scholarly journals T1000: A reduced toxicogenomics gene set for improved decision making

2019 ◽  
Author(s):  
Othman Soufan ◽  
Jessica Ewald ◽  
Charles Viau ◽  
Doug Crump ◽  
Markus Hecker ◽  
...  
Keyword(s):  
Dose Response ◽  
Gene Clusters ◽  
Gene Set ◽  
Chemical Hazards ◽  
Gene Sets ◽  
Toxicological Research ◽  
Multiple Species ◽  
Response Modeling

There is growing interest within regulatory agencies and toxicological research communities to develop, test, and apply new approaches, such as toxicogenomics, to more efficiently evaluate chemical hazards. Given the complexity of analyzing thousands of genes simultaneously, there is a need to identify reduced gene sets.Though several gene sets have been defined for toxicological applications, few of these were purposefully derived using toxicogenomics data. Here, we developed and applied a systematic approach to identify 1000 genes (called Toxicogenomics-1000 or T1000) highly responsive to chemical exposures. First, a co-expression network of 11,210genes was built by leveraging microarray data from the Open TG-GATEs program. This network was then re-weighted based on prior knowledge of their biological (KEGG, MSigDB) and toxicological (CTD) relevance. Finally, weighted correlation network analysis was applied to identify 258 gene clusters. T1000 was defined by selecting genes from each cluster that were most associated with outcome measures. For model evaluation, we compared the performance of T1000 to that of other gene sets (L1000, S1500, Genes selected by Limma, and random set) using two external datasets. Additionally, a smaller (T384) and a larger version (T1500) of T1000 were used for dose-response modeling to test the effect of gene set size. Our findings demonstrated that the T1000 gene set is predictive of apical outcomes across a range of conditions (e.g.,in vitroand in vivo, dose-response, multiple species, tissues, and chemicals), and generally performs as well, or better than other gene sets available.

scholarly journals T1000: a reduced gene set prioritized for toxicogenomic studies

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7975 ◽  
Author(s):  
Othman Soufan ◽  
Jessica Ewald ◽  
Charles Viau ◽  
Doug Crump ◽  
Markus Hecker ◽  
...  
Keyword(s):  
Dose Response ◽  
Gene Clusters ◽  
Gene Set ◽  
Chemical Hazards ◽  
Gene Sets ◽  
Toxicological Research ◽  
Multiple Species ◽  
Response Modeling

There is growing interest within regulatory agencies and toxicological research communities to develop, test, and apply new approaches, such as toxicogenomics, to more efficiently evaluate chemical hazards. Given the complexity of analyzing thousands of genes simultaneously, there is a need to identify reduced gene sets. Though several gene sets have been defined for toxicological applications, few of these were purposefully derived using toxicogenomics data. Here, we developed and applied a systematic approach to identify 1,000 genes (called Toxicogenomics-1000 or T1000) highly responsive to chemical exposures. First, a co-expression network of 11,210 genes was built by leveraging microarray data from the Open TG-GATEs program. This network was then re-weighted based on prior knowledge of their biological (KEGG, MSigDB) and toxicological (CTD) relevance. Finally, weighted correlation network analysis was applied to identify 258 gene clusters. T1000 was defined by selecting genes from each cluster that were most associated with outcome measures. For model evaluation, we compared the performance of T1000 to that of other gene sets (L1000, S1500, Genes selected by Limma, and random set) using two external datasets based on the rat model. Additionally, a smaller (T384) and a larger version (T1500) of T1000 were used for dose-response modeling to test the effect of gene set size. Our findings demonstrated that the T1000 gene set is predictive of apical outcomes across a range of conditions (e.g., in vitro and in vivo, dose-response, multiple species, tissues, and chemicals), and generally performs as well, or better than other gene sets available.

scholarly journals T1000: A reduced toxicogenomics gene set for improved decision making

2019 ◽  
Author(s):  
Othman Soufan ◽  
Jessica Ewald ◽  
Charles Viau ◽  
Doug Crump ◽  
Markus Hecker ◽  
...  
Keyword(s):  
Dose Response ◽  
Gene Clusters ◽  
Gene Set ◽  
Chemical Hazards ◽  
Gene Sets ◽  
Toxicological Research ◽  
Multiple Species ◽  
Response Modeling

There is growing interest within regulatory agencies and toxicological research communities to develop, test, and apply new approaches, such as toxicogenomics, to more efficiently evaluate chemical hazards. Given the complexity of analyzing thousands of genes simultaneously, there is a need to identify reduced gene sets.Though several gene sets have been defined for toxicological applications, few of these were purposefully derived using toxicogenomics data. Here, we developed and applied a systematic approach to identify 1000 genes (called Toxicogenomics-1000 or T1000) highly responsive to chemical exposures. First, a co-expression network of 11,210genes was built by leveraging microarray data from the Open TG-GATEs program. This network was then re-weighted based on prior knowledge of their biological (KEGG, MSigDB) and toxicological (CTD) relevance. Finally, weighted correlation network analysis was applied to identify 258 gene clusters. T1000 was defined by selecting genes from each cluster that were most associated with outcome measures. For model evaluation, we compared the performance of T1000 to that of other gene sets (L1000, S1500, Genes selected by Limma, and random set) using two external datasets. Additionally, a smaller (T384) and a larger version (T1500) of T1000 were used for dose-response modeling to test the effect of gene set size. Our findings demonstrated that the T1000 gene set is predictive of apical outcomes across a range of conditions (e.g.,in vitroand in vivo, dose-response, multiple species, tissues, and chemicals), and generally performs as well, or better than other gene sets available.

scholarly journals Predicting the in vivo developmental toxicity of benzo[a]pyrene (BaP) in rats by an in vitro–in silico approach

2021 ◽  
Author(s):  
Danlei Wang ◽  
Maartje H. Rietdijk ◽  
Lenny Kamelia ◽  
Peter J. Boogaard ◽  
Ivonne M. C. M. Rietjens
Keyword(s):  
Dose Response ◽  
In Silico ◽  
Response Curve ◽  
Developmental Toxicity ◽  
Toxicity Testing ◽  
Maximal Effect ◽  
Blood Concentrations ◽  
Reverse Dosimetry

AbstractDevelopmental toxicity testing is an animal-intensive endpoints in toxicity testing and calls for animal-free alternatives. Previous studies showed the applicability of an in vitro–in silico approach for predicting developmental toxicity of a range of compounds, based on data from the mouse embryonic stem cell test (EST) combined with physiologically based kinetic (PBK) modelling facilitated reverse dosimetry. In the current study, the use of this approach for predicting developmental toxicity of polycyclic aromatic hydrocarbons (PAHs) was evaluated, using benzo[a]pyrene (BaP) as a model compound. A rat PBK model of BaP was developed to simulate the kinetics of its main metabolite 3-hydroxybenzo[a]pyrene (3-OHBaP), shown previously to be responsible for the developmental toxicity of BaP. Comparison to in vivo kinetic data showed that the model adequately predicted BaP and 3-OHBaP blood concentrations in the rat. Using this PBK model and reverse dosimetry, a concentration–response curve for 3-OHBaP obtained in the EST was translated into an in vivo dose–response curve for developmental toxicity of BaP in rats upon single or repeated dose exposure. The predicted half maximal effect doses (ED50) amounted to 67 and 45 mg/kg bw being comparable to the ED50 derived from the in vivo dose–response data reported for BaP in the literature, of 29 mg/kg bw. The present study provides a proof of principle of applying this in vitro–in silico approach for evaluating developmental toxicity of BaP and may provide a promising strategy for predicting the developmental toxicity of related PAHs, without the need for extensive animal testing.

scholarly journals NR5A2 transcriptional activation by BRD4 promotes pancreatic cancer progression by upregulating GDF15

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Feng Guo ◽  
Yingke Zhou ◽  
Hui Guo ◽  
Dianyun Ren ◽  
Xin Jin ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cancer Cells ◽  
Cancer Progression ◽  
Transcriptional Activation ◽  
Ductal Adenocarcinoma ◽  
Pancreatic Cancer Cells ◽  
Gene Sets ◽  
And Migration

AbstractNR5A2 is a transcription factor regulating the expression of various oncogenes. However, the role of NR5A2 and the specific regulatory mechanism of NR5A2 in pancreatic ductal adenocarcinoma (PDAC) are not thoroughly studied. In our study, Western blotting, real-time PCR, and immunohistochemistry were conducted to assess the expression levels of different molecules. Wound-healing, MTS, colony formation, and transwell assays were employed to evaluate the malignant potential of pancreatic cancer cells. We demonstrated that NR5A2 acted as a negative prognostic biomarker in PDAC. NR5A2 silencing inhibited the proliferation and migration abilities of pancreatic cancer cells in vitro and in vivo. While NR5A2 overexpression markedly promoted both events in vitro. We further identified that NR5A2 was transcriptionally upregulated by BRD4 in pancreatic cancer cells and this was confirmed by Chromatin immunoprecipitation (ChIP) and ChIP-qPCR. Besides, transcriptome RNA sequencing (RNA-Seq) was performed to explore the cancer-promoting effects of NR5A2, we found that GDF15 is a component of multiple down-regulated tumor-promoting gene sets after NR5A2 was silenced. Next, we showed that NR5A2 enhanced the malignancy of pancreatic cancer cells by inducing the transcription of GDF15. Collectively, our findings suggest that NR5A2 expression is induced by BRD4. In turn, NR5A2 activates the transcription of GDF15, promoting pancreatic cancer progression. Therefore, NR5A2 and GDF15 could be promising therapeutic targets in pancreatic cancer.

scholarly journals Physiologically based kinetic modelling based prediction of in vivo rat and human acetylcholinesterase (AChE) inhibition upon exposure to diazinon

2021 ◽  
Author(s):  
Shensheng Zhao ◽  
Sebastiaan Wesseling ◽  
Bert Spenkelink ◽  
Ivonne M. C. M. Rietjens
Keyword(s):  
Dose Response ◽  
Kinetic Modelling ◽  
Ache Inhibition ◽  
Response Curves ◽  
Alternative Testing ◽  
Dose Response Curves ◽  
Physiologically Based Kinetic Modelling ◽  
Point Of Departure

AbstractThe present study predicts in vivo human and rat red blood cell (RBC) acetylcholinesterase (AChE) inhibition upon diazinon (DZN) exposure using physiological based kinetic (PBK) modelling-facilitated reverse dosimetry. Due to the fact that both DZN and its oxon metabolite diazoxon (DZO) can inhibit AChE, a toxic equivalency factor (TEF) was included in the PBK model to combine the effect of DZN and DZO when predicting in vivo AChE inhibition. The PBK models were defined based on kinetic constants derived from in vitro incubations with liver fractions or plasma of rat and human, and were used to translate in vitro concentration–response curves for AChE inhibition obtained in the current study to predicted in vivo dose–response curves. The predicted dose–response curves for rat matched available in vivo data on AChE inhibition, and the benchmark dose lower confidence limits for 10% inhibition (BMDL10 values) were in line with the reported BMDL10 values. Humans were predicted to be 6-fold more sensitive than rats in terms of AChE inhibition, mainly because of inter-species differences in toxicokinetics. It is concluded that the TEF-coded DZN PBK model combined with quantitative in vitro to in vivo extrapolation (QIVIVE) provides an adequate approach to predict RBC AChE inhibition upon acute oral DZN exposure, and can provide an alternative testing strategy for derivation of a point of departure (POD) in risk assessment.

STATEMENT BY COMMITTEE ON FETUS AND NEWBORN

PEDIATRICS ◽  
1961 ◽  
Vol 28 (4) ◽  
pp. 678-678
Author(s):  
Keyword(s):  
Dose Response ◽  
Animal Species ◽  
Older Children ◽  
Human Species ◽  
Basic Premise ◽  
Newborn Animal ◽  
Physical Size ◽  
Human Adults

IT IS A BASIC PREMISE of pediatrics that physical size is not the most important difference between children and adults. There is increasing awareness that it is also necessary to make more than a quantitative distinction between infants and children. The fetus and the newborn infant often behave so differently as to warrant consideration as separate categories of the human species. This necessitates re-evaluation of the effects of drugs independently in each category of the human so that they may be used safely. Existing drugs and agents that are developed in the future for use in the fetus and in infants must be subjected to more extensive preclinical investigation than is being carried out at the present time. The pharmacologic responses of the immature human may differ greatly both quantitatively and qualitatively from those of the adult. As a result, data obtained from tests in mature animals and human adults or older children cannot be accepted as a satisfactory basis for recommendations concerning the fetus and infant. The pharmacologic properties of drugs should be studied in vitro and in vivo in the fetus and newborn animal and compared with those in the adult of the same animal species. Of particular importance would be a knowledge of the LD50, dose response, metabolism, and distribution and disposition of the drug.

Abstract 14532: Computational Drug Repurposing Identifies a Piperlongumine Analog That Controls a Gstp1-iscu Pathogenic Axis in Pulmonary Hypertension

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Jimin Yang
Keyword(s):  
Drug Repurposing ◽  
Gene Clusters ◽  
Loss Of Function ◽  
Sequencing Data ◽  
Glutathione S Transferase ◽  
Computational Screening ◽  
Therapeutic Development ◽  
Pulmonary Arterial

Background and Hypothesis: Pulmonary arterial hypertension (PAH) is an incurable vascular disease for which chemotherapies are being considered for therapeutic development. There is no method reported to date for effective computational screening of these drugs for this disease. Big data analyses that leverage the molecular parallels between cancer and PH may define novel pathogenic mechanisms and facilitate repurposing of chemotherapies for PAH. More specifically, while functional deficiency of the iron-sulfur (Fe-S) biogenesis gene ISCU and oxidative metabolism in human pulmonary arterial endothelial cells (PAECs) is known to drive PAH, the pathogenic regulation of ISCU is not fully defined, and no tailored drugs have been identified to bolster ISCU activity. Methods and Results: We applied a computational algorithm EDDY (Evaluating Differential DependencY), which analyzes RNA sequencing data from 810 cancer cell lines exposed to 368 small molecules, in order to identify chemotherapeutics that depended upon rewired PH-related gene clusters. The top ranked drug was a piperlongumine (PL) analog (BRD2889) that was predicted to extensively rewire dependencies across PH gene clusters, mediated by ISCU. In vitro, coupling gain- and loss-of-function analyses of GSTP1 with BRD2889 exposure in PAECs, we found that BRD2889 inhibits glutathione S-transferase P1 (GSTP1), an enzyme which in turn catalyzes ISCU glutathionylation and increases its stability in hypoxia. Consequently, BRD2889 and GSTP1 knockdown phenocopy one another by increasing Fe-S-dependent Complex I activity and mitochondrial oxygen consumption while ameliorating pathogenic apoptosis. Consistent with these computational and in vitro results, in a mouse model of PAH (IL-6 transgenic mice in hypoxia), BRD2889 improved hemodynamic and molecular disease manifestations in vivo. Conclusions: Using a novel computational platform, we identified a coordinated connection between BRD342289 and GSTP1-ISCU axis, crucial to PAEC metabolism. This study offers insight to fundamental PH pathobiology and sets the stage for accelerated repurposing of chemotherapies such as BRD342289 in PH.

Histamine tachyphylaxis in canine airways despite prostaglandin synthesis inhibition

1988 ◽  
Vol 65 (5) ◽  
pp. 1944-1949 ◽  
Author(s):  
P. J. Antol ◽  
S. J. Gunst ◽  
R. E. Hyatt
Keyword(s):  
Smooth Muscle ◽  
Dose Response ◽  
Prostaglandin Synthesis ◽  
Response Curves ◽  
Synthesis Inhibition ◽  
High Concentrations ◽  
Alpha Chloralose ◽  
Prostaglandin Synthesis Inhibitors

Tachyphylaxis to aerosolized histamine was studied in dogs anesthetized with thiamylal after pretreatment with prostaglandin synthesis inhibitors. Three consecutive histamine dose-response curves were obtained in nine dogs pretreated with 5 mg/kg indomethacin; two of these nine were also pretreated with 10 mg/kg indomethacin. Seven of the nine dogs were pretreated with 4 mg/kg sodium meclofenamate; four of these seven were also pretreated with 12 mg/kg. All dogs had tachyphylaxis at high concentrations of histamine regardless of inhibitor used. Pretreatment with indomethacin while the dogs were under alpha-chloralose-urethan anesthesia gave similar results. Histamine tachyphylaxis was also studied both in the presence and in the absence of indomethacin in tracheal smooth muscle strips obtained from seven additional dogs. A decrease in the median effective dose to histamine was observed in the indomethacin-treated strips, but tachyphylaxis to histamine remained. We conclude that prostaglandin synthesis inhibition does not reverse histamine tachyphylaxis either in vivo or in vitro. Thus the mechanism of histamine tachyphylaxis remains unexplained.

Histamine H2-receptor of human and rabbit parietal cells

1987 ◽  
Vol 253 (4) ◽  
pp. G497-G501 ◽  
Author(s):  
R. Leth ◽  
B. Elander ◽  
U. Haglund ◽  
L. Olbe ◽  
E. Fellenius
Keyword(s):  
Dose Response ◽  
In Vivo Model ◽  
Response Curves ◽  
Gastric Glands ◽  
Histamine H2 Receptor ◽  
Receptor Affinity ◽  
H2 Receptor ◽  
Dose Response Curves

The histamine H2-receptor on the human parietal cell has been characterized by using dose-response curves and the negative logarithm of the molar concentration of an antagonist (pA2) analyses of cimetidine antagonism of betazole, histamine, and impromidine stimulation in isolated human and rabbit gastric glands. To evaluate the in vitro results, betazole-stimulated gastric acid secretion with and without cimetidine was also studied in healthy subjects. In the in vivo model, individual dose-response curves were shifted to the right with increasing cimetidine concentrations, but this was counteracted by increasing betazole doses, indicating competitive, reversible antagonism. The pA2 values ranged from 6.1 to 6.3. In isolated human gastric glands, impromidine was shown to be eight times more potent than histamine, indicating higher receptor affinity, but the maximally stimulated aminopyrine accumulation was the same as for histamine, and the pA2 values for cimetidine antagonism did not differ significantly, i.e., 5.7 (histamine) and 6.1 (impromidine). In isolated rabbit gastric glands, cimetidine inhibited the histamine- and impromidine-stimulated response with pA2 values of 6.0 and 7.3, respectively. Impromidine was shown to be approximately 100 times more potent than in human gastric glands, whereas histamine had the same potency. This confirms the role of the histamine H2-receptor and suggests a difference between the species concerning receptor affinity.

Sign in / Sign up

Export Citation Format

Share Document