ArticleProceedings of the National Academy of Sciences of the United States of America2019
Assessing micrometastases as a target for nanoparticles using 3D microscopy and machine learning.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. 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
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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.
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Who cites it
37 citing papers in PubMed, 92 citations in OpenAlex.
- Machine learning reshapes the paradigm of nanomedicine research.Acta pharmaceutica Sinica. B · 2026Review
- Nanoparticles reach metastatic tumours via enhanced permeability of adjacent vessels.Nature nanotechnology · 2026Article
- Review
- Machine Learning-Enhanced Nanoparticle Design for Precision Cancer Drug Delivery.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Advances in multimodal imaging techniques in nanomedicine: enhancing drug delivery precision.RSC advances · 2025Review
- Designing nanotheranostics with machine learning.Nature nanotechnology · 2024Review
- The Role of Artificial Intelligence and Machine Learning in Accelerating the Discovery and Development of Nanomedicine.Pharmaceutical research · 2024Article
- Rational strategies for improving the efficiency of design and discovery of nanomedicines.Nature communications · 2024Review
- Histopathological biomarkers for predicting the tumour accumulation of nanomedicines.Nature biomedical engineering · 2024Article
- Predicting tissue distribution and tumor delivery of nanoparticles in mice using machine learning models.Journal of controlled release : official journal of the Controlled Release Society · 2024Article
- Innovative optical imaging strategies for monitoring immunotherapy in the tumor microenvironments.Cancer medicine · 2024Review
- Three-dimensional imaging of upper tract urothelial carcinoma improves diagnostic yield and accuracy.JCI insight · 2024Article
- Computational Frontiers in Aptamer-Based Nanomedicine for Precision Therapeutics: A Comprehensive Review.ACS omega · 2024Review
- Bridging Smart Nanosystems with Clinically Relevant Models and Advanced Imaging for Precision Drug Delivery.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
- Nanotechnology's frontier in combatting infectious and inflammatory diseases: prevention and treatment.Signal transduction and targeted therapy · 2024Review
- Deep learning for automatic organ and tumor segmentation in nanomedicine pharmacokinetics.Theranostics · 2024Article
- Tissue clearing and immunostaining to visualize the spatial organization of vasculature and tumor cells in mouse liver.Frontiers in oncology · 2023Article
- Principles of Nanoparticle Delivery to Solid Tumors.BME frontiers · 2023Review
- Review
- 3D imaging for driving cancer discovery.The EMBO journal · 2022Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Metastasis of solid tumors is a key determinant of cancer patient survival. Targeting micrometastases using nanoparticles could offer a way to stop metastatic tumor growth before it causes excessive patient morbidity. However, nanoparticle delivery to micrometastases is difficult to investigate because micrometastases are small in size and lie deep within tissues. Here, we developed an imaging and image analysis workflow to analyze nanoparticle-cell interactions in metastatic tumors. This technique combines tissue clearing and 3D microscopy with machine learning-based image analysis to assess the physiology of micrometastases with single-cell resolution and quantify the delivery of nanoparticles within them. We show that nanoparticles access a higher proportion of cells in micrometastases (50% nanoparticle-positive cells) compared with primary tumors (17% nanoparticle-positive cells) because they reside close to blood vessels and require a small diffusion distance to reach all tumor cells. Furthermore, the high-throughput nature of our image analysis workflow allowed us to profile the physiology and nanoparticle delivery of 1,301 micrometastases. This enabled us to use machine learning-based modeling to predict nanoparticle delivery to individual micrometastases based on their physiology. Our imaging method allows researchers to measure nanoparticle delivery to micrometastases and highlights an opportunity to target micrometastases with nanoparticles. The development of models to predict nanoparticle delivery based on micrometastasis physiology could enable personalized treatments based on the specific physiology of a patient's micrometastases.
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What OpenQuestion holds
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.