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Autoantibody recognition mechanisms of MUC1

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  • Phillips, J.C.

Abstract

The most cost-effective blood-based, noninvasive molecular early cancer biomarkers are based on p53 epitopes and MUC1 tandem repeats. Here we use dimensionally compressed bioinformatic fractal scaling analysis to compare the two distinct and comparable probes, which examine different sections of the autoantibody population, achieving combined sensitivities of order 50%. We explain the experimental observation that glycosylation does not enhance, and can depress, the sensitivity of MUC1 tandem repeat biomarkers. We propose a possible supplementary MUC1 epitope in the SEA region outside the tandem repeats.

Suggested Citation

  • Phillips, J.C., 2017. "Autoantibody recognition mechanisms of MUC1," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 244-249.
    • Handle: RePEc:eee:phsmap:v:469:y:2017:i:c:p:244-249
    DOI: 10.1016/j.physa.2016.11.075
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    References listed on IDEAS

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    1. Phillips, J.C., 2016. "Autoantibody recognition mechanisms of p53 epitopes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 162-170.
    2. Phillips, J.C., 2014. "Fractals and self-organized criticality in proteins," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 440-448.
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