Using facial muscular movements to understand young children's emotion regulation and concurrent neural activation

Individual differences in young children's frustration responses set the stage for myriad developmental outcomes and represent an area of intense empirical interest. Emotion regulation is hypothesized to comprise the interplay of complex behaviors, such as facial expressions, and activation of concurrent underlying neural systems. At present, however, the literature has mostly examined children's observed emotion regulation behaviors and assumed underlying brain activation through separate investigations, resulting in theoretical gaps in our understanding of how children regulate emotion in vivo. Our goal was to elucidate links between young children's emotion regulation-related neural activation, facial muscular movements, and parent-rated temperamental emotion regulation. Sixty-five children (age 3-7) completed a frustration-inducing computer task while lateral prefrontal cortex (LPFC) activation and concurrent facial expressions were recorded. Negative facial expressions with eye constriction were inversely associated with both parent-rated temperamental emotion regulation and concurrent LPFC activation. Moreover, we found evidence that positive expressions with eye constriction during frustration may be associated with stronger LPFC activation. Results suggest a correspondence between facial expressions and LPFC activation that may explicate how children regulate emotion in real time.

Erratum: Atorvastatin exhibits anti-tumorigenic and anti-metastatic effects in ovarian cancer in vitro

[This corrects the article on p. 2478 in vol. 7, PMID: 29312801.].

Atorvastatin exhibits anti-tumorigenic and anti-metastatic effects in ovarian cancer in vitro

Ovarian cancer is the 8th most common cancer in women, and the 5th leading cause of cancer-related deaths among women in the United States. Statins have been shown to have promising anti-tumorigenic activity in many types of cancers. We sought to determine the effects of atorvastatin (ATO) on cell proliferation in ovarian cancer and identify the mechanisms by which ATO inhibits cell growth in this disease. ATO inhibited cell proliferation of both the Hey and SKOV3 ovarian cancer cells in a dose-dependent manner. The anti-proliferative activity of ATO in the ovarian cancer cell lines was associated with induction of apoptosis, autophagy, cellular stress and cell cycle G1 arrest via inhibition of AKT/mTOR and activation of the MAPK pathways. Moreover, ATO inhibited cell adhesion and invasion as well as decreased expression of VEGF and MMP9. c-Myc was downregulated in ovarian cancer cells exposed to ATO. Inhibition of c-Myc by JQ1 synergistically increased the sensitivity of ovarian cancer cells to ATO. This data suggests that ATO may have a therapeutic role in the treatment of ovarian cancer and warrant further exploration in clinical trials.

Phenformin has anti-tumorigenic effects in human ovarian cancer cells and in an orthotopic mouse model of serous ovarian cancer

Obesity and diabetes have been associated with increased risk and worse outcomes in ovarian cancer (OC). The biguanide metformin is used in the treatment of type 2 diabetes and is also believed to have anti-tumorigenic benefits. Metformin is highly hydrophilic and requires organic cation transporters (OCTs) for entry into human cells. Phenformin, another biguanide, was taken off the market due to an increased risk of lactic acidosis over metformin. However, phenformin is not reliant on transporters for cell entry; and thus, may have increased potency as both an anti-diabetic and anti-tumorigenic agent than metformin. Thus, our goal was to evaluate the effect of phenformin on established OC cell lines, primary cultures of human OC cells and in an orthotopic mouse model of high grade serous OC. In three OC cell lines, phenformin significantly inhibited cellular proliferation, induced cell cycle G1 arrest and apoptosis, caused cellular stress, inhibited adhesion and invasion, and activation of AMPK and inhibition of the mTOR pathway. Phenformin also exerted anti-proliferative effects in seven primary cell cultures of human OC. Lastly, phenformin inhibited tumor growth in an orthotopic mouse model of serous OC, coincident with decreased Ki-67 staining and phosphorylated-S6 expression and increased expression of caspase 3 and phosphorylated-AMPK. Our findings demonstrate that phenformin has anti-tumorigenic effects in OC as previously demonstrated by metformin but it is yet to be determined if it is superior to metformin for the potential treatment of this disease.

Dual inhibition of glycolysis and glutaminolysis as a therapeutic strategy in the treatment of ovarian cancer

Cancer cell metabolism is required to support the biosynthetic demands of cell growth and cell division, and to maintain reduction oxidaton (redox) homeostasis. This study was designed to test the effects of glucose and glutamine on ovarian cancer cell growth and explore the inter-relationship between glycolysis and glutaminolysis. The SKOV3, IGROV-1 and Hey ovarian cancer cell lines were assayed for glucose, pyruvate and glutamine dependence by analyzing cytotoxicity, cell cycle progression, apoptosis and ATP production. As determined by MTT assay, glucose stimulated cell growth while the combination of glucose, glutamine and pyruvate resulted in the greatest stimulation of cell proliferation. Furthermore, 2-deoxy-glucose (2-DG) and 3-bromopyruvate (3-BP) induced apoptosis, caused G1 phase cell cycle arrest and reduced glycolytic activity. Moreover, 2-DG in combination with a low dose of aminooxyacetate (AOA) synergistically increased the sensitivity to 2-DG in the inhibition of cell growth in the ovarian cancer cell lines. These studies suggest that dual inhibition of glycolysis and glutaminolysis may be a promising therapeutic strategy for the treatment of ovarian cancer.

Assessing the Impact of Tissue Target Concentration Data on Uncertainty in In Vivo Target Coverage Predictions

Understanding pharmacological target coverage is fundamental in drug discovery and development as it helps establish a sequence of research activities, from laboratory objectives to clinical doses. To this end, we evaluated the impact of tissue target concentration data on the level of confidence in tissue coverage predictions using a site of action (SoA) model for antibodies. By fitting the model to increasing amounts of synthetic tissue data and comparing the uncertainty in SoA coverage predictions, we confirmed that, in general, uncertainty decreases with longitudinal tissue data. Furthermore, a global sensitivity analysis showed that coverage is sensitive to experimentally identifiable parameters, such as baseline target concentration in plasma and target turnover half‐life and fixing them reduces uncertainty in coverage predictions. Overall, our computational analysis indicates that measurement of baseline tissue target concentration reduces the uncertainty in coverage predictions and identifies target‐related parameters that greatly impact the confidence in coverage predictions.

Glutaminase inhibitor compound 968 inhibits cell proliferation and sensitizes paclitaxel in ovarian cancer

Our overall goal was to investigate the anti-tumor activity of the glutaminase 1 (GLS1) Inhibitor compound 968 in ovarian cancer cells. The human ovarian cancer cell lines, HEY, SKOV3 and IGROV-1 were used. Cell proliferation was assessed by MTT assay after treatment with compound 968. Cell cycle progression and Annexin V expression were evaluated using Cellometer. Western blotting was performed to determine changes in GLS1, cellular stress and cell cycle checkpoints. Reactive oxygen species (ROS) and glutamate dehydrogenase (GDH) activity were assessed by ELISA assay. Compound 968 significantly inhibited cell proliferation and the expression of GLS1 in a dose-dependent manner in all three ovarian cancer cell lines. Compound 968 induced G1 phase cell cycle arrest and apoptosis. Treatment with compound 968 increased ROS levels and induced the protein expression of calnexin, binding immunoglobulin protein (BiP) and protein kinase RNA-like endoplasmic reticulum kinase (PERK). Deprivation of glutamine increased the sensitivity of cells to paclitaxel, and compound 968 sensitized cells to the anti-proliferative effects of paclitaxel. Compound 968 inhibited cell growth in ovarian cancer cells through induction of G1 phase cell cycle arrest, apoptosis and cellular stress, suggesting that targeting GLS1 provide a novel therapeutic strategy for ovarian cancer.

Buformin exhibits anti-proliferative and anti-invasive effects in endometrial cancer cells

OBJECTIVE

Biguanides are anti-diabetic drugs that are thought to have anti-tumorigenic effects. Most pre-clinical studies have focused on metformin for cancer treatment and prevention; however, buformin may be potentially more potent than metformin. Given this, our goal was to evaluate the effects of buformin on cell growth, adhesion and invasion in endometrial cancer cell lines.

METHODS

The ECC-1 and Ishikawa endometrial cancer cell lines were used. Cell proliferation was assessed by MTT assay. Apoptosis and cell cycle analysis was performed by FITC Annexin V assay and propidium iodide staining, respectively. Adhesion was analyzed using the laminin adhesion assay. Invasion was assessed using the transwell invasion assay. The effects of buformin on the AMPK/mTOR pathway were determined by Western immunoblotting.

RESULTS

Buformin and metformin inhibited cell proliferation in a dose-dependent manner in both endometrial cancer cell lines. IC50s were 1.4-1.6 mM for metformin and 8-150 μM for buformin. Buformin induced cell cycle G1 phase arrest in the ECC-1 cells and G2 phase arrest in the Ishikawa cells. For both ECC-1 and Ishikawa cells, treatment with buformin resulted in induction of apoptosis, reduction in adhesion and invasion, activation of AMPK and inhibition of phosphorylated-S6. Buformin potentiated the anti-proliferative effects of paclitaxel in both cell lines.

CONCLUSION

Buformin has significant anti-proliferative and anti-metastatic effects in endometrial cancer cells through modulation of the AMPK/mTOR pathway. IC50 values were lower for buformin than metformin, suggesting that buformin may be more potent for endometrial cancer treatment and worthy of further investigation.

Utility of a human FcRn transgenic mouse model in drug discovery for early assessment and prediction of human pharmacokinetics of monoclonal antibodies

Therapeutic antibodies continue to develop as an emerging drug class, with a need for preclinical tools to better predict in vivo characteristics. Transgenic mice expressing human neonatal Fc receptor (hFcRn) have potential as a preclinical pharmacokinetic (PK) model to project human PK of monoclonal antibodies (mAbs). Using a panel of 27 mAbs with a broad PK range, we sought to characterize and establish utility of this preclinical animal model and provide guidance for its application in drug development of mAbs. This set of mAbs was administered to both hemizygous and homozygous hFcRn transgenic mice (Tg32) at a single intravenous dose, and PK parameters were derived. Higher hFcRn protein tissue expression was confirmed by liquid chromatography-high resolution tandem mass spectrometry in Tg32 homozygous versus hemizygous mice. Clearance (CL) was calculated using non-compartmental analysis and correlations were assessed to historical data in wild-type mouse, non-human primate (NHP), and human. Results show that mAb CL in hFcRn Tg32 homozygous mouse correlate with human (r(2) = 0.83, r = 0.91, p < 0.01) better than NHP (r(2) = 0.67, r = 0.82, p < 0.01) for this dataset. Applying simple allometric scaling using an empirically derived best-fit exponent of 0.93 enabled the prediction of human CL from the Tg32 homozygous mouse within 2-fold error for 100% of mAbs tested. Implementing the Tg32 homozygous mouse model in discovery and preclinical drug development to predict human CL may result in an overall decreased usage of monkeys for PK studies, enhancement of the early selection of lead molecules, and ultimately a decrease in the time for a drug candidate to reach the clinic.

A mechanistic PK/PD model for two anti-IL13 antibodies explains the difference in total IL-13 accumulation observed in clinical studies

IMA-638 and IMA-026 are humanized IgG1 monoclonal antibodies (mAbs) that target non-overlapping epitopes of IL-13. Separate first-in-human single ascending dose studies were conducted for each mAb. These studies had similar study designs, but mild to moderate asthmatics were recruited for the IMA-638 study and healthy subjects were recruited for the IMA-026 study. IMA-638 and IMA-026 showed similar pharmacokinetic (PK) profiles, but very different total IL-13 (free and drug bound IL-13) profiles; free IL13 was not measured. IMA-026 treatment induced a dose-dependent accumulation of total IL-13, while IMA-638 treatment led to a much smaller accumulation without any clear dose-response. To understand the differences between the two total IL-13 profiles and to predict the free IL-13 profiles for each mAb treatment, a mechanistic PK/pharmacodynamic model was developed. PK-related parameters were first fit to the mean PK profiles of each mAb separately; thereafter, the target-related parameters were fit to both total IL-13 profiles simultaneously. The IL-13 degradation rate was assumed to be the same for asthma patients and healthy subjects. The model suggests that an approximately 100× faster elimination of IL-13-IMA-638 complex than IL-13-IMA-026 complex could be responsible for the differences observed in total IL-13 profiles for the two mAbs. Furthermore, the model predicts that IMA-638 administration results in greater and more prolonged free IL-13 inhibition than equivalent dosing of IMA-026 despite similar binding KD and PK profile. In conclusion, joint modeling of two similar molecules provided mechanistic insight that the elimination rate of mAb-target complex can regulate the degree of free target inhibition.

Glutamine promotes ovarian cancer cell proliferation through the mTOR/S6 pathway

Glutamine is one of the main nutrients used by tumor cells for biosynthesis. Therefore, targeted inhibition of glutamine metabolism may have anti-tumorigenic implications. In the present study, we aimed to evaluate the effects of glutamine on ovarian cancer cell growth. Three ovarian cancer cell lines, HEY, SKOV3, and IGROV-1, were assayed for glutamine dependence by analyzing cytotoxicity, cell cycle progression, apoptosis, cell stress, and glucose/glutamine metabolism. Our results revealed that administration of glutamine increased cell proliferation in all three ovarian cancer cell lines in a dose dependent manner. Depletion of glutamine induced reactive oxygen species and expression of endoplasmic reticulum stress proteins. In addition, glutamine increased the activity of glutaminase (GLS) and glutamate dehydrogenase (GDH) by modulating the mTOR/S6 and MAPK pathways. Inhibition of mTOR activity by rapamycin or blocking S6 expression by siRNA inhibited GDH and GLS activity, leading to a decrease in glutamine-induced cell proliferation. These studies suggest that targeting glutamine metabolism may be a promising therapeutic strategy in the treatment of ovarian cancer.

Evaluation of the antitumor effects of c-Myc-Max heterodimerization inhibitor 100258-F4 in ovarian cancer cells

Epithelial ovarian carcinoma is the most lethal gynecological cancer due to its silent onset and recurrence with resistance to chemotherapy. Overexpression of oncogene c-Myc is one of the most frequently encountered events present in ovarian carcinoma. Disrupting the function of c-Myc and its downstream target genes is a promising strategy for cancer therapy. Our objective was to evaluate the potential effects of small-molecule c-Myc inhibitor, 10058-F4, on ovarian carcinoma cells and the underlying mechanisms by which 10058-F4 exerts its actions. Using MTT assay, colony formation, flow cytometry and Annexin V FITC assays, we found that 10058-F4 significantly inhibited cell proliferation of both SKOV3 and Hey ovarian cancer cells in a dose dependent manner through induction of apoptosis and cell cycle G1 arrest. Treatment with 10058-F4 reduced cellular ATP production and ROS levels in SKOV3 and Hey cells. Consistently, primary cultures of ovarian cancer treated with 10058-F4 showed induction of caspase-3 activity and inhibition of cell proliferation in 15 of 18 cases. The response to 10058-F4 was independent the level of c-Myc protein over-expression in primary cultures of ovarian carcinoma. These novel findings suggest that the growth of ovarian cancer cells is dependent upon c-MYC activity and that targeting c-Myc-Max heterodimerization could be a potential therapeutic strategy for ovarian cancer.

Systems pharmacology of the nerve growth factor pathway: use of a systems biology model for the identification of key drug targets using sensitivity analysis and the integration of physiology and pharmacology

The nerve growth factor (NGF) pathway is of great interest as a potential source of drug targets, for example in the management of certain types of pain. However, selecting targets from this pathway either by intuition or by non-contextual measures is likely to be challenging. An alternative approach is to construct a mathematical model of the system and via sensitivity analysis rank order the targets in the known pathway, with respect to an endpoint such as the diphosphorylated extracellular signal-regulated kinase concentration in the nucleus. Using the published literature, a model was created and, via sensitivity analysis, it was concluded that, after NGF itself, tropomyosin receptor kinase A (TrkA) was one of the most sensitive druggable targets. This initial model was subsequently used to develop a further model incorporating physiological and pharmacological parameters. This allowed the exploration of the characteristics required for a successful hypothetical TrkA inhibitor. Using these systems models, we were able to identify candidates for the optimal drug targets in the known pathway. These conclusions were consistent with clinical and human genetic data. We also found that incorporating appropriate physiological context was essential to drawing accurate conclusions about important parameters such as the drug dose required to give pathway inhibition. Furthermore, the importance of the concentration of key reactants such as TrkA kinase means that appropriate contextual data are required before clear conclusions can be drawn. Such models could be of great utility in selecting optimal targets and in the clinical evaluation of novel drugs.

Dose selection based on physiologically based pharmacokinetic (PBPK) approaches

Physiologically based pharmacokinetic (PBPK) models are built using differential equations to describe the physiology/anatomy of different biological systems. Readily available in vitro and in vivo preclinical data can be incorporated into these models to not only estimate pharmacokinetic (PK) parameters and plasma concentration-time profiles, but also to gain mechanistic insight into compound properties. They provide a mechanistic framework to understand and extrapolate PK and dose across in vitro and in vivo systems and across different species, populations and disease states. Using small molecule and large molecule examples from the literature and our own company, we have shown how PBPK techniques can be utilised for human PK and dose prediction. Such approaches have the potential to increase efficiency, reduce the need for animal studies, replace clinical trials and increase PK understanding. Given the mechanistic nature of these models, the future use of PBPK modelling in drug discovery and development is promising, however some limitations need to be addressed to realise its application and utility more broadly.

Use of modelling and simulation techniques to support decision making on the progression of PF-04878691, a TLR7 agonist being developed for hepatitis C

AIM

To use non-linear mixed effects modelling and simulation techniques to predict whether PF-04878691, a toll-like receptor 7 (TLR7) agonist, would produce sufficient antiviral efficacy while maintaining an acceptable side effect profile in a 'proof of concept' (POC) study in chronic hepatitis C (HCV) patients.

METHODS

A population pharmacokinetic-pharmacodynamic (PKPD) model was developed using available 'proof of pharmacology' (POP) clinical data to describe PF-04878691 pharmacokinetics (PK) and its relationship to 2',5'-oligoadenylate synthetase (OAS; marker of pharmacology) and lymphocyte levels (marker of safety) following multiple doses in healthy subjects. A second model was developed to describe the relationship between change from baseline OAS expressed as fold change and HCV viral RNA concentrations using clinical data available in HCV patients for a separate compound, CPG-10101 (ACTILON™), a TLR9 agonist. Using these models the antiviral efficacy and safety profiles of PF-04878691 were predicted in HCV patients.

RESULTS

The population PKPD models described well the clinical data as assessed by visual inspection of diagnostic plots, visual predictive checks and precision of the parameter estimates. Using these relationships, PF-04878691 exposure and HCV viral RNA concentration was simulated in HCV patients receiving twice weekly administration for 4 weeks over a range of doses. The simulations indicated that significant reductions in HCV viral RNA concentrations would be expected at doses > 6 mg. However at these doses grade ≥ 3 lymphopenia was also predicted.

CONCLUSIONS

The model simulations indicate that PF-04878691 is unlikely to achieve POC criteria and support the discontinuation of this compound for the treatment of HCV.