Abstract

We have previously demonstrated differential nucleosome patterns in samples from a retrospective cohort of 4800 patients presenting with symptoms of Colorectal diseases. A diagnostic NuQ® panel was identified with sensitivity of 81% at a specificity of 80% in an age adjusted Linear Discriminant Analysis (LDA) model for the detection of Colorectal cancer (CRC). The success of stool based screening for CRC adopted across Europe has placed significant strain on limited colonoscopy capacity. The aim of the study was to evaluate combined NuQ® blood score and numeric FIT score as a triage approach for positive Fecal Immune Tests (FIT) in an average risk population i.e. to identify individuals with low risk adenomas or no findings on colonoscopy. We have developed ELISAs for specific epigenetic features of circulating nucleosomes (NuQ®) including histone modifications and variants, DNA modifications and nucleosome-protein adducts and shown that the epigenetic profiles can be correlated with disease. Serum samples were collected from a training cohort consisting of approximately 1900 FIT positive individuals with colonoscopic confirmation of diagnosis. 10 µl serum samples were analyzed using NuQ® ELISA blood tests and an algorithm developed by Linear Discriminant Analysis (LDA) was used to identify individuals with a false positive FIT result. A single, age adjusted NuQ® assay for nucleosome associated methylated DNA (normalized to total nucleosomes) combined with FIT score can reduce the need for unnecessary colonoscopies whilst maintaining sensitivity for CRC. For example, a 25% reduction in colonoscopies is associated with 96.6% sensitivity for CRC and 88.5% sensitivity for HRA. A single, age adjusted NuQ® blood score with FIT score could reduce non screen-relevant colonoscopies in FIT positive individuals with minimal reduction in cancer detection. This test has potential applications to reduce unnecessary colonoscopies and thereby ease the pressure on colonoscopy capacity constraints or, alternatively, to detect more cancers in a screening programme by increasing the throughput of screening subjects.

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