Multicyclic Peptides Targeting PD-L1 for Radiotheranostics: From Discovery to Clinical Proof-of-Concept

Radiotheranostics holds transformative potential for precision oncology by integrating diagnostic imaging with targeted radionuclide therapy. However, advancements in this field are significantly hindered by the limited availability of high-affinity ligands that are capable of engaging challenging cell-surface antigens, particularly flat, low-druggability targets such as programmed death-ligand 1 (PD-L1). Here, we overcome this barrier through de novo discovery and rational engineering of a disulfide-directed multicyclic peptide (DDMP), dmp10, which achieves a picomolar affinity for PD-L1 by leveraging conformationally constrained structural scaffolds. By combining disulfide-directed library design with iterative directed evolution, we successfully generated dmp10, a ∼3 kDa multicyclic peptide that establishes unprecedented shape complementarity to the expansive binding interface of PD-L1. Preclinical evaluations demonstrated that 68 Ga-labeled dmp10 enables high-contrast PET imaging of PD-L1 + tumors in murine models, achieving a tumor uptake of 13.27 %ID/g at 4 h post-injection. The therapeutic counterpart, 177 Lu-labeled dmp10, effectively eradicated 92.47% of established tumors in tumor models while sparing healthy tissues, thereby validating its dual radiotheranostic utility. The translational relevance of our findings was further confirmed in a first-in-human pilot study, where 68 Ga-labeled dmp10 was well tolerated and allowed visualization of PD-L1 + lesions in patients with solid tumors. This work not only establishes DDMPs as a versatile platform for targeting geometrically complex antigens but also delivers a promising radiotheranostic agent that bridges molecular imaging and precision radionuclide therapy for PD-L1-driven malignancies. Our findings advance current strategies for designing ultrahigh-affinity peptide binders and underscore the untapped potential of multicyclic architectures in overcoming longstanding challenges in cancer theranostics.