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Biopolymers. 2009 Mar;91(3):201-6. doi: 10.1002/bip.21117.

Identification of novel peptide ligands for the cancer-specific receptor mutation EFGRvIII using a mixture-based synthetic combinatorial library.

Author information

1
Department of Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, 2100 Copenhagen Ø, Denmark. charlotte.lund.denholt@rh.regionh.dk

Abstract

We report here, the design and synthesis of a positional scanning synthetic combinatorial library for the identification of novel peptide ligands targeted against the cancer-specific epidermal growth factor tyrosine kinase receptor mutation variant III (EGFRvIII). This receptor is expressed in several kinds of cancer, in particular, ovarian, glioblastomas, and breast cancer, but not in normal tissue. The library consisted of six individual positional sublibraries in the format, H-O(1-6)XXXXX-NH(2), O being one of the 19 proteinogenic amino acids (cysteine omitted) and X an equimolar mixture of these. The library consisted of 114 mixtures in total. Using a biotin-streptavidin assay, the binding of each sublibrary to NR6M, NR6W-A, and NR6 cells was tested. These cells express EGFRvIII, EGFR, and neither of the receptors, respectively. The result from each sublibrary was examined to identify the most active amino acid residue at each position. On the basis of this knowledge, eight peptides were synthesized and tested for binding to EGFRvIII. We identified one peptide, H-FALGEA-NH(2), that showed more selective binding to the mutated receptor than the EGFRvIII specific peptide PEPHC1. This study demonstrates the value of using mixture-based combinatorial positional scanning libraries for the identification of novel peptide ligands targeted against the cancer-specific EGFRvIII. Our best candidate H-FALGEA-NH(2) will be radioactively labeled and evaluated as an imaging agent for positron emission tomography investigation for diagnosis, staging, and monitoring of therapy of various types of cancer.

PMID:
19107925
DOI:
10.1002/bip.21117
[Indexed for MEDLINE]
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