughput screening platform, we identified many interesting single agents as CFTR modulators from a library of approved drugs and mechanistic probe compounds, and combinations that synergistically modulate F508del-CFTR channel function in Fischer rat thyroid cells, demonstrating the potential for combination therapeutics to address the defects that cause CF.

Currently, no approved therapeutics exist to treat or prevent infections induced by Ebola viruses, and recent events have demonstrated an urgent need for rapid discovery of new treatments. Repurposing approved drugs for emerging infections remains a critical resource for potential antiviral therapies. We tested ~2600 approved drugs and molecular probes in an in vitro infection assay using the type species, Zaire ebolavirus. Selective antiviral activity was found for 80 U.S. Food and Drug Administration–approved drugs spanning multiple mechanistic classes, including selective estrogen receptor modulators, antihistamines, calcium channel blockers, and antidepressants. Results using an in vivo murine Ebola virus infection model confirmed the protective ability of several drugs, such as bepridil and sertraline. Viral entry assays indicated that most of these antiviral drugs block a late stage of viral entry. By nature of their approved status, these drugs have the potential to be rapidly advanced to clinical settings and used as therapeutic countermeasures for Ebola virus infections.

Gravitational lensing assists in the detection of quasar hosts by amplifying and distorting the host light away from the unresolved quasar core images. We present the results of HST observations of 30 quasar hosts at redshifts 1 < z < 4.5. The hosts are small in size (r_e 1.7 is a factor of 3--6 higher than the local value. But, depending on the stellar content the ratio may decline at z>4 (if E/S0-like), flatten off to 6--10 times the local value (if Sbc-like), or continue to rise (if Im-like). We infer that galaxy bulge masses must have grown by a factor of 3--6 over the redshift range 3>z>1, and then changed little since z~1. This suggests that the peak epoch of galaxy formation for massive galaxies is above z~1. We also estimate the duty cycle of luminous AGNs at z>1 to be ~1%, or 10^7 yrs, with sizable scatter., Comment: 8 pages, 6 figures, review article with C. Impey at the conference on "QSO Host Galaxies: Evolution and Environment", Aug. 29-Sep. 2, 2005, Lorentz Center, Leiden, The Netherlands

In the present-day universe, supermassive black hole masses (MBH) appear to be strongly correlated with their galaxy's bulge luminosity, among other properties. In this study, we explore the analogous relationship between MBH, derived using the virial method, and the stellar R-band bulge luminosity (Lr) or stellar bulge mass (M*) at epochs of 1 < z < 4.5 using a sample of 31 gravitationally lensed AGNs and 20 non-lensed AGNs. At redshifts z > 1.7 (10--12 Gyrs ago), we find that the observed MBH--Lr relation is nearly the same (to within ~0.3 mag) as it is today. When the observed Lr are corrected for luminosity evolution, this means that the black holes grew in mass faster than their hosts, with the MBH/M* mass ratio being a factor of > 4(+2)(-1) times larger at z > 1.7 than it is today. By the redshift range 11.7 were fully formed bulges that passively faded to the present epoch are ruled out., Comment: ApJ accepted, includes Referee comments and statistics to better quantify the statistical significance of results. 23 pages, 11 figures, 4 tables

Tankyrases (TNKS) play roles in Wnt signaling, telomere homeostasis, and mitosis, offering attractive targets for anticancer treatment. Using unbiased combination screening in a large panel of cancer cell lines, we have identified a strong synergy between TNKS and MEK inhibitors (MEKi) in KRAS-mutant cancer cells. Our study uncovers a novel function of TNKS in the relief of a feedback loop induced by MEK inhibition on FGFR2 signaling pathway. Moreover, dual inhibition of TNKS and MEK leads to more robust apoptosis and antitumor activity both in vitro and in vivo than effects observed by previously reported MEKi combinations. Altogether, our results show how a novel combination of TNKS and MEK inhibitors can be highly effective in targeting KRAS-mutant cancers by suppressing a newly discovered resistance mechanism. Cancer Res; 74(12); 3294–305. ©2014 AACR.

Somatic PIK3CA mutations are frequently found in solid tumors, raising the hypothesis that selective inhibition of PI3Kα may have robust efficacy in PIK3CA-mutant cancers while sparing patients the side-effects associated with broader inhibition of the class I phosphoinositide 3-kinase (PI3K) family. Here, we report the biologic properties of the 2-aminothiazole derivative NVP-BYL719, a selective inhibitor of PI3Kα and its most common oncogenic mutant forms. The compound selectivity combined with excellent drug-like properties translates to dose- and time-dependent inhibition of PI3Kα signaling in vivo, resulting in robust therapeutic efficacy and tolerability in PIK3CA-dependent tumors. Novel targeted therapeutics such as NVP-BYL719, designed to modulate aberrant functions elicited by cancer-specific genetic alterations upon which the disease depends, require well-defined patient stratification strategies in order to maximize their therapeutic impact and benefit for the patients. Here, we also describe the application of the Cancer Cell Line Encyclopedia as a preclinical platform to refine the patient stratification strategy for NVP-BYL719 and found that PIK3CA mutation was the foremost positive predictor of sensitivity while revealing additional positive and negative associations such as PIK3CA amplification and PTEN mutation, respectively. These patient selection determinants are being assayed in the ongoing NVP-BYL719 clinical trials. Mol Cancer Ther; 13(5); 1117–29. ©2014 AACR.

HST V and I-band observations show that the gravitational lens B1359+154 consists of six images of a single z_s=3.235 radio source and its star-forming host galaxy, produced by a compact group of galaxies at z_l = 1. VLBA observations at 1.7 GHz strongly support this conclusion, showing six compact cores with similar low-frequency radio spectra. B1359+154 is the first example of galaxy-scale gravitational lensing in which more than four images are observed of the same background source. The configuration is due to the unique lensing mass distribution: three primary lens galaxies lying on the vertices of a triangle separated by 0.7 arcsec (4/h kpc), inside the 1.7 arcsec diameter Einstein ring defined by the radio images. The gravitational potential has additional extrema within this triangle, creating a pair of central images that supplement the ``standard'' four-image geometry of the outer components. Simple mass models consisting of three lens galaxies constrained by HST and VLBA astrometry naturally reproduce the observed image positions but must be finely-tuned to fit the flux densities., 28 pages including 6 figures, ApJ submitted

We performed an automated comparison of the FIRST radio survey with the APM optical catalog to find radio lobes with optical counterparts. Based on an initial survey covering ~3000 square degrees, we selected a sample of 33 lens candidates for VLA confirmation. VLA and optical observations of these candidates yielded two lens systems, one a new discovery (J0816+5003), and one of which was previously known (J1549+3047). Two other candidates have radio lobes with galaxies superposed, but lack evidence of multiple imaging. One of our targets (J0958+2947) is a projected close pair of quasars (8'' separation at redshifts 2.064 and 2.744). Our search method is highly efficient, with >5% of our observing targets being lensed, compared to the usual success rate of, Submitted to ApJ, 2000.07.28, revised 2000.09.12. Minor revisions and new observations of best example. Eleven eps figures. Uses AASTeX/LaTeX, psfig2.tex

We report the discovery of a new double-image quasar that was found during a search for gravitational lenses in the southern sky. Radio source PMN J1838-3427 is composed of two flat-spectrum components with separation 1", flux density ratio 14:1 and matching spectral indices, in VLA and VLBA images. Ground-based BRI images show the optical counterpart (total I=18.6) is also double with the same separation and position angle as the radio components. An HST/WFPC2 image reveals the lens galaxy. The optical flux ratio (27:1) is higher than the radio value probably due to differential extinction of the components by the lens galaxy. An optical spectrum of the bright component contains quasar emission lines at z=2.78 and several absorption features, including prominent Ly-alpha absorption. The lens galaxy redshift could not be measured but is estimated to be z=0.36 +/- 0.08. The image configuration is consistent with the simplest plausible models for the lens potential. The flat radio spectrum and observed variability of PMN J1838-3427 suggest the time delay between flux variations of the components is measurable, and could thus provide an independent measurement of H_0., 23 pages, incl. 6 figures, to appear in A.J.; replaced with accepted version; minor changes to text, improved figures

We have obtained and modeled NICMOS images of the Einstein ring lens system MG J1131+0456, which show that its lens galaxy is an H = 18.6 mag, transparent, early-type galaxy at a redshift of zl 0.84; it has a major axis effective radius Re = 07 ? 01, projected axis ratio b/a = 0.6 ? 0.1, and major axis P.A. = 55? ? 9?. The lens is the brightest member of a group of at least seven galaxies with similar R-I and I-H colors, and the two closest group members produce sufficient tidal perturbations to explain the shape of the ring. The host galaxy of the MG J1131+0456 source is a zs 2 extremely red object (ERO) that is lensed into optical and infrared rings of dramatically different morphologies. These differences imply a strongly wavelength-dependent source morphology that could be explained by embedding the host in a larger, dusty disk. At 1.6 ?m (H), the ring is spectacularly luminous, with a total observed flux of H = 17.4 mag and a demagnified flux of 19.3 mag, corresponding to a 1-2 L* galaxy at the probable source redshift of zs 2. Thus, it is primarily the stellar emission of the radio source host galaxy that produces the overall colors of two of the reddest radio lenses, MG J1131+0456 and JVAS B1938+666, aided by the suppression of optical active galactic nucleus emission by dust in the source galaxy. The dusty lens hypothesis ? that many massive early-type galaxies with 0 zl 1 have large, uniform dust opacities ? is ruled out.

We determine 37 differential extinctions in 23 gravitational lens galaxies over the range 0 < z_l < 1. Only 7 of the 23 systems have spectral differences consistent with no differential extinction. The median differential extinction for the optically-selected (radio-selected) subsample is E(B-V)=0.04 (0.06) mag. The extinction is patchy and shows no correlation with impact parameter. The median total extinction of the bluest images is E(B-V)=0.08 mag, although the total extinction distribution is dominated by the uncertainties in the intrinsic colors of quasars. The directly measured extinction distributions are consistent with the mean extinction estimated by comparing the statistics of quasar and radio lens surveys, thereby confirming the need for extinction corrections when using the statistics of lensed quasars to estimate the cosmological model. A disjoint subsample of two face-on, radio-selected spiral lenses shows both high differential and total extinctions, but standard dust-to-gas ratios combined with the observed molecular gas column densities overpredict the amount of extinction by factors of 2-5. For several systems we can estimate the extinction law, ranging from R_V=1.5+/-0.2 for a z_l=0.96 elliptical, to R_V=7.2+/-0.1 for a z_l=0.68 spiral. For the four radio lenses where we can construct non-parametric extinction curves we find no evidence for gray dust over the IR-UV wavelength range. The dust can be used to estimate lens redshifts with reasonable accuracy, although we sometimes find two degenerate redshift solutions.

We examine models of the mass distribution for the first known case of gravitational lensing. Several new sets of constraints are used, based on recent observations. We remodel the VLBI observations of the radio jets in the two images of Q0957+561, showing that the previously derived positions and uncertainties were incorrect. We use as additional constraints the candidate lensed pairs of galaxies identified recently with the Hubble Space Telescope. We explore a wider range of lens models than before, and find that the Hubble constant is not tightly constrained once elliptical lens models are considered. We also discuss the systematic uncertainties caused by the cluster containing the lens galaxy. We conclude that additional observations of the candidate lensed galaxies as well as direct measurements of the cluster mass profile are needed before an accurate value of the Hubble constant can be derived from this lens., 28 pages, Latex + 4 figures, accepted for ApJ. Final version, with minor changes. Model parameters in Table 4 corrected

We describe the goals of the CASTLES (CfA-Arizona-Space-Telescope-LEns-Survey) project including a sample of NICMOS images of gravitational lenses and a brief list of the preliminary findings.

Ebola viruses remain a substantial threat to both civilian and military populations as bioweapons, during sporadic outbreaks, and from the possibility of accidental importation from endemic regions by infected individuals. Currently, no approved therapeutics exist to treat or prevent infection by Ebola viruses. Therefore, we performed an in vitro screen of Food and Drug Administration (FDA)– and ex–US-approved drugs and selected molecular probes to identify drugs with antiviral activity against the type species Zaire ebolavirus (EBOV). From this screen, we identified a set of selective estrogen receptor modulators (SERMs), including clomiphene and toremifene, which act as potent inhibitors of EBOV infection. Anti-EBOV activity was confirmed for both of these SERMs in an in vivo mouse infection model. This anti-EBOV activity occurred even in the absence of detectable estrogen receptor expression, and both SERMs inhibited virus entry after internalization, suggesting that clomiphene and toremifene are not working through classical pathways associated with the estrogen receptor. Instead, the response appeared to be an off-target effect where the compounds interfere with a step late in viral entry and likely affect the triggering of fusion. These data support the screening of readily available approved drugs to identify therapeutics for the Ebola viruses and other infectious diseases. The SERM compounds described in this report are an immediately actionable class of approved drugs that can be repurposed for treatment of filovirus infections.

We show that the high redshift IRAS source F10214 is highly magnified by the gravitational field of an intervening elliptical galaxy, accounting for its many anomalous properties. Detailed radio and near-IR images identify the IRAS source with a symmetric arc, centered on a red object, or lensing galaxy. To explain the observed structures, the center of the source must much more highly magnified than its outer regions. Lensing predicts a small counterimage to the arc, which we find adjacent to the lensing galaxy. A red component in the observed spectrum suggests a lens redshift of unity, and the lens model yields a mass estimate of $M(r

Tumors are complex biological systems that often retain proliferative capacity even when challenged with drug treatment. Given this resiliency, drug combinations may provide greater therapeutic benefit, however, which molecules to combine and how many to include in combinations for effective responses is not clear yet. Using image-based proliferation and apoptosis assays in colorectal cancer cell lines we systematically investigated combinations that ranged in number from two to six drugs and targeted critical oncogenic pathways. Drug pairs targeting key signaling pathways resulted in synergies across a broad spectrum of genetic backgrounds, but often yielded only cytostatic responses. Enhanced cytotoxicity was observed when additional processes including apoptosis and cell cycle were targeted as part of the combination. In many cases, where cell lines were resistant to two- and three-way drug combinations, increased expression of anti-apoptotic proteins was observed and induction of cytotoxic responses required up to fourth-order combinations. Our results demonstrate that high-order drug combinations might be needed to kill cancers and show how systematic drug combination screening together with a molecular understanding of drug responses can guide their identification. Citation Format: Thomas Horn, Stephane Ferretti, Nicolas Ebel, Angela Tam, Samuel Ho, Fred Harbinski, Ali Farsidjani, Matt Zubrowski, William R. Sellers, Robert Schlegel, Dale Porter, Erick Morris, Jens Wuerthner, Sebastien Jeay, Joel Greshock, Ensar Halilovic, Levi A. Garraway, Giordano Caponigro, Joseph Lehar. High order drug combinations are required to effectively kill colorectal cancer cells. [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 1311.

The mammalian target of rapamycin (mTOR) is regulated by oncogenic growth factor signals and plays a pivotal role in controlling cellular metabolism, growth and survival. Everolimus (RAD001) is an allosteric mTOR inhibitor that has shown marked efficacy in certain cancers but is unable to completely inhibit mTOR activity. ATP-competitive mTOR inhibitors such as NVP-BEZ235 can block rapamycin-insensitive mTOR readouts and have entered clinical development as anti-cancer agents. Here, we show the degree to which RAD001 and BEZ235 can be synergistically combined to inhibit mTOR pathway activation, cell proliferation and tumor growth, both in vitro and in vivo. RAD001 and BEZ235 synergized in cancer lines representing different lineages and genetic backgrounds. Strong synergy is seen in neuronal, renal, breast, lung, and haematopoietic cancer cells harboring abnormalities in PTEN, VHL, LKB1, Her2, or KRAS. Critically, in the presence of RAD001, the mTOR-4EBP1 pathway and tumorigenesis can be fully inhibited using lower doses of BEZ235. This is relevant since RAD001 is relatively well tolerated in patients while the toxicity profiles of ATP-competitive mTOR inhibitors are currently unknown.

Phenotypes that might otherwise reveal a gene’s function can be obscured by genes with overlapping function. This phenomenon is best-known within gene families, where an important shared function may only be revealed by mutating all family members. Here we describe the ‘Green Monster’ technology enabling the precise deletion of many genes. In this method, a population of deletion strains with each deletion marked by an inducible green fluorescent protein (GFP) reporter gene, is subjected to repeated rounds of mating, meiosis, and flow-cytometric enrichment. This results in the aggregation of multiple deletion loci within single cells. The Green Monster strategy is potentially applicable to assembling other engineered alterations in any species with sex or alternative means of allelic assortment. To demonstrate the technology, we generated a single broadly drug-sensitive strain of Saccharomyces cerevisiae bearing precise deletions of all 16 adenosine triphosphate-binding cassette transporters within clades associated with multi-drug resistance.

SREBP-2, oxidosqualene cyclase (OSC) or lanosterol demethylase were identified as novel sterol pathway-associated targets that, when probed with chemical agents, can inhibit hepatitis C virus (HCV) replication. Using a combination chemical genetics approach, combinations of chemicals targeting sterol pathway enzymes downstream of and including OSC or protein geranylgeranyl transferase I (PGGT) produce robust and selective synergistic inhibition of HCV replication. Inhibition of enzymes upstream of OSC elicit proviral responses that are dominant to the effects of inhibiting all downstream targets. Inhibition of the sterol pathway without inhibition of regulatory feedback mechanisms ultimately results in an increase in HCV replication because of a compensatory upregulation of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) expression. Increases in HMGCR expression without inhibition of HMGCR enzymatic activity ultimately stimulate HCV replication through increasing the cellular pool of geranylgeranyl pyrophosphate (GGPP). Chemical inhibitors that ultimately prevent SREBP-2 activation, inhibit PGGT or encourage the production of polar sterols have great potential as HCV therapeutics if associated toxicities can be reduced., Chemical inhibition of enzymes in either the cholesterol or the fatty acid biosynthetic pathways has been shown to impact viral replication, both positively and negatively (Su et al, 2002; Ye et al, 2003; Kapadia and Chisari, 2005; Sagan et al, 2006; Amemiya et al, 2008). FBL2 has been identified as a 50 kDa geranylgeranylated host protein that is necessary for localization of the hepatitis C virus (HCV) replication complex to the membranous web through its close association with the HCV protein NS5A and is critical for HCV replication (Wang et al, 2005). Inhibition of the protein geranylgeranyl transferase I (PGGT), an enzyme that transfers geranylgeranyl pyrophosphate (GGPP) to cellular proteins such as FBL2 for the purpose of membrane anchoring, negatively impacts HCV replication (Ye et al, 2003). Conversely, chemical agents that increase intracellular GGPP concentrations promote viral replication (Kapadia and Chisari, 2005). Statin compounds that inhibit 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR), the rate-limiting enzyme in the sterol pathway (Goldstein and Brown, 1990), have been suggested to inhibit HCV replication through ultimately reducing the cellular pool of GGPP (Ye et al, 2003; Kapadia and Chisari, 2005; Ikeda et al, 2006). However, inhibition of the sterol pathway with statin drugs has not yielded consistent results in patients. The use of statins for the treatment of HCV is likely to be complicated by the reported compensatory increase in HMGCR expression in vitro and in vivo (Stone et al, 1989; Cohen et al, 1993) in response to treatment. Enzymes in the sterol pathway are regulated on a transcriptional level by sterol regulatory element-binding proteins (SREBPs), specifically SREBP-2 (Hua et al, 1993; Brown and Goldstein, 1997). When cholesterol stores in cells are depleted, SREBP-2 activates transcription of genes in the sterol pathway such as HMGCR, HMG-CoA synthase, farnesyl pyrophosphate (FPP) synthase, squalene synthase (SQLS) and the LDL receptor (Smith et al, 1988, 1990; Sakai et al, 1996; Brown and Goldstein, 1999; Horton et al, 2002). The requirement of additional downstream sterol pathway metabolites for HCV replication has not been completely elucidated. To further understand the impact of the sterol pathway and its regulation on HCV replication, we conducted a high-throughput combination chemical genetic screen using 16 chemical probes that are known to modulate the activity of target enzymes relating to the sterol biosynthesis pathway (Figure 1). Using this approach, we identified several novel antiviral targets including SREBP-2 as well as targets downstream of HMGCR in the sterol pathway such as oxidosqualene cyclase (OSC) and lanosterol demethylase. Many of our chemical probes, specifically SR-12813, farnesol and squalestatin, strongly promoted replicon replication. The actions of both farnesol and squalestatin ultimately result in an increase in the cellular pool of GGPP, which is known to increase HCV replication (Ye et al, 2003; Kapadia and Chisari, 2005; Wang et al, 2005). Chemical combinations targeting enzymes upstream of squalene epoxidase (SQLE) at the top of the sterol pathway (Figure 4A) elicited Bateson-type epistatic responses (Boone et al, 2007), where the upstream agent's response predominates over the effects of inhibiting all downstream targets. This was especially notable for combinations including simvastatin and either U18666A or squalestatin, and for squalestatin in combination with Ro48-8071. Treatment with squalestatin prevents the SQLS substrate, farnesyl pyrophosphate (FPP) from being further metabolized by the sterol pathway. As FPP concentrations increase, the metabolite can be shunted away from the sterol pathway toward farnesylation and GGPP synthetic pathways, resulting in an increase in host protein geranylgeranylation, including FBL2, and consequently replicon replication. This increase in replicon replication explains the source of the observed epistasis over Ro48-8071 treatment. Combinations between probes targeting enzymes downstream of and including OSC produced robust synergies with each other or with a PGGT inhibitor. Figure 4B highlights examples of antiviral synergy resulting from treatment of cells with an OSC inhibitor in combination with an inhibitor of either an enzyme upstream or downstream of OSC. A combination of terconazole and U18666A is synergistic without similar combination effects in the host proliferation screen. Likewise, clomiphene was also synergistic when added to replicon cells in combination with U18666A. One of the greatest synergies observed downstream in the sterol pathway is a combination of amorolfine and AY 9944, suggesting that there is value in developing combinations of drugs that target enzymes in the sterol pathway, which are downstream of HMGCR. Interactions with the protein prenylation pathway also showed strong mechanistic patterns (Figure 4C). GGTI-286 is a peptidomimetic compound resembling the CAAX domain of a protein to be geranylgeranylated and is a competitive inhibitor of protein geranylgeranylation. Simvastatin impedes the antiviral effect of GGTI-286 at low concentrations but that antagonism is balanced by comparable synergy at higher concentrations. At the low simvastatin concentrations, a compensatory increase in HMGCR expression leads to increased cellular levels of GGPP, which are likely to result in an increase in PGGT enzymatic turnover and decreased GGTI-286 efficacy. The antiviral synergy observed at the higher inhibitor concentrations is likely nonspecific as synergy was also observed in a host viability assay. Further downstream, however, a competitive interaction was observed between GGTI-286 and squalestatin, where the opposing effect of one compound obscures the other compound's effect. This competitive relationship between GGTI and SQLE explains the epistatic response observed between those two agents. For inhibitors of targets downstream of OSC, such as amorolfine, there are strong antiviral synergies with GGTI-286. Notably, combinations with OSC inhibitors and GGTI-286 were selective, in that comparable synergy was not found in a host viability assay. This selectivity suggests that jointly targeting OSC and PGGT is a promising avenue for future HCV therapy development. This study provides a comprehensive and unique perspective into the impact of sterol pathway regulation on HCV replication and provides compelling insight into the use of chemical combinations to maximize antiviral effects while minimizing proviral consequences. Our results suggest that HCV therapeutics developed against sterol pathway targets must consider the impact on underlying sterol pathway regulation. We found combinations of inhibitors of the lower part of the sterol pathway that are effective and synergistic with each other when tested in combination. Furthermore, the combination effects observed with simvastatin suggest that, though statins inhibit HMGCR activity, the resulting regulatory consequences of such inhibition ultimately lead to undesirable epistatic effects. Inhibitors that prevent SREBP-2 activation, inhibit PGGT or encourage the production of polar sterols have great potential as HCV therapeutics if associated toxicities can be reduced., The search for effective Hepatitis C antiviral therapies has recently focused on host sterol metabolism and protein prenylation pathways that indirectly affect viral replication. However, inhibition of the sterol pathway with statin drugs has not yielded consistent results in patients. Here, we present a combination chemical genetic study to explore how the sterol and protein prenylation pathways work together to affect hepatitis C viral replication in a replicon assay. In addition to finding novel targets affecting viral replication, our data suggest that the viral replication is strongly affected by sterol pathway regulation. There is a marked transition from antagonistic to synergistic antiviral effects as the combination targets shift downstream along the sterol pathway. We also show how pathway regulation frustrates potential hepatitis C therapies based on the sterol pathway, and reveal novel synergies that selectively inhibit hepatitis C replication over host toxicity. In particular, combinations targeting the downstream sterol pathway enzymes produced robust and selective synergistic inhibition of hepatitis C replication. Our findings show how combination chemical genetics can reveal critical pathway connections relevant to viral replication, and can identify potential treatments with an increased therapeutic window.

We propose that a large number of gravitationally lensed rings should be observable in the optical. We argue that the probability of forming a ring is likely to be similar for optical and radio sources. The number of optical rings in the sky can then be estimated from the rate of occurrence of rings in radio sources, and the observed number of optical sources. This gives ∼100 optical rings per square degree, or a few million over the whole sky, to a magnitude limit of B=26. Most of the rings should be substantially bluer than the foreground lenses, allowing them to be detected with multicolour imaging

Drug combinations are an increasingly favored strategy for increasing therapeutic windows for potential drugs, but enthusiasm for this approach is tempered by concerns that therapeutic synergy will too often be mirrored by synergistic toxicity. Here we review our recent experimental results and numerical simulations that establish the context-specificity of synergistic combinations. Thus systematic testing of chemical combinations in cell-based disease models can preferentially discover synergies with beneficial therapeutic selectivity. For an anti-inflammatory combination, we demonstrate how such selective synergy is achieved through differential expression of its targets in cells associated with therapeutic and toxic effects, and validate the combination's therapeutic relevance in animals. The narrower context specificity of synergistic combinations creates many new opportunities for such therapeutically relevant selectivity, and reinforces the realization that the most useful paradigm for a drug target is often a set of biomolecules that cooperate to produce a therapeutic response with reduced side effects.

Prevailing drug discovery approaches focus on compounds with molecular selectivity, inhibiting disease-relevant targets over others in vitro. However in vivo, many such agents are not therapeutically selective, either because of undesirable activity at effective doses or because the biological system responds to compensate. In theory, drug combinations should permit increased control of such complex biology, but there is a common concern that therapeutic synergy will generally be mirrored by synergistic side-effects. Here we provide evidence, from 94,110 multi-dose combination experiments representing diverse disease areas and large scale flux balance simulations of inhibited bacterial metabolism, that multi-target synergies are more specific than single agent activities to particular cellular contexts. Using an anti-inflammatory combination, we show how multi-target synergy can achieve therapeutic selectivity in animals through differential target expression. Synergistic combinations can increase the number of selective therapies using the current pharmacopeia, and offer opportunities for more precise control of biological systems.

Predicting the behavior of living organisms is an enormous challenge given their vast complexity. Efforts to model biological systems require large datasets generated by physical binding experiments and perturbation studies. Genetic perturbations have proven important and are greatly facilitated by the advent of comprehensive mutant libraries in model organisms. Small-molecule chemical perturbagens provide a complementary approach, especially for systems that lack mutant libraries, and can easily probe the function of essential genes. Though single chemical or genetic perturbations provide crucial information associating individual components (for example, genes, proteins or small molecules) with pathways or phenotypes, functional relationships between pathways and modules of components are most effectively obtained from combined perturbation experiments. Here we review the current state of and discuss some future directions for 'combination chemical genetics', the systematic application of multiple chemical or mixed chemical and genetic perturbations, both to gain insight into biological systems and to facilitate medical discoveries.

In 1981, a faint radio source (G') was detected near the center of the lensing galaxy of the famous "twin quasar" Q0957+561. It is still unknown whether this central radio source is a third quasar image or an active nucleus of the lensing galaxy, or a combination of both. In an attempt to resolve this ambiguity, we observed Q0957+561 at radio wavelengths of 13cm, 18cm, and 21cm, using the Very Long Baseline Array in combination with the phased Very Large Array and the Green Bank Telescope. We measured the spectrum of G' for the first time and found it to be significantly different from the spectra of the two bright quasar images. This finding suggests that the central component is primarily or entirely emission from the foreground lens galaxy, but the spectrum is also consistent with the hypothesis of a central quasar image suffering free-free absorption. In addition, we confirm the previously-reported VLBI position of G' just north of the optical center of the lens galaxy. The position slightly favors the hypothesis that G' originates in the lens, but is not conclusive. We discuss the prospects for further clarification of this issue., 18 pages, accepted for publication in AJ

Biological systems are robust, in that they can maintain stable phenotypes under varying conditions or attacks. Biological systems are also complex, being organized into many functional modules that communicate through interlocking pathways and feedback mechanisms. In these systems, robustness and complexity are linked because both qualities arise from the same underlying mechanisms. When perturbed by multiple attacks, such complex systems become fragile in both theoretical and experimental studies, and this fragility depends on the number of agents applied. We explore how this relationship can be used to study the functional robustness of a biological system using systematic high-order combination experiments. This presents a promising approach toward many biomedical and bioengineering challenges. For example, high-order experiments could determine the point of fragility for pathogenic bacteria and might help identify optimal treatments against multi-drug resistance. Such studies would also reinforce the growing appreciation that biological systems are best manipulated not by targeting a single protein, but by modulating the set of many nodes that can selectively control a system's functional state.