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bioRxiv · 10.1101/2025.09.16.676549

Engineering NIR probes to enhance affinity and clinical workflow compatibility for prostate cancer imaging

Abstract

Positive surgical margins following radical prostatectomy increase the risk of biochemical recurrence and subsequent disease progression. Fluorescence guided surgery (FGS) using targeted contrast agents has shown clinical benefits for several cancer types. However, current prostate cancer targeted imaging probes exhibit long pharmacokinetic (PK) profiles, necessitating extended waiting periods or repeated hospital visits, limiting their integration into standard clinical workflow. To overcome this critical clinical compatibility challenge, we developed an innovative tri-compartment, chemistry-driven probe design strategy. Specifically, we developed a congeneric library of near infrared (NIR) water soluble fluorescent probes incorporating: (1) a glutamic acid-urea-lysine (EuK) ligand targeting prostate specific membrane antigen (PSMA); (2) a NIR heptamethine cyanine fluorophore optimized for enhanced PSMA binding via secondary binding sites interactions; and (3) distinct PK modulators residing outside the PSMA binding pocket to promote rapid off-target tissue clearance. While molecular docking scores, photophysical properties and live-cell staining results showed similar overall performance, probes bearing PK modulators produced stronger tumor-specific fluorescence in vivo than the control lacking a PK modulator. This effort enabled identification of a lead probe with robust tumor targeting and accelerated off-target clearance, providing optimal tumor-specific signal and contrast in a timeframe, fully compatible with robotic-assisted radical prostatectomy (RARP) timelines.

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BibTeXRIS

Malankar, G. S., Szafran, D. A., Kumar, G., Pacce, J., Devereux, M., Tao, K., Gomes, M., Greer, W. S., Rounds, C. C., Masillati, A. M., Gergis, S., Ledvina, H., Wong, M. H., Niedre, M. J., Wang, L. G., Gibbs, S. L.. 2025-09-18. Engineering NIR probes to enhance affinity and clinical workflow compatibility for prostate cancer imaging. https://doi.org/10.1101/2025.09.16.676549

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