Dataset Information

Zhu2015 - Combined gemcitabine and birinapant in pancreatic cancer cells - basic PD model

ABSTRACT: Zhu2015 - Combined gemcitabine and birinapant in pancreatic cancer cells - basic PD model Mathematical model to illustrate the effectiveness of combination chemotherapy involving gemcitabine and birinapant against pancreatic cancer. This model is described in the article: Mechanism-based mathematical modeling of combined gemcitabine and birinapant in pancreatic cancer cells. Zhu X, Straubinger RM, Jusko WJ. J Pharmacokinet Pharmacodyn 2015 Oct; 42(5): 477-496 Abstract: Combination chemotherapy is standard treatment for pancreatic cancer. However, current drugs lack efficacy for most patients, and selection and evaluation of new combination regimens is empirical and time-consuming. The efficacy of gemcitabine, a standard-of-care agent, combined with birinapant, a pro-apoptotic antagonist of Inhibitor of Apoptosis Proteins (IAPs), was investigated in pancreatic cancer cells. PANC-1 cells were treated with vehicle, gemcitabine (6, 10, 20 nM), birinapant (50, 200, 500 nM), and combinations of the two drugs. Temporal changes in cell numbers, cell cycle distribution, and apoptosis were measured. A basic pharmacodynamic (PD) model based on cell numbers, and a mechanism-based PD model integrating all measurements, were developed. The basic PD model indicated that synergistic effects occurred in both cell proliferation and death processes. The mechanism-based model captured key features of drug action: temporary cell cycle arrest in S phase induced by gemcitabine alone, apoptosis induced by birinapant alone, and prolonged cell cycle arrest and enhanced apoptosis induced by the combination. A drug interaction term Ψ was employed in the models to signify interactions of the combination when data were limited. When more experimental information was utilized, Ψ values approaching 1 indicated that specific mechanisms of interactions were captured better. PD modeling identified the potential benefit of combining gemcitabine and birinapant, and characterized the key interaction pathways. An optimal treatment schedule of pretreatment with gemcitabine for 24-48 h was suggested based on model predictions and was verified experimentally. This approach provides a generalizable modeling platform for exploring combinations of cytostatic and cytotoxic agents in cancer cell culture studies. This model is hosted on BioModels Database and identified by: BIOMD0000000668. To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

SUBMITTER: Vijayalakshmi Chelliah

PROVIDER: BIOMD0000000668 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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			Action	DRS
	BIOMD0000000668?filename=BIOMD0000000668-biopax2.owl	Owl
	BIOMD0000000668?filename=BIOMD0000000668-biopax3.owl	Owl
	BIOMD0000000668?filename=BIOMD0000000668-matlab.m	Other
	BIOMD0000000668?filename=BIOMD0000000668-octave.m	Other
	BIOMD0000000668?filename=BIOMD0000000668.m	Other

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Publications

Mechanism-based mathematical modeling of combined gemcitabine and birinapant in pancreatic cancer cells.

Zhu Xu X Straubinger Robert M RM Jusko William J WJ

Journal of pharmacokinetics and pharmacodynamics 20150808 5

Combination chemotherapy is standard treatment for pancreatic cancer. However, current drugs lack efficacy for most patients, and selection and evaluation of new combination regimens is empirical and time-consuming. The efficacy of gemcitabine, a standard-of-care agent, combined with birinapant, a pro-apoptotic antagonist of Inhibitor of Apoptosis Proteins (IAPs), was investigated in pancreatic cancer cells. PANC-1 cells were treated with vehicle, gemcitabine (6, 10, 20 nM), birinapant (50, 200, ...[more]

PMID: 26252969

Similar Datasets

Project description:Zhu2015 - combined gemcitabine and birinapant in pancreatic cancer cells - mechanistic PD model Mechanistic mathematical model to illustrate the effectiveness of combination chemotherapy involving gemcitabine and birinapant against pancreatic cancer. This model is described in the article: Mechanism-based mathematical modeling of combined gemcitabine and birinapant in pancreatic cancer cells. Zhu X, Straubinger RM, Jusko WJ. J Pharmacokinet Pharmacodyn 2015 Oct; 42(5): 477-496 Abstract: Combination chemotherapy is standard treatment for pancreatic cancer. However, current drugs lack efficacy for most patients, and selection and evaluation of new combination regimens is empirical and time-consuming. The efficacy of gemcitabine, a standard-of-care agent, combined with birinapant, a pro-apoptotic antagonist of Inhibitor of Apoptosis Proteins (IAPs), was investigated in pancreatic cancer cells. PANC-1 cells were treated with vehicle, gemcitabine (6, 10, 20 nM), birinapant (50, 200, 500 nM), and combinations of the two drugs. Temporal changes in cell numbers, cell cycle distribution, and apoptosis were measured. A basic pharmacodynamic (PD) model based on cell numbers, and a mechanism-based PD model integrating all measurements, were developed. The basic PD model indicated that synergistic effects occurred in both cell proliferation and death processes. The mechanism-based model captured key features of drug action: temporary cell cycle arrest in S phase induced by gemcitabine alone, apoptosis induced by birinapant alone, and prolonged cell cycle arrest and enhanced apoptosis induced by the combination. A drug interaction term Ψ was employed in the models to signify interactions of the combination when data were limited. When more experimental information was utilized, Ψ values approaching 1 indicated that specific mechanisms of interactions were captured better. PD modeling identified the potential benefit of combining gemcitabine and birinapant, and characterized the key interaction pathways. An optimal treatment schedule of pretreatment with gemcitabine for 24-48 h was suggested based on model predictions and was verified experimentally. This approach provides a generalizable modeling platform for exploring combinations of cytostatic and cytotoxic agents in cancer cell culture studies. This model is hosted on BioModels Database and identified by: BIOMD0000000669. To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Project description:During carcinoma progression, mesenchymal stromal cells (MSCs) become recruited to tumors and contribute to the pool of cancer-associated fibroblasts (CAFs). Sub-populations of CAFs, have diverse and incompletely understood effects on disease progression and resistance to therapy. Adipose stromal cells (ASCs), the MSCs from fat tissue increasingly recruited by carcinomas in the context of obesity, have been shown to support cancer progression. Here, the roles of perivascular CAFs expressing platelet-derived growth factor receptor beta (Pdgfrb) and of CAFs expressing non-glycanated decorin (ngDCN), a marker of ASCs, were analyzed. We used mice orthotopically grafted with pancreatic ductal adenocarcinoma (KPC) cells. Ablation of cells expressing thymidine kinase under the control of Pdgfrb promoter with ganciclovir resulted in suppression of primary pancreatic tumor growth. However, ablation Pdgfrb+ cells induced spontaneous metastases to the liver. For depletion of ngDCN+ cells, we used a hunter-killer peptide D-CAN, which has been previously reported to induce apoptosis of ASCs and CAFs in mouse models. Here, D-CAN also had a negative effect on pancreatic tumor growth, however, there was no significant effect on metastatic dissemination. Single cell RNA sequencing of tumors demonstrated that targeting of Pdgfrb+ and ngDCN+ stromal cells had distinct effects on sub-populations of CAFs. Endothelial cell and cancer cell survival was decreased by depletion of either Pdgfrb+ or ngDCN+ stroma. However, pathway analysis revealed that depletion of Pdgfrb+ and ngDCN+ stromal cells has different effects on the markers of cancer cell aggressiveness. D-CAN treatment, and to a less extent Pdgfrb+ cell ablation, suppressed macrophage M2 polarization and increased infiltration of cytotoxic T-lymphocytes. This observation, confirmed in the MyCap graft model of prostate cancer, suggested that ablation of ngDCN+ stroma should synergize with immune checkpoint inhibitors. We tested the effect of D-CAN on the efficacy of anti-PD-L1 antibody in the orthotopic KPC model. Compared to D-CAN and anti-PD-L1 antibody alone, combination treatment had a synergistic effect on tumor growth. Importantly, liver metastases were suppressed by the D-CAN / anti-PD-L1 antibody combination, but not by individual agents. We conclude that improved approaches to target mesenchymal stroma in tumors may be effective in combination with immunotherapy.

Project description:Erlotinib is a tyrosine kinase inhibitor (TKI) that is approved as a second-line monotherapy in patients with advanced non-small cell lung cancer (NSCLC). In these patients, erlotinib prolongs survival but its benefit remains modest since many tumors express wild-type EGF receptor (wtEGFR) lacking a TKI-sensitizing mutation, develop a second-site EGFR mutation, e.g., EGFR-L858R/T790M, or activate an alternate receptor tyrosine kinase, e.g., through MET amplification. To test potential drug combinations that could improve the efficacy of erlotinib, we combined erlotinib with quinacrine, which inhibits the FACT (facilitates chromatin transcription) complex that is required for nuclear factor-M-NM-:B (NF-M-NM-:B) transcriptional activity. In A549 (wtEGFR), H1975 (EGFR-L858R/T790M) and H1993 (MET amplification) NSCLC cells, the combination of erlotinib and quinacrine was highly synergistic, as quantified by Chou-Talalay combination indices. The combination inhibited colony formation, induced cell cycle arrest and apoptosis, and slowed xenograft tumor growth. Quinacrine decreased the level of active FACT subunit SSRP1 and suppressed NF-M-NM-:B-dependent luciferase activity. Knockdown of SSRP1 decreased cell growth and sensitized cells to erlotinib. Transcriptomic profiling showed that quinacrine, alone or in combination with erlotinib, significantly affected cell cycle-related genes that contain binding sites for transcription factors that regulate SSRP1 target genes. As potential biomarkers of drug synergy, we identified genes that were more strongly suppressed by the combination than by either single treatment, and whose increased expression predicted poorer survival in lung adenocarcinoma patients. Combination of quinacrine and erlotinib is synergistic in NSCLC through suppression of FACT, resulting in inhibition of cell cycle progression. RNA was isolated from cells treated with 1 M-NM-<M erlotinib, 3 M-NM-<M or 5 M-NM-<M quinacrine or a combination of both for 6, 12, 24, or 48 h using the RNeasy Mini Kit (QIAGEN) according to the manufacturerM-bM-^@M-^Ys instructions. Microarray analysis was performed using the Affymetrix Human Gene 2.1 ST Array at the Gene Expression & Genotyping Core Facility at Case Comprehensive Cancer Center. Raw CEL files were pre-processed using the Affymetrix Expression Console Software 1.30 with Robust Multi-array Average (RMA) normalization (background correction, quantile normalization and log2 transformation). Probes were annotated using the HuGene 2.1 st hg19 probeset annotation files downloaded from the Affymetrix website.