  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 recent study of 50,000
patients (Pedersen et al., 2013) showed p53 15mer 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 bioinformatic fractal scaling analysis for
identifying sensitive epitopes from the p53 amino acid sequence, and show how
it could be used for early cancer detection (ECD). We trim 15mers to 7mers, and
identify specific 7mers from other species that could be more sensitive to
aggressive human cancers, such as liver cancer.
