ArticleJournal of visualized experiments : JoVE2018
Live Cell Imaging of the TGF- β/Smad3 Signaling Pathway In Vitro and In Vivo Using an Adenovirus Reporter System.
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 7 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.
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
7 citing papers in PubMed, 8 citations in OpenAlex.
- Extracellular Vesicles Secreted by Cancer-Associated Fibroblasts Drive Non-Invasive Cancer Cell Progression to Metastasis via TGF-β Signalling Hyperactivation.Journal of extracellular vesicles · 2025Article
- Article
- Simultaneously targeting extracellular vesicle trafficking and TGF-β receptor kinase activity blocks signaling hyperactivation and metastasis.Signal transduction and targeted therapy · 2023Article
- Review
- Dynamic Visualization of TGF-β/SMAD3 Transcriptional Responses in Single Living Cells.Cancers · 2022Article
- Tracking leukemic T-cell transcriptional dynamics in vivo with a blood-based reporter assay.FEBS open bio · 2020Article
- On-Target Anti-TGF-β Therapies Are Not Succeeding in Clinical Cancer Treatments: What Are Remaining Challenges?Frontiers in cell and developmental biology · 2020Review
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Transforming Growth Factor β (TGF-β) signaling regulates many important functions required for cellular homeostasis and is commonly found overexpressed in many diseases, including cancer. TGF-β is strongly implicated in metastasis during late stage cancer progression, activating a subset of migratory and invasive tumor cells. Current methods for signaling pathway analysis focus on endpoint models, which often attempt to measure signaling post-hoc of the biological event and do not reflect the progressive nature of the disease. Here, we demonstrate a novel adenovirus reporter system specific for the TGF-β/Smad3 signaling pathway that can detect transcriptional activation in live cells. Utilizing an Ad-CAGA12-Td-Tom reporter, we can achieve a 100% infection rate of MDA-MB-231 cells within 24 h in vitro. The use of a fluorescent reporter allows for imaging of live single cells in real-time with direct identification of transcriptionally active cells. Stimulation of infected cells with TGF-β displays only a subset of cells that are transcriptionally active and involved in specific biological functions. This approach allows for high specificity and sensitivity at a single cell level to enhance understanding of biological functions related to TGF-β signaling in vitro. Smad3 transcriptional activity can also be reported in vivo in real-time through the application of an Ad-CAGA12-Luc reporter. Ad-CAGA12-Luc can be measured in the same manner as traditional stably transfected luciferase cell lines. Smad3 transcriptional activity of cells implanted in vivo can be analyzed through conventional IVIS imaging and monitored live during tumor progression, providing unique insight into the dynamics of the TGF-β signaling pathway. Our protocol describes an advantageous reporter delivery system allowing for quick high-throughput imaging of live cell signaling pathways both in vitro and in vivo. This method can be expanded to a range of image based assays and presents as a sensitive and reproducible approach for both basic biology and therapeutic development.
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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.