ArticleScientific reports2020
The anti-tumoral potential of the saporin-based uPAR-targeting chimera ATF-SAP.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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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
12 citing papers in PubMed, 21 citations in OpenAlex.
- Review
- Urokinase-Type Plasminogen Activator Receptor (uPAR) in Inflammation and Disease: A Unique Inflammatory Pathway Activator.Biomedicines · 2024Review
- Novel loading protocol combines highly efficient encapsulation of exogenous therapeutic toxin with preservation of extracellular vesicles properties, uptake and cargo activity.Discover nano · 2024Article
- In vitro and in vivo anti-tumor effect of Trichobakin fused with urokinase-type plasminogen activator ATF-TBK.Molecular biology reports · 2024Article
- Urokinase-type plasminogen activator receptor (uPAR) as a therapeutic target in cancer.Journal of translational medicine · 2022Review
- Review
- Modulation of Cellular Function by the Urokinase Receptor Signalling: A Mechanistic View.Frontiers in cell and developmental biology · 2022Review
- A Novel RGD-4C-Saporin Conjugate Inhibits Tumor Growth in Mouse Models of Bladder Cancer.Frontiers in oncology · 2022Article
- The Urokinase Receptor (uPAR) as a "Trojan Horse" in Targeted Cancer Therapy: Challenges and Opportunities.Cancers · 2021Review
- Fibrinolytic System and Cancer: Diagnostic and Therapeutic Applications.International journal of molecular sciences · 2021Review
- Targeting the Urokinase-Type Plasminogen Activator Receptor (uPAR) in Human Diseases With a View to Non-invasive Imaging and Therapeutic Intervention.Frontiers in cell and developmental biology · 2021Review
- Targeting Receptors on Cancer Cells with Protein Toxins.Biomolecules · 2020Review
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The development of personalized therapies represents an urgent need owing to the high rate of cancer recurrence and systemic toxicity of conventional drugs. So far, targeted toxins have shown promising results as potential therapeutic compounds. Specifically, toxins conjugated to antibodies or fused to growth factors/enzymes have been largely demonstrated to selectively address and kill cancer cells. We investigated the anti-tumor potential of a chimeric recombinant fusion protein formed by the Ribosome Inactivating Protein saporin (SAP) and the amino-terminal fragment (ATF) of the urokinase-type plasminogen activator (uPA), whose receptor has been shown to be over-expressed on the surface of aggressive tumors. ATF-SAP was recombinantly produced by the P. pastoris yeast and its activity was assessed on a panel of bladder and breast cancer cell lines. ATF-SAP resulted to be highly active in vitro, as nano-molar concentrations were sufficient to impair viability on tumor cell lines. In contrast to untargeted toxins, the chimeric fusion protein displayed a significantly improved toxic effect in uPAR-expressing cells, demonstrating that the selective activity was due to the presence of the targeting moiety. Fibroblasts were not sensitive to ATF-SAP despite uPAR expression, indicating that cell-specific receptor-mediated internalization pathway(s) might be considered. The in vivo anti-tumor effect of the chimera was shown in a bladder cancer xenograft model. Current findings indicate ATF-SAP as a suitable anti-tumoral therapeutic option to cope with cancer aggressiveness, as a single treatment or in combination with traditional therapeutic approaches, to appropriately address the intra- and inter- tumor heterogeneity.
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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.