ArticleJournal of visualized experiments : JoVE2018
Practical Considerations in Studying Metastatic Lung Colonization in Osteosarcoma Using the Pulmonary Metastasis Assay.
Article in Journal of visualized experiments : JoVE, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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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.
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Who cites it
13 citing papers in PubMed, 18 citations in OpenAlex.
- The Osteosarcoma Tumor Microenvironment: From Cellular Interactions to Advanced Preclinical Models.Cancers · 2026Review
- Cystathionine gamma-lyase-mediated hypoxia inducible factor 1-alpha expression drives clear cell ovarian cancer progression.The Journal of pathology · 2025Article
- An improved experimental model of osteosarcoma lung metastases to investigate innovative therapeutic interventions and sex as a biological variable.International journal of pharmaceutics · 2025Article
- Pharmacologic Inhibition of EIF4A Blocks NRF2 Synthesis to Prevent Osteosarcoma Metastasis.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024Article
- State of the Art Modelling of the Breast Cancer Metastatic Microenvironment: Where Are We?Journal of mammary gland biology and neoplasia · 2024Review
- A Bifunctional PARP-HDAC Inhibitor with Activity in Ewing Sarcoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2023Article
- Osteosarcoma tumor microenvironment: the key for the successful development of biologically relevant 3D in vitro models.In vitro models · 2022Review
- NSG Mice FacilitateFrontiers in oncology · 2021Article
- Benefits of Zebrafish Xenograft Models in Cancer Research.Frontiers in cell and developmental biology · 2021Review
- Understanding and Modeling Metastasis Biology to Improve Therapeutic Strategies for Combating Osteosarcoma Progression.Frontiers in oncology · 2020Review
- Metastasis and cachexia: alongside in clinics, but not so in animal models.Journal of cachexia, sarcopenia and muscle · 2019Review
- Provocative questions in osteosarcoma basic and translational biology: A report from the Children's Oncology Group.Cancer · 2019Review
- Automated quantitative image analysis for ex vivo metastasis assays reveals differing lung composition requirements for metastasis suppression by KISS1.Clinical & experimental metastasis · 2018Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The pulmonary metastasis assay (PuMA) is an ex vivo lung explant and closed cell culture system that permits researchers to study the biology of lung colonization in osteosarcoma (OS) by fluorescence microscopy. This article provides a detailed description of the protocol, and discusses examples of obtaining image data on metastatic growth using widefield or confocal fluorescence microscopy platforms. The flexibility of the PuMA model permits researchers to study not only the growth of OS cells in the lung microenvironment, but also to assess the effects of anti-metastatic therapeutics over time. Confocal microscopy allows for unprecedented, high-resolution imaging of OS cell interactions with the lung parenchyma. Moreover, when the PuMA model is combined with fluorescent dyes or fluorescent protein genetic reporters, researchers can study the lung microenvironment, cellular and subcellular structures, gene function, and promoter activity in metastatic OS cells. The PuMA model provides a new tool for osteosarcoma researchers to discover new metastasis biology and assess the activity of novel anti-metastatic, targeted therapies.
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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.