ArticleNanoscale2016
Enhanced performance of macrophage-encapsulated nanoparticle albumin-bound-paclitaxel in hypo-perfused cancer lesions.
Article in Nanoscale, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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
37 citing papers in PubMed, 62 citations in OpenAlex.
- Nanomedicine beyond carriers - devices, cells & living therapeutics.Biomedical microdevices · 2026Review
- Advancing Tumor Treatment Through Artificial Intelligence and Mathematical Modeling: A Comprehensive Review.Health science reports · 2026Article
- Spatio-Temporal Dynamics of MBulletin of mathematical biology · 2025Article
- Realizing the potential of nanomedicines to treat breast cancer liver metastasis.Nanomedicine (London, England) · 2025Article
- Preclinical advance in nanoliposome-mediated photothermal therapy in liver cancer.Lipids in health and disease · 2025Review
- Macrophage Checkpoint Nanoimmunotherapy Has the Potential to Reduce Malignant Progression in BioengineeredACS applied bio materials · 2024Article
- Characterization of the Breast Cancer Liver Metastasis Microenvironment via Machine Learning Analysis of the Primary Tumor Microenvironment.Cancer research communications · 2024Article
- Macrophage-Based Microrobots for Anticancer Therapy: Recent Progress and Future Perspectives.Biomimetics (Basel, Switzerland) · 2023Review
- Evaluation of Lung Cancer Patient Response to First-Line Chemotherapy by Integration of Tumor Core Biopsy Metabolomics with Multiscale Modeling.Annals of biomedical engineering · 2023Article
- Recent progress of macrophage vesicle-based drug delivery systems.Drug delivery and translational research · 2022Review
- Modeling of Tumor Growth with Input from Patient-Specific Metabolomic Data.Annals of biomedical engineering · 2022Article
- The impact of tumor associated macrophages on tumor biology under the lens of mathematical modelling: A review.Frontiers in immunology · 2022Review
- Modeling of tumor response to macrophage and T lymphocyte interactions in the liver metastatic microenvironment.Cancer immunology, immunotherapy : CII · 2021Article
- Chemically Engineered Immune Cell-Derived Microrobots and Biomimetic Nanoparticles: Emerging Biodiagnostic and Therapeutic Tools.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2021Review
- Impact of tumor-parenchyma biomechanics on liver metastatic progression: a multi-model approach.Scientific reports · 2021Article
- Macrophage-Targeted Lung Delivery of Dexamethasone Improves Pulmonary Fibrosis Therapy via Regulating the Immune Microenvironment.Frontiers in immunology · 2021Article
- Modeling immune cell behavior across scales in cancer.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- Multi-objective optimization of tumor response to drug release from vasculature-bound nanoparticles.Scientific reports · 2020Article
- Nonlinear response to cancer nanotherapy due to macrophage interactions revealed by mathematical modeling and evaluated in a murine model via CRISPR-modulated macrophage polarization.Cancer immunology, immunotherapy : CII · 2020Article
- Modeling of Nanotherapy Response as a Function of the Tumor Microenvironment: Focus on Liver Metastasis.Frontiers in bioengineering and biotechnology · 2020Review
Corrections and comments
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Authors and funding
12 authors at 4 institutions in 2 countries.
Funding
Abstract
Hypovascularization in tumors such as liver metastases originating from breast and other organs correlates with poor chemotherapeutic response and higher mortality. Poor prognosis is linked to impaired transport of both low- and high-molecular weight drugs into the lesions and to high washout rate. Nanoparticle albumin-bound-paclitaxel (nAb-PTX) has demonstrated benefits in clinical trials when compared to paclitaxel and docetaxel. However, its therapeutic efficacy for breast cancer liver metastasis is disappointing. As macrophages are the most abundant cells in the liver tumor microenvironment, we design a multistage system employing macrophages to deliver drugs into hypovascularized metastatic lesions, and perform in vitro, in vivo, and in silico evaluation. The system encapsulates nAb-PTX into nanoporous biocompatible and biodegradable multistage vectors (MSV), thus promoting nAb-PTX retention in macrophages. We develop a 3D in vitro model to simulate clinically observed hypo-perfused tumor lesions surrounded by macrophages. This model enables evaluation of nAb-PTX and MSV-nab PTX efficacy as a function of transport barriers. Addition of macrophages to this system significantly increases MSV-nAb-PTX efficacy, revealing the role of macrophages in drug transport. In the in vivo model, a significant increase in macrophage number, as compared to unaffected liver, is observed in mice, confirming the in vitro findings. Further, a mathematical model linking drug release and retention from macrophages is implemented to project MSV-nAb-PTX efficacy in a clinical setting. Based on macrophage presence detected via liver tumor imaging and biopsy, the proposed experimental/computational approach could enable prediction of MSV-nab PTX performance to treat metastatic cancer in the liver.
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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.