Autoantibody recognition mechanisms of MUC1
classification
🧬 q-bio.OT
keywords
muc1autoantibodyrepeatstandemachievinganalysisbioinformaticbiomarkers
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The most cost-effective blood-based, noninvasive molecular 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 discover a promising MUC1 epitope in the SEA region outside the tandem repeats.
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