An optimized predictor panel for colorectal cancer diagnosis based on the combination of tumor-associated antigens obtained from protein and phage microarrays

J Proteomics. 2012 Aug 3;75(15):4647-55. doi: 10.1016/j.jprot.2012.03.004. Epub 2012 Mar 18.

Abstract

Humoral response in cancer patients appears early in cancer progression and can be used for diagnosis, including early detection. By using human recombinant protein and T7 phage microarrays displaying colorectal cancer (CRC)-specific peptides, we previously selected 6 phages and 6 human recombinant proteins as tumor-associated antigens (TAAs) with high diagnostic value. After completing validation in biological samples, TAAs were classified according to their correlation, redundancy in reactivity patterns and multiplex diagnostic capabilities. For predictor model optimization, TAAs were reanalyzed with a new set of samples. A combination of three phages displaying peptides homologous to GRN, NHSL1 and SREBF2 and four proteins PIM1, MAPKAPK3, FGFR4 and ACVR2B, achieved an area under the curve (AUC) of 94%, with a sensitivity of 89.1% and specificity of 90.0%, to correctly predict the presence of cancer. For early colorectal cancer stages, the AUC was 90%, with a sensitivity of 88.2% and specificity of 82.6%. In summary, we have defined an optimized predictor panel, combining TAAs from different sources, with highly improved accuracy and diagnostic value for colorectal cancer. This article is part of a Special Issue entitled: Translational Proteomics.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Antigens, Neoplasm / metabolism*
  • Colorectal Neoplasms / diagnosis*
  • Colorectal Neoplasms / metabolism*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Neoplasm Proteins / metabolism*
  • Neoplasm Staging
  • Peptide Library*
  • Predictive Value of Tests

Substances

  • Antigens, Neoplasm
  • Neoplasm Proteins
  • Peptide Library