Implication of the Insulin-like Growth Factor-IR Pathway in the Resistance of Non–small Cell Lung Cancer Cells to Treatment with Gefitinib

Abstract

Purpose: Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors have been found to be effective against lung cancer in vitro, but clinical resistance to these agents has developed as their usage has increased. In this study, we determined whether the insulin-like growth factor I (IGF-I) signaling pathway induces resistance of non–small cell lung cancer (NSCLC) cells to the EGFR tyrosine kinase inhibitor gefitinib. Experimental Design: The effects of gefitinib and cetuximab on NSCLC cells, alone or with an IGF-I receptor (IGF-IR) inhibitor, were assessed using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay, the flow cytometry–based terminal nucleotidyl transferase–mediated nick end labeling assay, coimmunoprecipitation, and Western blot analysis. EGFR and IGFR expression in NSCLC tissues were examined by Western blot analysis. Results: Gefitinib inhibited NSCLC cell proliferation by inducing apoptosis when IGF-IR signaling was suppressed. Treatment with gefitinib, but not cetuximab, induced EGFR:IGF-IR heterodimerization and activation of IGF-IR and its downstream signaling mediators, resulting in increased survivin expression in NSCLC cell lines with high levels of IGF-IR expression. Inhibition of IGF-IR activation and knockdown of survivin expression led to increased apoptosis. In contrast, overexpression of survivin protected cells with low IGF-IR expression from gefitinib-induced apoptosis. Most NSCLC tissues with EGFR overexpression had associated high levels of IGF-IR expression. Conclusions: IGF-IR expression may be useful as a predictive marker for gefitinib treatment of NSCLC. Suppression of IGF-IR signaling pathways may prevent or delay development of gefitinib resistance in patients with NSCLC.

Augmentation of response to nab-paclitaxel by inhibition of insulin-like growth factor (IGF) signaling in preclinical pancreatic cancer models

“…IGF-1R overexpression has been correlated with tumor aggressiveness [43–45] while disruption of IGF-1R activation inhibited growth and motility of a wide range of cancers [46]. Additionally, the blockage of IGF-1R signaling has been shown to enhance chemotherapy response in preclinical studies of several cancer types including pancreatic and non small-cell lung cancers as well as Ewing's sarcoma [43, 47, 48]. Since IGF-1R and IR are highly homologous, antagonist development was initially focused towards monoclonal antibodies that selectively target IGF-1R and not affect IR signaling, which could lead to dysregulation of glucose homeostasis [21].…”

Inhibition of Hsp90 activates osteoclast c-Src signaling and promotes growth of prostate carcinoma cells in bone

“…Tyrosine kinase-addicted tumors escape molecularly targeted inhibitors by mutations that interfere with drug binding (e.g., mutations in the kinase domain of Bcr-Abl and EGFR) or by a process termed ''oncogene switching,'' whereby drug-treated cells use an alternative tyrosine kinase to drive downstream signaling pathways (e.g., c-Met or IGF-1 receptor utilization nonsmall cell lung cancers exposed to EGFR tyrosine kinase inhibitors) (39)(40)(41)(42). It has been proposed that cancer cells by their very nature may be ''Hsp90 addicted'' (43), yet neither drug-sparing mutations nor utilization of alternative chaperones have been identified in Hsp90 inhibitor-treated tumor cells to date.…”

Combination of EGFR and MEK1/2 inhibitor shows synergistic effects by suppressing EGFR/HER3-dependent AKT activation in human gastric cancer cells

“…To determine the effects of the combined drug treatments, any potentiation was estimated by multiplying the percentage of remaining cells (percent growth) for each drug. The classification indices were calculated as previously described (29). Synergism was defined as % AB/(% A × % B) > 1.0; additivity was defined as % AB/(% A × % B) = 0.9 to 1.0; and antagonism was defined as % AB/(% A × % B) < 0.9 (in these equations, A and B are the effects of individual agents, and AB represents the effects of the combination of the two drugs).…”