Autoantibody recognition mechanisms of p53 epitopes

• The earliest stages of cancers generate biochemically detectable autoantibodies.
• A massive clinical study showed that p53 epitopes are the most effective tool.
• Bioinformatic scaling identifies these epitopes as exposed beta strands.
• Refined p53 epitopes are shorter and can be obtained from other species.
• Liver cancer epitopes can be studied clinically with 1000 times fewer patients.

There is an urgent need for economical blood based, noninvasive molecular biomarkers to assist in the detection and diagnosis of cancers in a cost-effective manner at an early stage, when curative interventions are still possible. Serum autoantibodies are attractive biomarkers for early cancer detection, but their development has been hindered by the punctuated genetic nature of the ten million known cancer mutations. A landmark study of 50,000 patients (Pedersen et al., 2013) showed that a few p53 15-mer epitopes are much more sensitive colon cancer biomarkers than p53, which in turn is a more sensitive cancer biomarker than any other protein. The function of p53 as a nearly universal “tumor suppressor” is well established, because of its strong immunogenicity in terms of not only antibody recruitment, but also stimulation of autoantibodies. Here we examine dimensionally compressed bioinformatic fractal scaling analysis for identifying the few sensitive epitopes from the p53 amino acid sequence, and show how it could be used for early cancer detection (ECD). We trim 15-mers to 7-mers, and identify specific 7-mers from other species that could be more sensitive to aggressive human cancers, such as liver cancer. Our results could provide a roadmap for ECD.