The use of fluoroproline in MUC1 antigen enables efficient detection of antibodies in patients with prostate cancer

A structure-based design of a new gene22ration tumor-associated glycopeptides with improved affinity against two anti-MUC1 antibodies is described. These unique antigens feature a fluorinated proline residue, such as a (4S)-4-fluoro-L-proline or 4,4-difluoroproline, at the most immunogenic domain. Binding assays using bio-layer interferometry reveal 3-fold to 10-fold affinity improvement with respect to the natural (glyco)peptides. According to X-ray crystallography and MD simulations, the fluorinated residues stabilize the antigen-antibody complex by enhancing key CH/ interactions. Interestingly, a notable improvement in detection of cancer-associated anti-MUC1 antibodies from serum of patients with prostate cancer is achieved with the non-natural antigens, which proves that these derivatives can be considered better diagnostic tools than the natural antigen for this type of cancer.We thank the Ministerio de Economía y Competitividad (projects CTQ2015-67727-R, UNLR13-4E-1931, CTQ2013-44367-C2-2-P, CTQ2015-64597-C2-1P, and BFU2016-75633-P). I. A. B. thanks the Asociación Española Contra el Cancer en La Rioja for a grant. I. S. A. and G. J. L. B. thank FCT Portugal (PhD studentship and FCT Investigator, respectively) and the EPSRC for funding. G. J. L. B. holds a Royal Society URF and an ERC StG (TagIt). F.C. and G. J. L. B thank the EU (Marie-Sklodowska Curie ITN, Protein Conjugates). R.H-G. thanks Agencia Aragonesa para la Investigación y Desarrollo (ARAID) and the Diputación General de Aragón (DGA, B89) for financial support. The research leading to these results has also received funding from the FP7 (2007-2013) under BioStruct-X (grant agreement N°283570 and BIOSTRUCTX_5186). We thank synchrotron radiation source DIAMOND (Oxford) and beamline I04 (number of experiment mx10121-19). Hokkaido University group acknowledges to JSPS KAKENHI Grant Number 25220206 and JSPS Wakate B KAKENHI Grant Number 24710242. We also thank CESGA (Santiago de Compostela) for computer support