Identification of a high affinity TAG-72 binding peptide by phage display selection.
OBJECTIVE
Phage display was used to select novel peptides that specifically bind the TAG-72 antigen and with properties suitable for imaging TAG-72 positive cancers.


RESULTS
After three rounds of selection against TAG-72 and using two different elution conditions including a long elution, the consensus sequences FRERCDKHPQKCTKFL and DPRHCQKRVLPCPAWL were expressed on phages G3-15 and T3-15 respectively. ELISA, fluorescence-activated cell sorting analysis and fluorescence microscopy provided evidence that both phages specifically bound TAG-72 in vitro. Both peptides are stable in 37oC serum. By a cell binding competition assay, the IC50 for T3-15 was measured as 0.29 nM and therefore 36-fold higher affinity than G3-15 at 10.32 nM. The biodistribution in mice carrying LS-174T tumors in one thigh were similar for both 99mTc-peptides at 30 min, but at 90 min the 99mTc-T3-15 peptide accumulated almost three times higher in the tumor. The SPECT/CT images were consistent with the biodistribution results.


METHODS
The f88-4/Cys6 phage library and two different elution conditions were used to identify two new higher affinity binding peptides for the TAG-72 antigen. One, was a single brief elution with pH 2.2 glycine buffer, and the second began with the glycine elution but was followed with a longer elution with Tris buffered saline (TBS) at pH 7.4. The phages that bound TAG-72 were evaluated by fluorescence-activated cell sorting analysis using TAG-72 positive LS-174T cells and confirmed by immunofluorescence imaging. The consensus peptides displayed on the selected phages were synthesized and conjugated with NHS-MAG3 for radiolabeling with 99mTc. The IC50 for TAG-72 binding was evaluated by cell binding competition in vitro while binding affinity was evaluated in vivo by necropsy and SPECT/CT imaging in a tumor mouse model.


CONCLUSIONS
We have identified a peptide with a sub nanomolar inhibition constant for the TAG-72 antigen that may have application in cancer imaging.
Xiao
Nan
N
University of Massachusetts Medical School, Worcester, Massachusetts, USA.
Cheng
Dengfeng
D
Wang
Yi
Y
Chen
Ling
L
Liu
Xinrong
X
Dou
Shuping
S
Liu
Guozheng
G
Liang
Minmin
M
Hnatowich
Donald J
DJ
Rusckowski
Mary
M
D000595:Amino Acid Sequence; D000818:Animals; D000951:Antigens, Neoplasm / Q000235:genetics / Q000378:metabolism*; D045744:Cell Line, Tumor; D003110:Colonic Neoplasms / Q000000981:diagnostic imaging / Q000378:metabolism; D006023:Glycoproteins / Q000378:metabolism*; D019073:HT29 Cells; D006801:Humans; D008297:Male; D051379:Mice; D008819:Mice, Nude; D008969:Molecular Sequence Data; D019151:Peptide Library; D010455:Peptides / Q000378:metabolism* / Q000493:pharmacokinetics; D011485:Protein Binding; D013667:Technetium; D014018:Tissue Distribution; D015899:Tomography, Emission-Computed, Single-Photon; D023041:Xenograft Model Antitumor Assays
D000951:Antigens, Neoplasm; D006023:Glycoproteins; D019151:Peptide Library; D010455:Peptides; C047052:tumor-associated antigen 72; D013667:Technetium