Targeting the HGF/c-MET pathway in advanced pancreatic cancer: a key element of treatment that limits primary tumour growth and eliminates metastasis
説明
<jats:title>Abstract</jats:title><jats:sec> <jats:title>Background</jats:title> <jats:p>Stromal–tumour interactions facilitate pancreatic cancer (PC) progression. The hepatocyte growth factor (HGF)/c-MET pathway is upregulated in PC and mediates the interaction between cancer cells and stromal pancreatic stellate cells (PSCs). This study assessed the effect of HGF/c-MET inhibition plus gemcitabine (G) on the progression of advanced PC.</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>Orthotopic PC was produced by implantation of luciferase-tagged human cancer cells + human PSCs into mouse pancreas. Tumours were allowed to develop without treatment for 4 weeks. Mice were then treated for 6 weeks with one of the following: IgG, G, HGF inhibitor (Hi), c-MET inhibitor (Ci), Hi + Ci, Hi + G, Ci + G, or Hi + Ci + G.</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>Bioluminescence imaging showed similar tumour sizes in all mice at the initiation of treatments. Triple therapy (Hi + Ci + G): (1) completely eliminated metastasis; (2) significantly reduced tumour size as assessed by bioluminescence and at necropsy; (3) significantly reduced proliferating cancer cell density and stem cell marker DCLK1 expression in tumours. In vitro 3D culture studies supported our in vivo findings.</jats:p> </jats:sec><jats:sec> <jats:title>Conclusion</jats:title> <jats:p>Even at an advanced disease stage, a two-pronged approach, targeting (a) HGF/c-MET with relevant inhibitors and (b) cancer cells with chemotherapy, completely eliminated metastasis and significantly decreased tumour growth, suggesting that this is a promising treatment approach for PC.</jats:p> </jats:sec>
収録刊行物
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- British Journal of Cancer
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British Journal of Cancer 122 (10), 1486-1495, 2020-03-23
Springer Science and Business Media LLC
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詳細情報 詳細情報について
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- CRID
- 1360853567364746624
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- ISSN
- 15321827
- 00070920
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- データソース種別
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- Crossref
- KAKEN