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

• Published in: Clinical gastroenterology and hepatology Vol. 21; no. 7; pp. 1802 - 1809.e6
• Main Authors: Haan, David, Bergamaschi, Anna, Friedl, Verena, Guler, Gulfem D., Ning, Yuhong, Reggiardo, Roman, Kesling, Michael, Collins, Micah, Gibb, Bill, Hazen, Kyle, Bates, Steve, Antoine, Michael, Fraire, Carolina, Lopez, Vanessa, Malta, Roger, Nabiyouni, Maryam, Nguyen, Albert, Phillips, Tierney, Riviere, Michael, Leighton, Anna, Ellison, Christopher, McCarthy, Erin, Scott, Aaron, Gigliotti, Lauren, Nilson, Eric, Sheard, Judith, Peters, Melissa, Bethel, Kelly, Chowdhury, Shimul, Volkmuth, Wayne, Levy, Samuel
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.07.2023
• Subjects: Cell-Free Nucleic Acids; Diabetes Mellitus, Type 2 - diagnosis; Early Cancer Detection; Early Detection of Cancer; Epigenomic Profiling; Epigenomics; Gastroenterology and Hepatology; Humans; Liquid Biopsy; Machine Learning; New-Onset Diabetes; Pancreatic Cancer; Pancreatic Neoplasms - diagnosis; Pancreatic Neoplasms - genetics; Liquid Biopsy; NOD; WGS; Early Cancer Detection; New-Onset Diabetes; CI; IPMN; Pancreatic Cancer; Machine Learning; CA19-9; 5hmC; Epigenomic Profiling; PaC; cfDNA; 5-hydroxymethylcytosine; intraductal papillary mucinous neoplasm; carbohydrate antigen 19-9; whole genome sequencing; cell-free DNA; confidence interval
• ISSN: 1542-3565; 1542-7714; 1542-7714
• DOI: 10.1016/j.cgh.2023.03.016

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. 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. 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%). 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. [Display omitted]