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2006:
Sarkioja Merja; Kanerva Anna; Salo Jarmo; Kangasniemi Lotta; Eriksson Minna; Raki Mari; Ranki Tuuli; Hakkarainen Tanja; Hemminki Akseli
Noninvasive imaging for evaluation of the systemic delivery of capsid-modified adenoviruses in an orthotopic model of advanced lung cancer.
Cancer 2006;
107(
7):.
BACKGROUND: Variable expression of the coxsackie and adenovirus receptor (CAR) has limited gene transfer efficacy to many types of tumors. Consequently, tropism-modified adenoviruses have been developed for enhanced infectivity. To the authors' knowledge, targeting approaches for nonsmall cell lung cancer (NSCLC) have not been comprehensively evaluated. The current hypothesis was that modified adenoviruses could be used for increasing gene transfer to and killing of NSCLC cells in vitro and in vivo. METHODS: Ten NSCLC cell lines were analyzed to represent the different NSCLC histologies. Because clinical tumors may differ from established cell lines, 6 clinical specimens fresh from patients were analyzed. For in vivo studies, a novel orthotopic murine model of advanced lung cancer was developed. Because tumor response is difficult to quantitate in orthotopic models, noninvasive imaging of green fluorescent protein (GFP) was utilized as a surrogate for tumor size measurements. RESULTS: Adenoviruses whose capsids were modified with RGD-4C, the serotype 3 knob, or polylysine displayed increased gene transfer to NSCLC cell lines and clinical samples in comparison to serotype 5 viruses. Conditionally replicating oncolytic adenoviruses (CRAds) with the same modifications showed enhanced therapeutic efficiency in vitro and in vivo. The median survival of mice treated with Ad5.pK7-Delta24 or Ad5-Delta24RGD increased 37% (P<.01). GFP imaging allowed noninvasive individualized detection of response and recurrence. CONCLUSIONS: Targeting of adenovirus to heterologous receptors can improve killing of NSCLC cells. Utilization of clinical samples and an orthotopic model of advanced lung cancer may provide clinically relevant translational data.
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