Epigenomic Blood-Based Early Detection of Pancreatic Cancer Employing Cell-Free DNA.

BACKGROUND & AIMS: Early detection of pancreatic cancer (PaC) can drastically improve survival rates. Approximately 25% of subjects with PaC have type 2 diabetes diagnosed within 3 years prior to the PaC diagnosis, suggesting that subjects with type 2 diabetes are at high risk of occult PaC. We have developed an early-detection PaC test, based on changes in 5-hydroxymethylcytosine (5hmC) signals in cell-free DNA from plasma. METHODS: Blood was collected from 132 subjects with PaC and 528 noncancer subjects to generate epigenomic and genomic feature sets yielding a predictive PaC signal algorithm. The algorithm was validated in a blinded cohort composed of 102 subjects with PaC, 2048 noncancer subjects, and 1524 subjects with non-PaCs. RESULTS: 5hmC differential profiling and additional genomic features enabled the development of a machine learning algorithm capable of distinguishing subjects with PaC from noncancer subjects with high specificity and sensitivity. The algorithm was validated with a sensitivity for early-stage (stage I/II) PaC of 68.3% (95% confidence interval [CI], 51.9%-81.9%) and an overall specificity of 96.9% (95% CI, 96.1%-97.7%). CONCLUSIONS: The PaC detection test showed robust early-stage detection of PaC signal in the studied cohorts with varying type 2 diabetes status. This assay merits further clinical validation for the early detection of PaC in high-risk individuals.

Analytical Validation of an Early Detection Pancreatic Cancer Test Using 5-Hydroxymethylation Signatures.

Early detection of pancreatic cancer has been shown to improve patient survival rates. However, effective early detection tools to detect pancreatic cancer do not currently exist. The Avantect Pancreatic Cancer Test, leveraging the 5-hydroxymethylation [5-hydroxymethylcytosine (5hmC)] signatures in cell-free DNA, was developed and analytically validated to address this unmet need. We report a comprehensive analytical validation study encompassing precision, sample stability, limit of detection, interfering substance studies, and a comparison with an alternative method. The assay performance on an independent case-control patient cohort was previously reported with a sensitivity for early-stage (stage I/II) pancreatic cancer of 68.3% (95% CI, 51.9%-81.9%) and an overall specificity of 96.9% (95% CI, 96.1%-97.7%). Precision studies showed a cancer classification of 100% concordance in biological replicates. The sample stability studies revealed stable assay performance for up to 7 days after blood collection. The limit of detection studies revealed equal results between early- and late-stage cancer samples, emphasizing strong early-stage performance characteristics. Comparisons of concordance of the Avantect assay with the enzymatic methyl sequencing (EM-Seq) method, which measures both methylation (5-methylcytosine) and 5hmC, were >95% for all samples tested. The Avantect Pancreatic Cancer Test showed strong analytical validation in multiple validation studies required for laboratory-developed test accreditation. The comparison of 5hmC versus EM-Seq further validated the 5hmC approach as a robust and reproducible assay.

A20 and ABIN1 Suppression of a Keratinocyte Inflammatory Program with a Shared Single-Cell Expression Signature in Diverse Human Rashes.

Genetic variation in the NF-κB inhibitors, ABIN1 and A20, increase risk for psoriasis. While critical for hematopoietic immune cell function, these genes are believed to additionally inhibit psoriasis by dampening inflammatory signaling in keratinocytes. We dissected ABIN1 and A20's regulatory role in human keratinocyte inflammation using an RNA sequencing-based comparative genomic approach. Here we show subsets of the IL-17 and tumor necrosis factor-α signaling pathways are robustly restricted by A20 overexpression. In contrast, ABIN1 overexpression inhibits these genes more modestly for IL-17, and weakly for tumor necrosis factor-α. Our genome-scale analysis also indicates that inflammatory program suppression appears to be the major transcriptional influence of A20/ABIN1 overexpression, without obvious influence on keratinocyte viability genes. Our findings thus enable dissection of the differing anti-inflammatory mechanisms of two distinct psoriasis modifiers, which may be directly exploited for therapeutic purposes. Importantly, we report that IL-17-induced targets of A20 show similar aberrant epidermal layer-specific transcriptional upregulation in keratinocytes from diseases as diverse as psoriasis, atopic dermatitis, and erythrokeratodermia variabilis, suggesting a contributory role for epidermal inflammation in a broad spectrum of rashes.