Semi-Mechanism-Based Pharmacokinetic/Pharmacodynamic Model for the Combination Use of Dexamethasone and Gemcitabine in Breast Cancer

An integrated PK/PD model investigating the impact of tumor size and systemic safety on animal survival in SW1990 pancreatic cancer xenograft

Survival is one of the most important endpoints in cancer therapy, and parametric survival analysis could comprehensively reveal the overall result of disease progression, drug efficacy, toxicity as well as their interactions. In this study we investigated the efficacy and toxicity of dexamethasone (DEX) combined with gemcitabine (GEM) in pancreatic cancer xenograft. Nude mice bearing SW1990 pancreatic cancer cells derived tumor were treated with DEX (4 mg/kg, i.g.) and GEM (15 mg/kg, i.v.) alone or in combination repeatedly (QD, Q3D, Q7D) until the death of animal or the end of study. Tumor volumes and net body weight (NBW) were assessed every other day. Taking NBW as a systemic safety indicator, an integrated pharmacokinetic/pharmacodynamic (PK/PD) model was developed to quantitatively describe the impact of tumor size and systemic safety on animal survival. The PK/PD models with time course data for tumor size and NBW were established, respectively, in a sequential manner; a parametric time-to-event (TTE) model was also developed based on the longitudinal PK/PD models to describe the survival results of the SW1990 tumor-bearing mice. These models were evaluated and externally validated. Only the mice with good tumor growth inhibition and relatively stable NBW had an improved survival result after DEX and GEM combination therapy, and the simulations based on the parametric TTE model showed that NBW played more important role in animals' survival compared with tumor size. The established model in this study demonstrates that tumor size was not always the most important reason for cancer-related death, and parametric survival analysis together with safety issues was also important in the evaluation of oncology therapies in preclinical studies.

A Novel Integrated Pharmacokinetic-Pharmacodynamic Model to Evaluate Combination Therapy and Determine In Vivo Synergism

Understanding pharmacokinetic (PK)-pharmacodynamic (PD) relationships is essential in translational research. Existing PK-PD models for combination therapy lack consideration of quantitative contributions from individual drugs, whereas interaction factor is always assigned arbitrarily to one drug and overstretched for the determination of in vivo pharmacologic synergism. Herein, we report a novel generic PK-PD model for combination therapy by considering apparent contributions from individual drugs coadministered. Doxorubicin (Dox) and sorafenib (Sor) were used as model drugs whose PK data were obtained in mice and fit to two-compartment model. Xenograft tumor growth was biphasic in mice, and PD responses were described by three-compartment transit models. This PK-PD model revealed that Sor (contribution factor = 1.62) had much greater influence on overall tumor-growth inhibition than coadministered Dox (contribution factor = 0.644), which explains the mysterious clinical findings on remarkable benefits for patients with cancer when adding Sor to Dox treatment, whereas there were none when adding Dox to Sor therapy. Furthermore, the combination index method was integrated into this predictive PK-PD model for critical determination of in vivo pharmacologic synergism that cannot be correctly defined by the interaction factor in conventional models. In addition, this new PK-PD model was able to identify optimal dosage combination (e.g., doubling experimental Sor dose and reducing Dox dose by 50%) toward much greater degree of tumor-growth inhibition (>90%), which was consistent with stronger synergy (combination index = 0.298). These findings demonstrated the utilities of this new PK-PD model and reiterated the use of valid method for the assessment of in vivo synergism. SIGNIFICANCE STATEMENT: A novel pharmacokinetic (PK)-pharmacodynamic (PD) model was developed for the assessment of combination treatment by considering contributions from individual drugs, and combination index method was incorporated to critically define in vivo synergism. A greater contribution from sorafenib to tumor-growth inhibition than that of coadministered doxorubicin was identified, offering explanation for previously inexplicable clinical observations. This PK-PD model and strategy shall have broad applications to translational research on identifying optimal dosage combinations with stronger synergy toward improved therapeutic outcomes.

Dexamethasone enhances the antitumor efficacy of Gemcitabine by glucocorticoid receptor signaling

Gemcitabine (Gem) is currently used as the first-line therapy for liver and pancreatic cancer but has limited efficacy in most cases. Dexamethasone (Dex) have been applied as a chemoprotectant and chemosensitizer in cancer chemotherapy. This study further explored the potential of combination of Gem and Dex and tested the hypothesis that glucocorticoid receptor signaling is essential for the synergistic antitumor activity. In the HepG2 and AsPC-1 xenograft models, the combination treatment showed a significantly synergistic antitumor activity. Immunohistochemistry of post-treatment tumors showed a significant decrease in proliferation and angiogenesis as compared to either of the treatments alone. Dex alone and the combination with Gem inhibited the expression of glucocorticoid receptor. The combination of Dex and Gem showed synergistic cytotoxicity in cell lines in vitro. The antiproliferative synergism is prevented by used glucocorticoid receptor (GR) small interfering RNA, demonstrating that the glucocorticoid receptor is required for the antiproliferative synergism of Gem and Dex. The inhibition of glucocorticoid receptor signaling pathway and induction of apoptosis via activation of caspases 3, 8 and 9, PARP, contributed to the synergistic effect of this combination therapy. These results demonstrate that Dex could potentiate the antitumor efficacy of Gem. The synergistic antitumor activity of the combination of Dex and Gem was through glucocorticoid receptor signaling. Taken together, a combination of Dex and Gem shows a significant synergistic antitumor activity and lesser toxicity both in vitro and in vivo and could be a combination chemotherapy for the treatment of highly expression of glucocorticoid receptor patients.

Preclinical PK/PD model for the combinatorial use of dexamethasone and sulpiride in the treatment of breast cancer

Previous studies show that dopamine D₂-like receptor (D2DR) antagonist sulpiride (SUL) enhances the antitumor efficacy of dexamethasone (DEX) in drug-resistant breast cancer involving cancer stem-like cells (CSCs). In this study, we investigated the pharmacokinetic (PK) properties of SUL in nude mice and developed a semi-mechanism PK/PD model to quantitatively characterize the synergistic effect of DEX and SUL in preclinical breast cancer xenografts. After nude mice received oral administration of a single dose of SUL (50 mg/kg, ig), plasma concentrations were assessed using LC-MS/MS. A two-compartment model with double first-order absorption rate was developed to describe the PK profiles of SUL. The pharmacodynamic (PD) study was conducted in nude mice bearing human breast cancer MCF-7/Adr xenografts, which received oral administration of DEX (1, 8 mg·kg⁻¹·d⁻¹) or SUL (25, 50 mg·kg⁻¹·d⁻¹) alone or in various combination. Tumor volumes were measured every other day. The PK model of SUL as well as that of DEX with a time-dependent clearance were integrated into the final PK/PD model both using Hill’s function, where DEX exerted its antitumor efficacy by inhibiting the proliferation of tumor cells, and SUL enhanced DEX responses by decreasing the sensitivity parameter EC₅₀. The PK/PD model was evaluated and subjected external validation. Finally, simulations were performed to predict the antitumor efficacy of DEX combined with SUL under various dose regimens, where changing dosing frequency of SUL had little effect, while the antitumor efficacy was predicted to be improved when DEX was given more frequently. The established PK/PD model in this study quantitatively characterizes the antitumor efficacy of the DEX combined with SUL as well as their synergism, and the simulations could provide reference for dose optimization of the combination in future studies.

Pharmacokinetic/Pharmacodynamic Modeling of the Anti-Cancer Effect of Dexamethasone in Pancreatic Cancer Xenografts and Anticipation of Human Efficacious Doses

Dexamethasone (DEX), a synthetic glucocorticoid, exhibited anti-cancer efficacy in pancreatic xenografts derived from patient tumor tissue or cancer cell lines. The aim of this study was to establish pharmacokinetic/pharmacodynamic (PK/PD) models to quantitatively characterize the inhibitory effect of DEX on tumor growth as well as its discrepancy among 3 xenograft models. Data of tumor growth profiles were collected from a patient-derived xenograft (PDX) model in NOD/SCID mice and 2 cell line-derived (PANC-1 and SW1990) xenograft models in BALB/c nude mice. Empirical PK/PD models were developed to establish mathematical relationships between plasma concentration of DEX and tumor growth dynamics after integrating PK parameters extracted from literature. Drug effect in each model was well described by a linear inhibitory function with a potency factor of 4.67, 3.14, and 2.35 L/mg for PDX, PANC-1, and SW1990 xenograft, respectively. Human efficacious doses of DEX were preliminarily predicted through model-based simulation, and 60% tumor growth inhibition at clinical exposure corresponded to a daily dose range of 26-52 mg intravenously. This modeling work quantified the preclinical anti-cancer effect of DEX and demonstrated the feasibility of its medication in pancreatic cancer, which would be conductive to future translational research.

Gemcitabine induced cytotoxicity, DNA damage and hepatic injury in laboratory mice

The present study was conducted to demonstrate cytotoxicity, apoptosis and hepatic damage induced by gemcitabine in laboratory mice. Animals were treated with a single dose of gemcitabine (415 mg/kg body wt), equivalent to a human therapeutic dose, and sacrificed after 1, 2 and 3 weeks. A significant decrease in mean body weight and absolute liver weight was registered. The levels of alkaline phosphatase (ALP), aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were increased as a result of this induced stress. Various structural changes were observed in the liver tissue of treated mice, as evident in the histological sections. Specifically, gemcitabine exposure was able to induce apoptosis in liver cells, and the incidence of TUNEL positive liver cells was increased compared to the control group. DNA fragmentation appeared on agarose gel and flow cytometry analysis confirmed the induction of apoptosis. These findings in gemcitabine-treated animal tissues suggest that inhibition or disruption of cells' DNA synthesis may be the mechanism by which this drug induces toxicity in the animal body.

Time-dependent pharmacokinetics of dexamethasone and its efficacy in human breast cancer xenograft mice: a semi-mechanism-based pharmacokinetic/pharmacodynamic model

Dexamethasone (DEX) is the substrate of CYP3A. However, the activity of CYP3A could be induced by DEX when DEX was persistently administered, resulting in auto-induction and time-dependent pharmacokinetics (pharmacokinetics with time-dependent clearance) of DEX. In this study we investigated the pharmacokinetic profiles of DEX after single or multiple doses in human breast cancer xenograft nude mice and established a semi-mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) model for characterizing the time-dependent PK of DEX as well as its anti-cancer effect. The mice were orally given a single or multiple doses (8 mg/kg) of DEX, and the plasma concentrations of DEX were assessed using LC-MS/MS. Tumor volumes were recorded daily. Based on the experimental data, a two-compartment model with first order absorption and time-dependent clearance was established, and the time-dependence of clearance was modeled by a sigmoid E_max equation. Moreover, a semi-mechanism-based PK/PD model was developed, in which the auto-induction effect of DEX on its metabolizing enzyme CYP3A was integrated and drug potency was described using an E_max equation. The PK/PD model was further used to predict the drug efficacy when the auto-induction effect was or was not considered, which further revealed the necessity of adding the auto-induction effect into the final PK/PD model. This study established a semi-mechanism-based PK/PD model for characterizing the time-dependent pharmacokinetics of DEX and its anti-cancer effect in breast cancer xenograft mice. The model may serve as a reference for DEX dose adjustments or optimization in future preclinical or clinical studies.

Dopamine D2 receptor antagonist sulpiride enhances dexamethasone responses in the treatment of drug-resistant and metastatic breast cancer

Recent evidence shows that dopamine D2-like receptor (D2DR) antagonists, such as trifluoperazine and thioridazine, are effective for cancer therapy and inhibition of cancer stem-like cells (CSCs). In this study, we investigated the anti-cancer effects of combination therapy of dexamethasone (DEX) and sulpiride (SUL), an atypical antipsychotic, against drug-resistant and metastatic breast cancers and further explored the underlying mechanisms. Oral administration of SUL (25, 100 mg·kg^-1·d^-1) alone did not inhibit the tumor growth in human breast cancer MCF-7/Adr xenograft model, but dose-dependently decreased the proportion of CSCs in vitro and in vivo. In contrast, combination therapy of SUL (50 mg·kg^-1·d^-1) and DEX (8 mg·kg^-1·d^-1) markedly suppressed the tumor growth in MCF-7/Adr xenograft model with little systemic toxicity and lung metastasis in murine metastatic breast cancer 4T1 xenograft model. Among the metastasis-associated biomarkers analyzed, the combination therapy significantly decreased the levels of MMP-2, but increased E-cadherin levels in 4T1 xenograft tumors. Moreover, the combination therapy significantly inhibited the cell colony formation, migration and invasion of 4T1 and human breast cancer MDA-MB-231 cells in vitro. Addition of a specific D2DR agonist 7-OH-DPAT to the combination therapy reversed the enhanced anti-cancer effects in vivo and CSC population loss in tumor tissues. Our data demonstrate that SUL remarkably enhances the efficacy of DEX in the treatment of drug-resistant and metastatic breast cancer via the antagonism of D2DR, which might result from the eradication of CSCs.

Mathematical model on Alzheimer's disease

Background

Alzheimer disease (AD) is a progressive neurodegenerative disease that destroys memory and cognitive skills. AD is characterized by the presence of two types of neuropathological hallmarks: extracellular plaques consisting of amyloid β-peptides and intracellular neurofibrillary tangles of hyperphosphorylated tau proteins. The disease affects 5 million people in the United States and 44 million world-wide. Currently there is no drug that can cure, stop or even slow the progression of the disease. If no cure is found, by 2050 the number of alzheimer’s patients in the U.S. will reach 15 million and the cost of caring for them will exceed $ 1 trillion annually.

Results

The present paper develops a mathematical model of AD that includes neurons, astrocytes, microglias and peripheral macrophages, as well as amyloid β aggregation and hyperphosphorylated tau proteins. The model is represented by a system of partial differential equations. The model is used to simulate the effect of drugs that either failed in clinical trials, or are currently in clinical trials.

Conclusions

Based on these simulations it is suggested that combined therapy with TNF- α inhibitor and anti amyloid β could yield significant efficacy in slowing the progression of AD.

Dexamethasone suppresses the growth of human non-small cell lung cancer via inducing estrogen sulfotransferase and inactivating estrogen

AIM

Dexamethasone (DEX) is a widely used synthetic glucocorticoid, which has shown anti-cancer efficacy and anti-estrogenic activity. In this study we explored the possibility that DEX might be used as an endocrine therapeutic agent to treat human non-small cell lung cancer (NSCLC).

METHODS

The viability and proliferation of human NSCLC cell lines A549 and H1299 were assessed in vitro. Anti-tumor action was also evaluated in A549 xenograft nude mice treated with DEX (2 or 4 mg·kg(-1)·d(-1), ig) or the positive control tamoxifen (50 mg·kg(-1)·d(-1), ig) for 32 d. The expression of estrogen sulfotransferase (EST) in tumor cells and tissues was examined. The intratumoral estrogen levels and uterine estrogen responses were measured.

RESULTS

DEX displayed mild cytotoxicity to the NSCLC cells (IC50 >500 μmol/L) compared to tamoxifen (IC50 <50 μmol/L), but it was able to inhibit the cell proliferation at low micromolar ranges. Furthermore, DEX (0.1-10 μmol/L) dose-dependently up-regulated EST expression in the cells, and inhibited the cell migration in vitro. Triclosan, a sulfation inhibitor, was able to diminish DEX-caused inhibition on the cell viability. In A549 xenograft nude mice, DEX or tamoxifen administration remarkably suppressed the tumor growth. Moreover, DEX administration dose-dependently increased EST expression in tumor tissues, and reduced intratumoral estrogen levels as well as the volumes and weights of uterine.

CONCLUSION

DEX suppresses the growth of A549 xenograft tumors via inducing EST and decreasing estradiol levels in tumor tissues, suggesting that DEX may be used as anti-estrogenic agent for the treatment of NSCLC.