ArticleMethods in molecular biology (Clifton, N.J.)2018
Intravital Imaging of Tumor Cell Motility in the Tumor Microenvironment Context.
Article in Methods in molecular biology (Clifton, N.J.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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.
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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
11 citing papers in PubMed, 20 citations in OpenAlex.
- Type V Collagen Controls Decidual Extracellular Matrix Organization and Angiogenesis During Embryo Implantation.bioRxiv : the preprint server for biology · 2026Article
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- BEHAV3D Tumor Profiler to map heterogeneous cancer cell behavior in the tumor microenvironment.eLife · 2025Article
- Visualizing cellular interactions: intravital imaging in tumor microenvironment.Frontiers in immunology · 2025Review
- BEHAV3D: a 3D live imaging platform for comprehensive analysis of engineered T cell behavior and tumor response.Nature protocols · 2024Article
- Advanced Tumor Imaging Approaches in Human Tumors.Cancers · 2022Review
- Intravital microscopy of dynamic single-cell behavior in mouse mammary tissue.Nature protocols · 2021Article
- Frontiers in Intravital Multiphoton Microscopy of Cancer.Cancer reports (Hoboken, N.J.) · 2020Review
- Improving nanotherapy delivery and action through image-guided systems pharmacology.Theranostics · 2020Review
- Invadopodia-mediated ECM degradation is enhanced in the G1 phase of the cell cycle.Journal of cell science · 2019Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Cancer cell motility and invasion are key features of metastatic tumors. Both are highly linked to tumor microenvironmental parameters, such as collagen architecture or macrophage density. However, due to the genetic, epigenetic and microenvironmental heterogeneities, only a small portion of tumor cells in the primary tumor are motile and furthermore, only a small portion of those will metastasize. This creates a challenge in predicting metastatic fate of single cells based on the phenotype they exhibit in the primary tumor. To overcome this challenge, tumor cell subpopulations need to be monitored at several timescales, mapping their phenotype in primary tumor as well as their potential homing to the secondary tumor site. Additionally, to address the spatial heterogeneity of the tumor microenvironment and how it relates to tumor cell phenotypes, large numbers of images need to be obtained from the same tumor. Finally, as the microenvironment complexity results in nonlinear relationships between tumor cell phenotype and its surroundings, advanced statistical models are required to interpret the imaging data. Toward improving our understanding of the relationship between cancer cell motility, the tumor microenvironment context and successful metastasis, we have developed several intravital approaches for continuous and longitudinal imaging, as well as data classification via support vector machine (SVM) algorithm. We also describe methods that extend the capabilities of intravital imaging by postsacrificial microscopy of the lung as well as correlative immunofluorescence in the primary tumor.
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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.