Non-Small Cell Lung Cancer Imaging Using a Phospholipase A2 Activatable Fluorophore.

Lung cancer, the most common cause of cancer-related death in the United States, requires advanced intraoperative detection methods to improve evaluation of surgical margins. In this study we employed DDAO-arachidonate (DDAO-A), a phospholipase A2 (PLA2) activatable fluorophore, designed for the specific optical identification of lung cancers in real-time during surgery. The fluorescence activation of DDAO-A by porcine sPLA2 was tested in various liposomal formulations, with 100 nm extruded EggPC showing the best overall characteristics. Extruded EggPC liposomes containing DDAO-A were tested for their stability under various storage conditions, demonstrating excellent stability for up to 4 weeks when stored at -20 °C or below. Cell studies using KLN 205 and LLC1 lung cancer cell lines showed DDAO-A activation was proportional to cell number. DDAO-A showed preferential activation by human recombinant cPLA2, an isoform highly specific to arachidonic acid-containing lipids, when compared to a control probe, DDAO palmitate (DDAO-P). studies with DBA/2 mice bearing KLN 205 lung tumors recapitulated these results, with preferential activation of DDAO-A relative to DDAO-P following intratumoral injection. Topical application of DDAO-A-containing liposomes to human (n = 10) and canine (n = 3) lung cancers demonstrated the preferential activation of DDAO-A in tumor tissue relative to adjacent normal lung tissue, with fluorescent tumor-to-normal ratios (TNR) of up to 5.2:1. The combined results highlight DDAO-A as a promising candidate for clinical applications, showcasing its potential utility in intraoperative and back-table imaging and topical administration during lung cancer surgeries. By addressing the challenge of residual microscopic disease at resection margins and offering stability in liposomal formulations, DDAO-A emerges as a potentially valuable tool for advancing precision lung cancer surgery and improving curative resection rates.