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Supplementary Data 4 from Integrating Global Gene Expression and Radiation Survival Parameters across the 60 Cell Lines of the National Cancer Institute Anticancer Drug Screen

Supplementary Table 3 from A Cell Proliferation and Chromosomal Instability Signature in Anaplastic Thyroid Carcinoma

Supplementary Data 3 from Integrating Global Gene Expression and Radiation Survival Parameters across the 60 Cell Lines of the National Cancer Institute Anticancer Drug Screen

Supplementary Data 2 from Integrating Global Gene Expression and Radiation Survival Parameters across the 60 Cell Lines of the National Cancer Institute Anticancer Drug Screen

Supplementary Figure 1 from A Cell Proliferation and Chromosomal Instability Signature in Anaplastic Thyroid Carcinoma

The 60 cell lines of the National Cancer Institute Anticancer Drug Screen (NCI-60) constitute the most extensively characterized in vitro cancer cell model. They have been tested for sensitivity to more than 100,000 potential chemotherapy agents and have been profiled extensively at the DNA, RNA, protein, functional, and pharmacologic levels. We have used the NCI-60 cell lines and three additional lines to develop a database of responses of cancer cells to ionizing radiation. We compared clonogenic survival, apoptosis, and gene expression response by microarray. Although several studies have profiled relative basal gene expression in the NCI-60, this is the first comparison of large-scale gene expression changes in response to genotoxic stress. Twenty-two genes were differentially regulated in cells with low survival after 2-Gy γ-rays; 14 genes identified lines more sensitive to 8 Gy. Unlike reported basal gene expression patterns, changes in expression in response to radiation showed little tissue-of-origin effect, except for differentiating the lymphoblastoid cell lines from other cell types. Basal expression patterns, however, discriminated well between radiosensitive and more resistant lines, possibly being more informative than radiation response signatures. The most striking patterns in the radiation data were a set of genes up-regulated preferentially in the p53 wild-type lines and a set of cell cycle regulatory genes down-regulated across the entire NCI-60 panel. The response of those genes to γ-rays seems to be unaffected by the myriad of genetic differences across this diverse cell set; it represents the most penetrant gene expression response to ionizing radiation yet observed. [Cancer Res 2008;68(2):415–24]

Supplementary Table 4 from A Cell Proliferation and Chromosomal Instability Signature in Anaplastic Thyroid Carcinoma

Supplementary Table 5 from A Cell Proliferation and Chromosomal Instability Signature in Anaplastic Thyroid Carcinoma

Supplementary Table 1 from A Cell Proliferation and Chromosomal Instability Signature in Anaplastic Thyroid Carcinoma

Supplementary Table 2 from A Cell Proliferation and Chromosomal Instability Signature in Anaplastic Thyroid Carcinoma

Supplementary Figure 1 from Integrating Global Gene Expression and Radiation Survival Parameters across the 60 Cell Lines of the National Cancer Institute Anticancer Drug Screen

Here, we show that the anaplastic thyroid carcinoma (ATC) features the up-regulation of a set of genes involved in the control of cell cycle progression and chromosome segregation. This phenotype differentiates ATC from normal tissue and from well-differentiated papillary thyroid carcinoma. Transcriptional promoters of the ATC up-regulated genes are characterized by a modular organization featuring binding sites for E2F and NF-Y transcription factors and cell cycle–dependent element (CDE)/cell cycle gene homology region (CHR) cis-regulatory elements. Two protein kinases involved in cell cycle regulation, namely, Polo-like kinase 1 (PLK1) and T cell tyrosine kinase (TTK), are part of the gene set that is up-regulated in ATC. Adoptive overexpression of p53, p21 (CIP1/WAF1), and E2F4 down-regulated transcription from the PLK1 and TTK promoters in ATC cells, suggesting that these genes might be under the negative control of tumor suppressors of the p53 and pRB families. ATC, but not normal thyroid, cells depended on PLK1 for survival. RNAi-mediated PLK1 knockdown caused cell cycle arrest associated with 4N DNA content and massive mitotic cell death. Thus, thyroid cell anaplastic transformation is accompanied by the overexpression of a cell proliferation/genetic instability-related gene cluster that includes PLK1 kinase, which is a potential molecular target for ATC treatment. [Cancer Res 2007;67(21):10148–57]

Supplementary Data 1 from Integrating Global Gene Expression and Radiation Survival Parameters across the 60 Cell Lines of the National Cancer Institute Anticancer Drug Screen

Hot-iron disbudding of calves is a stressful and painful procedure and leaves a burn wound. Pain management procedures and the effects of hot-iron disbudding on biochemical markers of pain perception and stress response have been widely investigated in recent years. The aim of this study was to investigate the potential effects of pain management and age of the calf on the healing of burn wounds caused by disbudding. 327 healthy female German Holstein calves were included in this randomised, triple-blinded, prospective study. Calves were either disbudded at the age of four to 10 or 15 to 28 days using a gas-powered hot iron. Each calf was randomly allocated to one of nine possible treatment groups (BG). All calves received either the active ingredients to be tested (xylazine hydrochloride with 0.2 or 0.05 mg / kg body mass (BM) intramuscular for sedation, procaine hydrochloride (2 %) each 8 ml locally on both sides subcutaneously (SC) to the cornual nerves, meloxicam with 0,5 mg / kg BM SC for anti-inflammatory purposes) or an identical amount of saline solution (placebo). Calves in the group `thermE` and `ScheinE` received only placebo. In group `ScheinE` disbudding was simulated and in `thermE` it was carried out. The calves were clinically monitored starting one day before and ending 28 days after the procedure and the burn wounds were assessed. Both the rectal temperature and parameters of wound healing changed significantly during the study period and had characteristic profiles over time. Wound healing was not influenced by the different analgesic protocols, indicating that a multimodal analgesia does not pose a risk for wound healing after thermal disbudding. There were no observed differences between the age groups. The results of this study show, that disbudding of young calves and a multimodal pain management protocol does not affect wound healing in calves.Die thermische Zerstörung der Hornanlage (ZHA) von Kälbern stellt einen Eingriff dar, welcher mit Schmerz und Stress verbunden ist und eine Verbrennungswunde hinterlässt. Verschiedene Verfahren der Schmerzausschaltung sowie der Einfluss der thermischen ZHA auf Marker der Schmerz- und Stressreaktion wurden bereits evaluiert. Ziel der vorliegenden Studie war es zu prüfen, inwieweit das Schmerzmanagement selbst oder das Alter der Kälber die Wundheilung thermisch bedingter Wunden nach ZHA beeinflusst. In die randomisierte, dreifach verblindete, prospektive Studie wurden 327 gesunde, weibliche Deutsch-Holstein-Kälber einbezogen. Die ZHA erfolgte entweder zwischen dem vierten und 10. oder dem 15. und 28. Lebenstag mit einem gasbetriebenen Enthornungsgerät. Jedes Kalb wurde einer von neun Behandlungsgruppen (BG) zugelost. Alle Kälber bekamen entweder die zu testenden Wirkstoffe (Xylazinhydrochlorid mit 0,2 oder 0,05 mg/kg Körpermasse (KM) zur Sedation intramuskulär, Procainhydrochlorid (2 %) je 8 ml lokal beidseitig subkutan (SC) an die Rr. cornuales, Meloxicam mit 0,5 mg/kg KM SC zur Entzündungshemmung/Analgesie) oder eine identische Menge an isotoner Kochsalzlösung (Placebo) injiziert. Kälber der Gruppe `thermE` und `ScheinE` erhielten nur Placebo, bei `ScheinE` wurde die ZHA simuliert, bei `thermE` durchgeführt. Die Gruppe `Melo` erhielt nur Meloxicam, `LA` nur Procainhydrochlorid, `Melo-LA` Meloxicam + Procainhydrochlorid, `Seda 0,2` nur Xylazinhydrochlorid, `Seda 0,05-Melo` und `Seda 0,2-Melo ` (Xylazinhydrochlorid + Meloxicam), und `Seda 0,2-Melo-LA` alle zu testenden Wirkstoffe. Die Kälber wurden von einem Tag vor bis 28 Tage nach dem Eingriff klinisch überwacht und die Wunden befundet. Sowohl die inneren Körpertemperatur (IKT) als auch die Merkmale der Wundheilung unterschieden sich signifikant zwischen den einzelnen Untersuchungstagen und zeigten einen zeitlichen Verlauf. Die Wundheilung wurde durch die verschiedenen Analgetika oder deren Kombinationen nicht beeinflusst, eine multimodale Analgesie stellt demnach kein Risiko für die Wundheilung nach ZHA unter Praxisbedingungen dar. Zwischen den Altersgruppen wurden keine Unterschiede in der Wundheilung beobachtet. Die ZHA von Kälbern kann unter Praxisbedingungen demnach bereits früh und unter Ausschöpfung aller analgetischen Möglichkeiten erfolgen.L’ébourgeonnage thermique des veaux est une procédure stressante et douloureuse qui laisse une brûlure. Les procédures de gestion de la douleur et les effets de l’ébourgeonnage thermique sur les marqueurs biochimiques de la perception de la douleur et de la réponse au stress ont été largement étudiés ces dernières années. Le but de cette étude était d’étudier les effets potentiels de la gestion de la douleur et de l’âge du veau sur la cicatrisation des brûlures causées par l’ébourgeonnage. 327 veaux Holstein allemands femelles en bonne santé ont été inclus dans cette étude prospective randomisée en triple aveugle. Les veaux ont été soit ébourgeonnés à l’âge de 4 à 10 jours ou de 15 à 28 jours à l’aide d’un thermocautère à gaz. Chaque veau a été réparti au hasard dans l’un des neuf groupes de traitement possibles (BG). Tous les veaux ont reçu soit les principes actifs à tester (chlorhydrate de xylazine à 0,2 ou 0,05 mg/kg de masse corporelle (BM) par voie intramusculaire pour sédation, chlorhydrate de procaïne (2 %) 8 ml localement des deux côtés par voie sous-cutanée (SC) jusqu’aux nerfs cornuaux , méloxicam à 0,5 mg/kg de masse corporelle SC à visée anti-inflammatoire) ou une quantité identique de solution saline (placebo). Les veaux du groupe « thermE » et « ScheinE » ont reçu uniquement un placebo. Dans le groupe ‹ScheinE’ l’ébourgeonnage a été simulé et dans ‘thermE’ il a été réalisé. Le groupe « Melo » n’a reçu que du méloxicam, le groupe « LA » uniquement du chlorhydrate de procaïne, le grpoupe « Melo-LA » du méloxicam + chlorhydrate de procaïne, le groupe « Seda 0,2 » uniquement du chlorhydrate de xylazine, les groupes « Seda 0,05-Melo » et« Seda 0,2 -Melo » duchlorhydrate de xylazine et du méloxicam), et le groupe « Seda 0,2-Melo-LA » toutes les substances actives à tester. Les veaux ont été suivis cliniquement en commençant un jour avant et en terminant 28 jours après la procédure et les brûlures ont été évaluées. La température rectale et les paramètres de cicatrisation des plaies ont changé de manière significative au cours de la période d’étude et ont eu des profils caractéristiques au fil du temps. La cicatrisation n’a pas été influencée par les différents protocoles analgésiques, ce qui indique qu’une analgésie multimodale ne présente pas de risque quant à la cicatrisation après ébourgeonnage thermique. Aucune différence n’a été observée entre les groupes d’âge. Les résultats de cette étude montrent que l’ébourgeonnage des jeunes veaux et un protocole multimodal de gestion de la douleur n’affectent pas la cicatrisation des veaux.La decornazione termica dei vitelli è una procedura che è associata a dolore e stress e lascia una ferita da ustione. Diversi metodi di analgesia e l’influenza della decornazione termica sui marcatori del dolore e della risposta allo stress sono già stati valutati. Lo scopo del presente studio era quello di esaminare la misura in cui, la gestione del dolore stesso o l’età dei vitelli, influenzi la guarigione delle ferite provocate dopo la decornazione termica. Lo studio randomizzato, in triplo cieco e prospettico ha incluso 327 vitelli sani di razza Holstein tedesca. La decornazione è stata eseguita tra il quarto e il decimo o il quindicesimo e il ventottesimo giorno di vita utilizzando un dispositivo di decornazione a gas. Ogni vitello è stato assegnato a uno dei nove gruppi di trattamento (GT). A tutti i vitelli sono stati iniettati o gli agenti da testare (xilazina cloridrato a 0,2 o 0,05 mg/kg di massa corporea (MC) per via intramuscolare per la sedazione, procaina cloridrato (2 %) 8 ml ciascuno per via locale bilaterale sottocutanea (SC) ai rr. cornuales, meloxicam a 0,5 mg/kg KM SC per antinfiammatorio/analgesia) o una quantità identica di soluzione salina isotonica (placebo). I vitelli nei gruppi `thermE` e `ScheinE` hanno ricevuto solo placebo; la decornazione è stata simulata in `ScheinE` ed eseguita in `thermE`. Il gruppo `Melo` ha ricevuto solo meloxicam, `LA` solo procaina cloridrato, `Melo-LA` meloxicam + procaina cloridrato, `Seda 0,2` solo xilazina cloridrato, `Seda 0,05-Melo` e `Seda 0,2-Melo` (xilazina cloridrato + meloxicam), e `Seda 0,2-Melo-LA` tutti gli agenti da testare. I vitelli sono stati monitorati clinicamente da un giorno prima a 28 giorni dopo la procedura e sono state valutate le ferite. Sia la temperatura corporea interna (TCI) che le caratteristiche di guarigione della ferita differivano significativamente tra i giorni di studio e mostravano un andamento temporale. La guarigione della ferita non è stata influenzata dai diversi analgesici o dalle loro combinazioni; l’analgesia multimodale non rappresenta quindi un rischio per la guarigione della ferita dopo la decornazione in condizioni reali. Non sono state osservate differenze nella guarigione delle ferite tra i gruppi di età. Pertanto, la decornazione dei vitelli in condizioni reali può essere eseguita presto e con l’esaurimento di tutte le possibilità analgesiche.

Background Several studies have highlighted both the extreme anticancer effects of Cryptotanshinone (CT), a Stat3 crippling component from Salvia miltiorrhiza, as well as other STAT3 inhibitors to fight cancer. Methods Data presented in this experiment incorporates 2 years of in vitro studies applying a comprehensive live-cell drug-screening analysis of human and canine cancer cells exposed to CT at 20 μM concentration, as well as to other drug combinations. As previously observed in other studies, dogs are natural cancer models, given to their similarity in cancer genetics, epidemiology and disease progression compared to humans. Results Results obtained from several types of human and canine cancer cells exposed to CT and varied drug combinations, verified CT efficacy at combating cancer by achieving an extremely high percentage of apoptosis within 24 hours of drug exposure. Conclusions CT anticancer efficacy in various human and canine cancer cell lines denotes its ability to interact across different biological processes and cancer regulatory cell networks, driving inhibition of cancer cell survival.

Colorectal cancer (CRC) is one of the most prevalent types of cancer in the world and ranks second in cancer deaths in the US. Despite the recent improvements in screening and treatment, the number of deaths associated with CRC is still very significant. The complexities involved in CRC therapy stem from multiple oncogenic mutations and crosstalk between abnormal pathways. This calls for using advanced molecular genetics to understand the underlying pathway interactions responsible for this cancer. In this paper, we construct the CRC pathway from the literature and using an existing public dataset on healthy vs tumor colon cells, we identify the genes and pathways that are mutated and are possibly responsible for the disease progression. We then introduce drugs in the CRC pathway, and using a boolean modeling technique, we deduce the drug combinations that produce maximum cell death. Our theoretical simulations demonstrate the effectiveness of Cryptotanshinone, a traditional Chinese herb derivative, achieved by targeting critical oncogenic mutations and enhancing cell death. Finally, we validate our theoretical results using wet lab experiments on HT29 and HCT116 human colorectal carcinoma cell lines.

Colorectal cancer (CRC) is one of the most prevalent types of cancer in the world and ranks second in cancer deaths in the US. Despite the recent improvements in screening and treatment, the number of deaths associated with CRC is still very significant. The complexities involved in CRC therapy stem from multiple oncogenic mutations and crosstalk between abnormal pathways. This calls for using advanced molecular genetics to understand the underlying pathway interactions responsible for this cancer. In this paper, we construct the CRC pathway from the literature and using an existing public dataset on healthy vs tumor colon cells, we identify the genes/pathways that are mutated and are possibly responsible for the disease progression. We then introduce drugs in the CRC pathway, and using a boolean modeling technique, we deduce the drug combinations that produce maximum cell death. Our theoretical simulations demonstrate the effectiveness of Cryptotanshinone, a traditional Chinese herb derivative, achieved by targeting critical oncogenic mutations and enhancing cell death. Finally, we validate our theoretical results using wet lab experiments on HT29 and HCT116 human colorectal carcinoma cell lines.

Background: Osteosarcoma (OS) is the most common primary bone tumor in both humans and canines. This tumor has an aggressive course leading to the development of metastatic lesions in most patients diagnosed with this disease. Two new novel agents, MLN9708 and SH4-54, work as a proteasome inhibitor and a STAT3 inhibitor, respectively. Targets of these drugs have been shown to be overexpressed in OS in both species. Methods: Two human and two canine OS cell lines were exposed in vitro to both drugs alone and in combination. The number of cells undergoing apoptosis, as well as the number of cells capable of invasion through a matrigel basement membrane was evaluated after exposure to the drugs. Additionally, PCR and Western blots of downstream targets were evaluated. Finally, both drugs were tested against each cell line in an in vivo murine xenograft model. Results: All four cell lines were sensitive to MLN9708, one of the human cell lines and both canine cell lines were resistant to SH4-54. MLN9708 was also better at inhibiting invasion in three of the four cell lines. In the murine xenografts MLN9708 inhibited growth and metastasis in 143B (human OS) and the combination inhibited growth in the canine OS cell line (MCKOS). Conclusions: Though SH4-54 demonstrated robust cell killing in 143B in vitro, MLN9708 demonstrated broader activity across species for the treatment of OS. Further investigation into this drug is warranted as a treatment for OS. Combination of this drug with a STAT3 inhibitor may be worthwhile in canine OS.

BackgroundSeveral studies have highlighted both the extreme anticancer effects of Cryptotanshinone (CT), a Stat3 crippling component from Salvia miltiorrhiza, as well as other STAT3 inhibitors to fight cancer.MethodsData presented in this experiment incorporates 2 years of in vitro studies applying a comprehensive live-cell drug-screening analysis of human and canine cancer cells exposed to CT at 20 μM concentration, as well as to other drug combinations. As previously observed in other studies, dogs are natural cancer models, given to their similarity in cancer genetics, epidemiology and disease progression compared to humans.ResultsResults obtained from several types of human and canine cancer cells exposed to CT and varied drug combinations, verified CT efficacy at combating cancer by achieving an extremely high percentage of apoptosis within 24 hours of drug exposure.ConclusionsCT anticancer efficacy in various human and canine cancer cell lines denotes its ability to interact across different biological processes and cancer regulatory cell networks, driving inhibition of cancer cell survival.

In modern aircraft engines, the low-pressure compressor (LPC) is subjected to a flow characterized by strong wakes and secondary flows from the upstream fan. This concerns ultra-high bypass ratio (UHBR) turbofan engines, in particular. This paper presents the aerodynamic and aeroelastic sensitivities of parametric variations on the LPC, driven by the design considerations in the upstream fan. The goal of this investigation was to determine the influence of design-based geometry parameter variations on the LPC performance under realistic inlet flow distributions and the presence of an s-duct. Aerodynamic simulations are conducted at the design and off-design operating points with the fan outflow as the inlet boundary conditions. Based on the aerodynamic results, time-linearized unsteady simulations are conducted to evaluate the vibration amplitude at the resonance operating points. First, the bypass ratio is varied by reducing the channel height of the LPC. The LPC efficiency decreases by up to 1.7% due to the increase in blockage of the core flow. The forced response amplitude of the rotor decreases with increasing bypass ratio due to increased aerodynamic damping. Secondly, the fan cavity leakage flow is considered as it directly affects the near hub fan flow and thus the inflow of the LPC. This results in an increased total-pressure loss for the s-duct due to mixing losses. The additional mixing redistributes the flow at the s-duct exit leading to a total-pressure loss reduction of 4.3% in the first rotor at design point. This effect is altered at off-design conditions. The vibration amplitude at low speed resonance points is increased by 19% for the first torsion and 26% for second bending. Thirdly, sweep and lean are applied to the inlet guide vane (IGV) upstream of the LPC. Despite the s-duct and the variable inlet guide vane (VIGV) affecting the flow, the three-dimensional blade design achieves aerodynamic and aeroelastic improvements of rotor 1 at off-design. The total-pressure loss reduces by up to 18% and the resonance amplitude more than 10%. Only negligible improvements for rotor 1 are present at the design point. In a fourth step, the influence of axial gap size between the stator and the rotor rows in the LPC is examined in the range of small variations which shows no distinct aerodynamic and aeroelastic sensitivities. This finding not only supports previous studies, but it also suggests a correlation between mode shapes and locally increased excitaion with increasing axial gap size. As a result, potential design improvements in future fan-compressor design are suggested.

Background Metastatic melanoma is an aggressive form of skin cancer that evades various anti-cancer treatments including surgery, radio-,immuno- and chemo-therapy. TRAIL-induced apoptosis is a desirable method to treat melanoma since, unlike other treatments, it does not harm non-cancerous cells. The pro-inflammatory response to melanoma by nF κB and STAT3 pathways makes the cancer cells resist TRAIL-induced apoptosis. We show that due to to its dual action on DR5, a death receptor for TRAIL and on STAT3, Cryptotanshinone can be used to increase sensitivity to TRAIL. Methods The development of chemoresistance and invasive properties in melanoma cells involves several biological pathways. The key components of these pathways are represented as a Boolean network with multiple inputs and multiple outputs. Results The possible mutations in genes that can lead to cancer are captured by faults in the combinatorial circuit and the model is used to theoretically predict the effectiveness of Cryptotanshinone for inducing apoptosis in melanoma cell lines. This prediction is experimentally validated by showing that Cryptotanshinone can cause enhanced cell death in A375 melanoma cells. Conclusion The results presented in this paper facilitate a better understanding of melanoma drug resistance. Furthermore, this framework can be used to detect additional drug intervention points in the pathway that could amplify the action of Cryptotanshinone. Electronic supplementary material The online version of this article (10.1186/s12885-018-4756-0) contains supplementary material, which is available to authorized users.

Metformin, a widely used anti-diabetic drug, has recently been associated with inhibition of cell proliferation in multiple cancers. However, it is not clear if the reduction in proliferation on treatment with metformin is a result of cell death or slowdown in the rate of growth of cancer cells, because cell viability assays measure only the number of cells at the beginning and end of the experiment. The aim of this study is to utilize a fluorescent imaging technique to directly follow cell death overtime in order to investigate the effect of metformin on colorectal cancer cells HCT116 and SW480. Epifluorescent imaging analysis carried out using ImageXpress Micro XLS High-Content Imaging System show that there is no significant change in cell death observed in the cancer cell lines, as compared to the control, over multiple closely spaced time points, suggesting that metformin in pharmacological doses may not be an effective inducer of cell death in these colon cancer cell lines.

The landscape of translational research has been shifting toward drug combination therapies. Pairing of drugs allows for more types of drug interaction with cells. In order to accurately and comprehensively assess combinational drug efficacy, analytical methods capable of recognizing these alternative reactions will be required to prioritize those drug candidates having better chances of delivering appreciable therapeutic benefits. Traditional efficacy measures are primarily based on the “extent” of drug inhibition, which is the percentage of cells being killed after drug exposure. Here, we introduce a second dimension of evaluation criterion, speed of killing, based on a live cell imaging assay. This dynamic response trajectory approach takes advantage of both “extent” and “speed” information and uncovers synergisms that would otherwise be missed, while also generating hypotheses regarding important mechanistic modes of drug action.

Cell-based high-content screening (HCS) assays have become an increasingly attractive alternative to traditional in vitro and in vivo testing in pharmaceutical drug development and toxicological safety assessment. The time- and cost-effectiveness of HCS assays, combined with the organotypic nature of human induced pluripotent stem cell (iPSC)-derived cells, open new opportunities to employ physiologically relevant in vitro model systems to improve screening for potential chemical hazards. In this study, we used two human iPSC types, cardiomyocytes and hepatocytes, to test various high-content and molecular assay combinations for their applicability in a multiparametric screening format. Effects on cardiomyocyte beat frequency were characterized by calcium flux measurements for up to 90 min. Subsequent correlation with intracellular cAMP levels was used to determine if the effects on cardiac physiology were G-protein-coupled receptor dependent. In addition, we utilized high-content cell imaging to simultaneously determine cell viability, mitochondrial integrity, and reactive oxygen species (ROS) formation in both cell types. Kinetic analysis indicated that ROS formation is best detectable 30 min following initial treatment, whereas cytotoxic effects were most stable after 24 h. For hepatocytes, high-content imaging was also used to evaluate cytotoxicity and cytoskeletal integrity, as well as mitochondrial integrity and the potential for lipid accumulation. Lipid accumulation, a marker for hepatic steatosis, was most reliably detected 48 h following treatment with test compounds. Overall, our results demonstrate how a compendium of assays can be utilized for quantitative screening of chemical effects in iPSC cardiomyocytes and hepatocytes and enable rapid and cost-efficient multidimensional biological profiling of toxicity.

Background Cancer Tissue Heterogeneity is an important consideration in cancer research as it can give insights into the causes and progression of cancer. It is known to play a significant role in cancer cell survival, growth and metastasis. Determining the compositional breakup of a heterogeneous cancer tissue can also help address the therapeutic challenges posed by heterogeneity. This necessitates a low cost, scalable algorithm to address the challenge of accurate estimation of the composition of a heterogeneous cancer tissue. Methods In this paper, we propose an algorithm to tackle this problem by utilizing the data of accurate, but high cost, single cell line cell-by-cell observation methods in low cost aggregate observation method for heterogeneous cancer cell mixtures to obtain their composition in a Bayesian framework. Results The algorithm is analyzed and validated using synthetic data and experimental data. The experimental data is obtained from mixtures of three separate human cancer cell lines, HCT116 (Colorectal carcinoma), A2058 (Melanoma) and SW480 (Colorectal carcinoma). Conclusion The algorithm provides a low cost framework to determine the composition of heterogeneous cancer tissue which is a crucial aspect in cancer research.

Insensitivity to standard clinical interventions, including chemotherapy, radiotherapy, and tyrosine kinase inhibitor (TKI) treatment, remains a substantial hindrance towards improving the prognosis of patients with non–small cell lung cancer (NSCLC). The molecular mechanism of therapeutic resistance remains poorly understood. The TNF-like weak inducer of apoptosis (TWEAK)–FGF-inducible 14 (TNFRSF12A/Fn14) signaling axis is known to promote cancer cell survival via NF-κB activation and the upregulation of prosurvival Bcl-2 family members. Here, a role was determined for TWEAK–Fn14 prosurvival signaling in NSCLC through the upregulation of myeloid cell leukemia sequence 1 (MCL1/Mcl-1). Mcl-1 expression significantly correlated with Fn14 expression, advanced NSCLC tumor stage, and poor patient prognosis in human primary NSCLC tumors. TWEAK stimulation of NSCLC cells induced NF-κB–dependent Mcl-1 protein expression and conferred Mcl-1–dependent chemo- and radioresistance. Depletion of Mcl-1 via siRNA or pharmacologic inhibition of Mcl-1, using EU-5148, sensitized TWEAK-treated NSCLC cells to cisplatin- or radiation-mediated inhibition of cell survival. Moreover, EU-5148 inhibited cell survival across a panel of NSCLC cell lines. In contrast, inhibition of Bcl-2/Bcl-xL function had minimal effect on suppressing TWEAK-induced cell survival. Collectively, these results position TWEAK–Fn14 signaling through Mcl-1 as a significant mechanism for NSCLC tumor cell survival and open new therapeutic avenues to abrogate the high mortality rate seen in NSCLC. Implications: The TWEAK–Fn14 signaling axis enhances lung cancer cell survival and therapeutic resistance through Mcl-1, positioning both TWEAK–Fn14 and Mcl-1 as therapeutic opportunities in lung cancer. Mol Cancer Res; 12(4); 550–9. ©2014 AACR.

Gene set enrichment analysis (GSA) methods have been widely adopted by biological labs to analyze data and generate hypotheses for validation. Most of the existing comparison studies focus on whether the existing GSA methods can produce accurate P-values; however, practitioners are often more concerned with the correct gene-set ranking generated by the methods. The ranking performance is closely related to two critical goals associated with GSA methods: the ability to reveal biological themes and ensuring reproducibility, especially for small-sample studies. We have conducted a comprehensive simulation study focusing on the ranking performance of seven representative GSA methods. We overcome the limitation on the availability of real data sets by creating hybrid data models from existing large data sets. To build the data model, we pick a master gene from the data set to form the ground truth and artificially generate the phenotype labels. Multiple hybrid data models can be constructed from one data set and multiple data sets of smaller sizes can be generated by resampling the original data set. This approach enables us to generate a large batch of data sets to check the ranking performance of GSA methods. Our simulation study reveals that for the proposed data model, the Q2 type GSA methods have in general better performance than other GSA methods and the global test has the most robust results. The properties of a data set play a critical role in the performance. For the data sets with highly connected genes, all GSA methods suffer significantly in performance.

Vulvovaginal candidiasis (VVC) affects a significant number of women, especially in working age. In an estimated 75% of women an episode of acute vulvovaginal candidiasis occurs during lifetime and another 5–10% of women develop recurrent vulvovaginal candidiasis (RVVC). This is mainly characterized by intense burning, itching, pain, abnormal discharge, dyspareunia. Immune response to candidiasis is both cellular (CMI) (natural protection mechanisms) and humoral (antibody production). Understanding the principles of immunity in candidiasis is also important for development of candida vaccines.CANDIVAC contains lyophilized Candida lysate (C. albicans, C. krusei, C. glabrata) together with immunostimulatory bacterial strain of Propionibacterium acnes. The product is taken orally in capsules for 10 days followed by a 20-day pause. It is administered for 3 to 6 months. The product has been tested in a total of 75 women at the age of 18–45 years. In these women at least 4 episodes of vulvovaginal candidiasis have been microscopically or laboratory diagnosed during the last 12 months. Following CANDIVAC administration, statistically significant changes occurred in the evaluation of subjective and some objective criteria. The most important marker of product efficiency is a significant reduction in recurrence compared to the recent state. This criterion has a fundamental importance in patient satisfaction. Before medication the patients suffered from at least 4 attacks, while after medication an attack occurred in only 31% of women and more than 2 attacks in only 3% of treated women.Compromised balance of immune system plays a major role in recurrent vulvovaginal candidiasis. Specific oral product CANDIVAC, prepared from the most common strains of yeast infections, supports immune mechanisms, ensuring resistance of the human organism against yeasts. Its administration significantly prolongs remission, leads to a reduction in application of antimycotics and also changes properties of cellular and humoral immunity in medicated patients.

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, "organotypic" cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomic data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.

For science, theoretical or applied, to significantly advance, researchers must use the most appropriate mathematical methods. A century and a half elapsed between Newton's development of the calculus and Laplace's development of celestial mechanics. One cannot imagine the latter without the former. Today, more than three-quarters of a century has elapsed since the birth of stochastic systems theory. This article provides a perspective on the utilization of systems theory as the proper vehicle for the development of systems biology and its application to complex regulatory diseases such as cancer.

Background Most dynamical models for genomic networks are built upon two current methodologies, one process-based and the other based on Boolean-type networks. Both are problematic when it comes to experimental design purposes in the laboratory. The first approach requires a comprehensive knowledge of the parameters involved in all biological processes a priori, whereas the results from the second method may not have a biological correspondence and thus cannot be tested in the laboratory. Moreover, the current methods cannot readily utilize existing curated knowledge databases and do not consider uncertainty in the knowledge. Therefore, a new methodology is needed that can generate a dynamical model based on available biological data, assuming uncertainty, while the results from experimental design can be examined in the laboratory. Results We propose a new methodology for dynamical modeling of genomic networks that can utilize the interaction knowledge provided in public databases. The model assigns discrete states for physical entities, sets priorities among interactions based on information provided in the database, and updates each interaction based on associated node states. Whenever uncertainty in dynamics arises, it explores all possible outcomes. By using the proposed model, biologists can study regulation networks that are too complex for manual analysis. Conclusions The proposed approach can be effectively used for constructing dynamical models of interaction-based genomic networks without requiring a complete knowledge of all parameters affecting the network dynamics, and thus based on a small set of available data.

This paper proposes a framework to study the drug effect at the molecular level in order to address the following question of current interest in the drug community: Given a fixed total delivered drug, which is better, frequent small or infrequent large drug dosages? A hybrid system model is proposed to link the drug's pharmacokinetic and pharmacodynamic information, and allows the drug effects for different dosages and treatment schedules to be compared. A hybrid model facilitates the modeling of continuous quantitative changes that leads to discrete transitions. An optimal dosage-frequency regimen and the necessary and sufficient conditions for the drug to be effective are obtained analytically when the drug is designed to control a target gene. Then, we extend the analysis to the case where the target gene is part of a genetic regulatory network. A crucial observation is that there exists a "sweet spot," defined as the "drug efficacy region (DER)" in this paper, for certain dosage and frequency arrangements given the total delivered drug. This paper quantifies the therapeutic benefits of dosage regimen lying within the DER. Simulations are performed using MATLAB/SIMULINK to validate the analytical results.

Patients with cystic fibrosis periodically experience pulmonary exacerbations. Previous studies have noted that some patients' lung function (FEV(1)) does not improve with treatment.To determine the proportion of patients treated for a pulmonary exacerbation that does not recover to spirometric baseline, and to identify factors associated with the failure to recover to spirometric baseline.Cohort study using the Cystic Fibrosis Foundation Patient Registry from 2003-2006. We randomly selected one pulmonary exacerbation treated with intravenous antibiotics per patient and compared the best FEV(1) in the 3 months after treatment with the best FEV(1) in the 6 months before treatment. Recovery to baseline was defined as any FEV(1) in the 3 months after treatment that was greater than or equal to 90% of the baseline FEV(1). Multivariable logistic regression was used to estimate associations with the failure to recover to baseline FEV(1).Of 8,479 pulmonary exacerbations, 25% failed to recover to baseline FEV(1). A higher risk of failing to recover to baseline was associated with female sex; pancreatic insufficiency; being undernourished; Medicaid insurance; persistent infection with Pseudomonas aeruginosa, Burkholderia cepacia complex, or methicillin-resistant Staphylococcus aureus; allergic bronchopulmonary aspergillosis; a longer time since baseline spirometric assessment; and a larger drop in FEV(1) from baseline to treatment initiation.For a randomly selected pulmonary exacerbation, 25% of patients' pulmonary function did not recover to baseline after treatment with intravenous antibiotics. We identified factors associated with the failure to recover to baseline, allowing clinicians to identify patients who may benefit from closer monitoring and more aggressive treatment.

Objective To measure the abilities of the continuous measures of disease activity used in rheumatoid arthritis (RA) and the 3 versions of the Juvenile Arthritis Disease Activity Score (JADAS; based upon 10-, 27-, and 71-joint counts) to accurately classify the American College of Rheumatology (ACR) pediatric measures of response, flare, and inactive disease in polyarticular-course juvenile idiopathic arthritis (JIA). Methods We conducted a secondary analysis of a randomized trial of infliximab in polyarticular-course JIA. Disease activity was calculated at baseline and weeks 14, 28, and 52 using the Disease Activity Score (DAS), DAS in 28 joints, Simplified Disease Activity Index, Clinical Disease Activity Index, and JADAS. The ability of the RA measures and JADAS to classify each ACR pediatric measure, flare, and inactive disease was measured by areas under the receiver operating characteristic curve (AUCs). Positive predictive values (PPVs) for inactive disease were calculated. Results Data from 97 participants were available. The AUCs for the RA scores for each ACR pediatric measure were 0.73–0.89. The AUCs of the JADAS for the ACR pediatric measures were 0.75–0.92. The PPVs of the RA scores for inactive disease were 0.33–0.67. The PPVs of the JADAS for inactive disease were each 0.93. Based on the RA and JADAS scores, the percentage of visits misclassified as inactive disease ranged from 7–67%. Conclusion The RA measures and JADAS versions showed acceptable to excellent ability to classify participants for each pediatric outcome measure, but the clinical significance of differences between AUCs for these scores could not be assessed. Misclassification of active disease versus inactive disease by the RA and JADAS scores was not uncommon in this cohort.

This paper reports the development of a biodosimetry device suitable for rapidly measuring expression levels of a low-density gene set that can define radiation exposure, dose and injury in a public health emergency. The platform comprises a set of 14 genes selected on the basis of their abundance and differential expression level in response to radiation from an expression profiling series measuring 41,000 transcripts. Gene expression is analyzed through direct signal amplification using a quantitative Nuclease Protection Assay (qNPA). This assay can be configured as either a high-throughput microplate assay or as a handheld detection device for individual point-of-care assays. Recently, we were able to successfully develop the qNPA platform to measure gene expression levels directly from human whole blood samples. The assay can be performed with volumes as small as 30 microL of whole blood, which is compatible with collection from a fingerstick. We analyzed in vitro irradiated blood samples with qNPA. The results revealed statistically significant discrimination between irradiated and non-irradiated samples. These results indicate that the qNPA platform combined with a gene profile based on a small number of genes is a valid test to measure biological radiation exposure. The scalability characteristics of the assay make it appropriate for population triage. This biodosimetry platform could also be used for personalized monitoring of radiotherapy treatments received by patients.

Features for standard expression microarray and RNA-Seq classification are expression averages over collections of cells. Single cell provides expression measurements for individual cells in a collection of cells from a particular tissue sample. Hence, it can yield feature vectors consisting of higher order and mixed moments. This article demonstrates the advantage of using these expression moments in cancer-related classification. We use synthetic data generated from 2 real networks, the mammalian cell cycle network and a melanoma-related pathway network, and real single-cell data generated via fluorescent protein reporters from 2 cell lines, HT-29 and HCT-116. The networks consist of hidden binary regulatory networks with Gaussian observations. The steady-state distributions of both the original and mutated networks are found, and data are drawn from these for moment-based classification using the mean, variance, skewness, and mixed moments. For the real data, we only observe 1 gene at a time, so that only the mean, variance, and skewness are considered, the analysis being done for 2 genes, EGFR and ERRB2. For the synthetic data, classification improves as we move from just the mean to mean, variance, and skewness and then to these plus the mixed moments. Comparisons are done with 3, 4, or 5 features, using feature selection. Sample size effects are considered. For the real data, we only consider mean, variance, and skewness, with results improving when the higher order moments are used as features.

Human cancer cells typically harbour multiple chromosomal aberrations, nucleotide substitutions and epigenetic modifications that drive malignant transformation. The Cancer Genome Atlas ( TCGA) pilot project aims to assess the value of large- scale multi- dimensional analysis of these molecular characteristics in human cancer and to provide the data rapidly to the research community. Here we report the interim integrative analysis of DNA copy number, gene expression and DNA methylation aberrations in 206 glioblastomas - the most common type of primary adult brain cancer - and nucleotide sequence aberrations in 91 of the 206 glioblastomas. This analysis provides new insights into the roles of ERBB2, NF1 and TP53, uncovers frequent mutations of the phosphatidylinositol- 3- OH kinase regulatory subunit gene PIK3R1, and provides a network view of the pathways altered in the development of glioblastoma. Furthermore, integration of mutation, DNA methylation and clinical treatment data reveals a link between MGMT promoter methylation and a hypermutator phenotype consequent to mismatch repair deficiency in treated glioblastomas, an observation with potential clinical implications. Together, these findings establish the feasibility and power of TCGA, demonstrating that it can rapidly expand knowledge of the molecular basis of cancer.

Canalizing genes possess such broad regulatory power, and their action sweeps across a such a wide swath of processes that the full set of affected genes are not highly correlated under normal conditions. When not active, the controlling gene will not be predictable to any significant degree by its subject genes, either alone or in groups, since their behavior will be highly varied relative to the inactive controlling gene. When the controlling gene is active, its behavior is not well predicted by any one of its targets, but can be very well predicted by groups of genes under its control. To investigate this question, we introduce in this paper the concept of intrinsically multivariate predictive (IMP) genes, and present a mathematical study of IMP in the context of binary genes with respect to the coefficient of determination (CoD), which measures the predictive power of a set of genes with respect to a target gene. A set of predictor genes is said to be IMP for a target gene if all properly contained subsets of the predictor set are bad predictors of the target but the full predictor set predicts the target with great accuracy. We show that logic of prediction, predictive power, covariance between predictors, and the entropy of the joint probability distribution of the predictors jointly affect the appearance of IMP genes. In particular, we show that high-predictive power, small covariance among predictors, a large entropy of the joint probability distribution of predictors, and certain logics, such as XOR in the 2-predictor case, are factors that favor the appearance of IMP. The IMP concept is applied to characterize the behavior of the gene DUSP1, which exhibits control over a central, process-integrating signaling pathway, thereby providing preliminary evidence that IMP can be used as a criterion for discovery of canalizing genes.

High-throughput technologies for genomics provide tens of thousands of genetic measurements, for instance, gene-expression measurements on microarrays, and the availability of these measurements has motivated the use of machine learning (inference) methods for classification, clustering, and gene networks. Generally, a design method will yield a model that satisfies some model constraints and fits the data in some manner. On the other hand, a scientific theory consists of two parts: (1) a mathematical model to characterize relations between variables, and (2) a set of relations between model variables and observables that are used to validate the model via predictive experiments. Although machine learning algorithms are constructed to hopefully produce valid scientific models, they do not ipso facto do so. In some cases, such as classifier estimation, there is a well-developed error theory that relates to model validity according to various statistical theorems, but in others such as clustering, there is a lack of understanding of the relationship between the learning algorithms and validation. The issue of validation is especially problematic in situations where the sample size is small in comparison with the dimensionality (number of variables), which is commonplace in genomics, because the convergence theory of learning algorithms is typically asymptotic and the algorithms often perform in counter-intuitive ways when used with samples that are small in relation to the number of variables. For translational genomics, validation is perhaps the most critical issue, because it is imperative that we understand the performance of a diagnostic or therapeutic procedure to be used in the clinic, and this performance relates directly to the validity of the model behind the procedure. This paper treats the validation issue as it appears in two classes of inference algorithms relating to genomics – classification and clustering. It formulates the problem and reviews salient results.

The cell division cycle comprises a sequence of phenomena controlled by a stable and robust genetic network. We applied a probabilistic genetic network (PGN) to construct a hypothetical model with a dynamical behavior displaying the degree of robustness typical of the biological cell cycle. The structure of our PGN model was inspired in well-established biological facts such as the existence of integrator subsystems, negative and positive feedback loops, and redundant signaling pathways. Our model represents genes interactions as stochastic processes and presents strong robustness in the presence of moderate noise and parameters fluctuations. A recently published deterministic yeast cell-cycle model does not perform as well as our PGN model, even upon moderate noise conditions. In addition, self stimulatory mechanisms can give our PGN model the possibility of having a pacemaker activity similar to the observed in the oscillatory embryonic cell cycle.