EGFRvIII and c-Met pathway inhibitors synergize against PTEN-null/EGFRvIII+ glioblastoma xenografts

EGFRvIII 和 c-Met 通路抑制剂对 PTEN 缺失/EGFRvIII 阳性胶质母细胞瘤异种移植具有协同作用

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Abstract

Receptor tyrosine kinase (RTK) systems, such as hepatocyte growth factor (HGF) and its receptor c-Met, and epidermal growth factor receptor (EGFR), are responsible for the malignant progression of multiple solid tumors. Recent research shows that these RTK systems comodulate overlapping and dynamically adaptable oncogenic downstream signaling pathways. This study investigates how EGFRvIII, a constitutively active EGFR deletion mutant, alters tumor growth and signaling responses to RTK inhibition in PTEN-null/HGF(+)/c-Met(+) glioma xenografts. We show that a neutralizing anti-HGF monoclonal antibody (L2G7) potently inhibits tumor growth and the activation of Akt and mitogen-activated protein kinase (MAPK) in PTEN-null/HGF(+)/c-Met(+)/EGFRvIII(-) U87 glioma xenografts (U87wt). Isogenic EGFRvIII(+) U87 xenografts (U87-EGFRvIII), which grew five times more rapidly than U87-wt xenografts, were unresponsive to EGFRvIII inhibition by erlotinib and were only minimally responsive to anti-HGF monoclonal antibodies. EGFRvIII expression diminished the magnitude of Akt inhibition and completely prevented MAPK inhibition by L2G7. Despite the lack of response to L2G7 or erlotinib as single agents, their combination synergized to produce substantial antitumor effects (inhibited tumor cell proliferation, enhanced apoptosis, arrested tumor growth, prolonged animal survival), against subcutaneous and orthotopic U87-EGFRvIII xenografts. The dramatic response to combining HGF:c-Met and EGFRvIII pathway inhibitors in U87-EGFRvIII xenografts occurred in the absence of Akt and MAPK inhibition. These findings show that combining c-Met and EGFRvIII pathway inhibitors can generate potent antitumor effects in PTEN-null tumors. They also provide insights into how EGFRvIII and c-Met may alter signaling networks and reveal the potential limitations of certain biochemical biomarkers to predict the efficacy of RTK inhibition in genetically diverse cancers.

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