ArticleCancer research2012
Combinatorial chemotherapeutic efficacy in non-Hodgkin lymphoma can be predicted by a signaling model of CD20 pharmacodynamics.
Article in Cancer research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Population-based meta-analysis of bortezomib exposure-response relationships in multiple myeloma patients.Journal of pharmacokinetics and pharmacodynamics · 2020Pooled it
- Systemic Exposure of Rituximab Increased by Ibrutinib: Pharmacokinetic Results and Modeling Based on the HELIOS Trial.Pharmaceutical research · 2019Trial
- Network-Based Systems Analysis Explains Sequence-Dependent Synergism of Bortezomib and Vorinostat in Multiple Myeloma.The AAPS journal · 2021Article
- Development, Validation, and Comparison of Two Mass Spectrometry Methods (LC-MS/HRMS and LC-MS/MS) for the Quantification of Rituximab in Human Plasma.Molecules (Basel, Switzerland) · 2021Article
- Sequential Exposure of Bortezomib and Vorinostat is Synergistic in Multiple Myeloma Cells.Pharmaceutical research · 2017Article
- Review
- Array of translational systems pharmacodynamic models of anti-cancer drugs.Journal of pharmacokinetics and pharmacodynamics · 2016Review
- Feedback control indirect response models.Journal of pharmacokinetics and pharmacodynamics · 2016Article
- Biomarker- versus drug-driven tumor growth inhibition models: an equivalence analysis.Journal of pharmacokinetics and pharmacodynamics · 2015Article
- Mechanism-based mathematical modeling of combined gemcitabine and birinapant in pancreatic cancer cells.Journal of pharmacokinetics and pharmacodynamics · 2015Article
- Logic-Based and Cellular Pharmacodynamic Modeling of Bortezomib Responses in U266 Human Myeloma Cells.The Journal of pharmacology and experimental therapeutics · 2015Article
- Model-Based Design of a Decision Tree for Treating HER2+ Cancers Based on Genetic and Protein Biomarkers.CPT: pharmacometrics & systems pharmacology · 2015Article
- Developing Exposure/Response Models for Anticancer Drug Treatment: Special Considerations.CPT: pharmacometrics & systems pharmacology · 2015Article
- FLT3 and CDK4/6 inhibitors: signaling mechanisms and tumor burden in subcutaneous and orthotopic mouse models of acute myeloid leukemia.Journal of pharmacokinetics and pharmacodynamics · 2014Article
- Network-based approaches in drug discovery and early development.Clinical pharmacology and therapeutics · 2013Review
- Using network biology to bridge pharmacokinetics and pharmacodynamics in oncology.CPT: pharmacometrics & systems pharmacology · 2013Article
- Antibody therapy of pediatric B-cell lymphoma.Frontiers in oncology · 2013Article
- Intracellular-signaling tumor-regression modeling of the pro-apoptotic receptor agonists dulanermin and conatumumab.Journal of pharmacokinetics and pharmacodynamics · 2012Article
- Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Combination chemotherapy represents the standard-of-care for non-Hodgkin lymphoma. However, the development of new therapeutic regimens is empirical and this approach cannot be used prospectively to identify novel or optimal drug combinations. Quantitative system pharmacodynamic models could promote the discovery and development of combination regimens based upon first principles. In this study, we developed a mathematical model that integrates temporal patterns of drug exposure, receptor occupancy, and signal transduction to predict the effects of the CD20 agonist rituximab in combination with rhApo2L/TNF-related apoptosis inducing ligand or fenretinide, a cytotoxic retinoid, upon growth kinetics in non-Hodgkin lymphoma xenografts. The model recapitulated major regulatory mechanisms, including target-mediated disposition of rituximab, modulation of proapoptotic intracellular signaling induced by CD20 occupancy, and the relative efficacy of death receptor isoforms. The multiscale model coupled tumor responses to individual anticancer agents with their mechanisms of action in vivo, and the changes in Bcl-xL and Fas induced by CD20 occupancy were linked to explain the synergy of these drugs. Tumor growth profiles predicted by the model agreed with cell and xenograft data, capturing the apparent pharmacologic synergy of these agents with fidelity. Together, our findings provide a mechanism-based platform for exploring new regimens with CD20 agonists.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.