Journal
MOLECULAR CANCER
Volume 13, Issue -, Pages -Publisher
BMC
DOI: 10.1186/1476-4598-13-2
Keywords
Molecular targeted therapy; Insulin-like growth factor; NVP-AEW541; MK2206; BEZ235; RAD001
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Funding
- National Health Research Institute, Taiwan [NHRI-EX101-9911BC, NHRI-EX102-9911BC, NSC 100-2314-B-002-058-MY3]
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Background: To explore whether combining inhibitors that target the insulin-like growth factor receptor (IGFR)/PI3K/Akt/mTOR signaling pathway (vertical blockade) can improve treatment efficacy for hepatocellular carcinoma (HCC). Methods: HCC cell lines (including Hep3B, Huh7, and PLC5) and HUVECs (human umbilical venous endothelial cells) were tested. The molecular targeting therapy agents tested included NVP-AEW541 (IGFR kinase inhibitor), MK2206 (Akt inhibitor), BEZ235 (PI3K/mTOR inhibitor), and RAD001 (mTOR inhibitor). Potential synergistic antitumor effects were tested by median dose-effect analysis in vitro and by xenograft HCC models. Apoptosis was analyzed by flow cytometry (sub-G1 fraction analysis) and Western blotting. The activities of pertinent signaling pathways and expression of apoptosis-related proteins were measured by Western blotting. Results: Vertical blockade induced a more sustained inhibition of PI3K/Akt/mTOR signaling activities in all the HCC cells and HUVEC tested. Synergistic apoptosis-inducing effects, however, varied among different cell lines and drug combinations and were most prominent when NVP-AEW541 was combined with MK2206. Using an apoptosis array, we identified survivin as a potential downstream mediator. Over-expression of survivin in HCC cells abolished the anti-tumor synergy between NVP-AEW541 and MK2206, whereas knockdown of survivin improved the anti-tumor effects of all drug combinations tested. In vivo by xenograft studies confirmed the anti-tumor synergy between NVP-AEW541 and MK2206 and exhibited acceptable toxicity profiles. Conclusions: Vertical blockade of the IGFR/PI3K/Akt/mTOR pathway has promising anti-tumor activity for HCC. Survivin expression may serve as a biomarker to predict treatment efficacy.
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