There is an urgent need for biomarkers to identify malignant thyroid nodules from indeterminate follicular lesions. We have used a subtractive proteomic strategy to identify novel biomarkers by selecting ligands to goiter tissue from a 12-mer random peptide phage-displayed library using the BRASIL method (Biopanning and Rapid Analysis of Selective Interactive Ligands). After three rounds of selection, two highly reactive clones to the papillary thyroid tumor cell line NPA were further evaluated, and their specific binding to tumor proteins was confirmed using phage-ELISA. The antibody-like peptide CaT12 was tumor-specific, which was further tested by immunohistochemistry against TMAs (tissue microarrays) comprised of 775 human benign and malignant tissues, including 232 thyroid nodular lesions: 15 normal thyroid tissues, 53 nodular goiters (NG), 54 follicular adenomas (FA); 69 papillary thyroid carcinomas (PTC); and 41 follicular carcinomas (FC). CaT12 was able to identify PTC among thyroid nodular lesions with 91.2% sensitivity and 85.1% specificity, despite its non-specificity for thyroid tissues. Additionally, the CaT12 peptide helped characterize follicular lesions distinguishing the follicular variant of PTC (FVPTC) from FA with 91.9% accuracy; FVPTC from NG with 83.1% accuracy; FVPTC from the classic PTC with 57.7% accuracy; and FVPTC from FC with 88.7% accuracy. In conclusion, our strategy to select differentially expressed ligands to thyroid tissue was highly effective and resulted in a useful antibody-like biomarker that recognizes malignancy among thyroid nodules and may help distinguish follicular patterned lesions.
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