Literature DB >> 19351773

Sequencing of type I insulin-like growth factor receptor inhibition affects chemotherapy response in vitro and in vivo.

Xianke Zeng1, Deepali Sachdev, Hua Zhang, Martine Gaillard-Kelly, Douglas Yee.   

Abstract

PURPOSE: The aim of this study was to determine the optimal sequence of combining anti-type I insulin-like growth factor receptor (IGF1R) antibodies with chemotherapeutic drugs in cancer cells in vitro and in vivo. EXPERIMENTAL
DESIGN: MCF-7 and LCC6 cells were treated with subcytotoxic concentrations of doxorubicin with or without anti-IGF1R antibodies (scFv-Fc or EM164 and its humanized version AVE1642). Treatments were given simultaneously, doxorubicin followed by anti-IGF1R antibody, or anti-IGF1R antibody followed by doxorubicin, with measurement of in vitro proliferation, apoptosis, and anchorage-independent growth. The effects of sequencing on LCC6 xenograft growth and metastasis were studied.
RESULTS: Doxorubicin followed by anti-IGF1R antibody (scFv-Fc or EM164) was the most effective combination strategy to inhibit cell monolayer growth and anchorage-independent growth. This sequential combination triggered increased poly (ADP-ribose) polymerase cleavage compared with other treatment sequences. The reverse sequence, antibody followed by doxorubicin treatment, protected cells from chemotherapy by decreasing apoptosis, arresting cells in S phase, and inhibiting the level and activity of topoisomerase IIalpha. Finally, our in vivo data show that recovery of IGF1R prior to doxorubicin therapy resulted in the best therapeutic responses. Low doses of AVE1642 that allowed IGF1R expression to recover at one week were more effective in combination with doxorubicin than higher antibody doses.
CONCLUSION: The timing of IGF1R inhibition affects responses to chemotherapy. The optimal sequence was doxorubicin followed by anti-IGF1R antibody, whereas the opposite sequence inhibited doxorubicin effects. Thus, the dose and sequencing of anti-IGF1R therapies should be considered in the design of future clinical trials.

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Year:  2009        PMID: 19351773      PMCID: PMC2720270          DOI: 10.1158/1078-0432.CCR-08-1401

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   12.531


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