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Abstract
Detection of pancreatic cancer remains a high priority and effective diagnostic tools are needed for clinical applications. Many cancer cells overexpress integrin a(v)ß(6), a cell surface receptor being evaluated as a novel clinical biomarker.To validate this molecular target, several highly stable cystine knot peptides were engineered by directed evolution to bind specifically and with high affinity (3-6 nmol/L) to integrin a(v)ß(6). The binders do not cross-react with related integrin a(v)ß(5), integrin a(5)ß(1), or tumor-angiogenesis-associated integrin, a(v)ß(3).Positron emission tomography showed that these disulfide-stabilized peptides rapidly accumulate at tumors expressing integrin a(v)ß(6). Clinically relevant tumor-to-muscle ratios of 7.7 ± 2.4 to 11.3 ± 3.0 were achieved within 1 hour after radiotracer injection. Minimization of off-target dosing was achieved by reformatting a(v)ß(6)-binding activities across various natural and pharmacokinetically stabilized cystine knot scaffolds with different amino acid content. We show that the primary sequence of a peptide scaffold directs its pharmacokinetics. Scaffolds with high arginine or glutamic acid content suffered high renal retention of more than 75% injected dose per gram (%ID/g). Substitution of these amino acids with renally cleared amino acids, notably serine, led to significant decreases in renal accumulation of less than 20%ID/g 1 hour postinjection (P < 0.05, n = 3).We have engineered highly stable cystine knot peptides with potent and specific integrin a(v)ß(6)-binding activities for cancer detection. Pharmacokinetic engineering of scaffold primary sequence led to significant decreases in off-target radiotracer accumulation. Optimization of binding affinity, specificity, stability, and pharmacokinetics will facilitate translation of cystine knots for cancer molecular imaging.
View details for DOI 10.1158/1078-0432.CCR-11-1116
View details for Web of Science ID 000300115000027
View details for PubMedID 22173551
View details for PubMedCentralID PMC3271184