Abstract
Purpose
Intraoperative identification of lung tumors can be challenging. Tumor-targeted fluorescence-guided surgery can provide surgeons with a tool for real-time intraoperative tumor detection. This study evaluated cell surface biomarkers, partially selected via data-driven selection software, as potential targets for fluorescence-guided surgery in non-small cell lung cancers: adenocarcinomas (ADC), adenocarcinomas in situ (AIS), and squamous cell carcinomas (SCC).
Procedures
Formalin-fixed paraffin-embedded tissue slides of resection specimens from 15 patients with ADC and 15 patients with SCC were used and compared to healthy tissue. Molecular targets were selected based on two strategies: (1) a data-driven selection using > 275 multi-omics databases, literature, and experimental evidence; and (2) the availability of a fluorescent targeting ligand in advanced stages of clinical development. The selected targets were carbonic anhydrase 9 (CAIX), collagen type XVII alpha 1 chain (collagen XVII), glucose transporter 1 (GLUT1), G protein-coupled receptor 87 (GPR87), transmembrane protease serine 4 (TMPRSS4), carcinoembryonic antigen (CEA), epithelial cell adhesion molecule (EpCAM), folate receptor alpha (FRα), integrin αvβ6 (αvβ6), and urokinase-type plasminogen activator receptor (uPAR). Tumor expression of these targets was assessed by immunohistochemical staining. A total immunostaining score (TIS, range 0–12), combining the percentage and intensity of stained cells, was calculated. The most promising targets in ADC were explored in six AIS tissue slides to explore its potential in non-palpable lesions.
Results
Statistically significant differences in TIS between healthy lung and tumor tissue for ADC samples were found for CEA, EpCAM, FRα, αvβ6, CAIX, collagen XVII, GLUT-1, and TMPRSS4, and of these, CEA, CAIX, and collagen XVII were also found in AIS. For SCC, EpCAM, uPAR, CAIX, collagen XVII, and GLUT-1 were found to be overexpressed.
Conclusions
EpCAM, CAIX, and Collagen XVII were identified using concomitant use of data-driven selection software and clinical evidence as promising targets for intraoperative fluorescence imaging for both major subtypes of non-small cell lung carcinomas.
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Meijer, R.P.J., Neijenhuis, L.K.A., Zeilstra, A.P. et al. Data-Driven Identification of Targets for Fluorescence-Guided Surgery in Non-Small Cell Lung Cancer. Mol Imaging Biol 25, 228–239 (2023). https://doi.org/10.1007/s11307-022-01791-5
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DOI: https://doi.org/10.1007/s11307-022-01791-5