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

被引：16

作者：

Haan, David ^{[1
]}

Bergamaschi, Anna ^{[1
]}

Friedl, Verena ^{[2
]}

Guler, Gulfem D. ^{[2
]}

Ning, Yuhong ^{[2
]}

Reggiardo, Roman ^{[2
]}

Kesling, Michael ^{[2
]}

Collins, Micah ^{[1
]}

Gibb, Bill ^{[2
]}

Hazen, Kyle ^{[2
]}

Bates, Steve ^{[1
]}

Antoine, Michael ^{[1
]}

Fraire, Carolina ^{[1
]}

Lopez, Vanessa ^{[1
]}

Malta, Roger ^{[1
]}

Nabiyouni, Maryam ^{[1
]}

Nguyen, Albert ^{[1
]}

Phillips, Tierney ^{[1
]}

Riviere, Michael ^{[1
]}

Leighton, Anna ^{[1
]}

Ellison, Christopher ^{[1
]}

McCarthy, Erin ^{[1
]}

Scott, Aaron ^{[2
]}

Gigliotti, Lauren ^{[2
]}

Nilson, Eric ^{[2
]}

Sheard, Judith ^{[1
]}

Peters, Melissa ^{[1
]}

Bethel, Kelly ^{[1
]}

Chowdhury, Shimul ^{[1
]}

Volkmuth, Wayne ^{[2
]}

Levy, Samuel ^{[1
,3
]}

机构：

[1] ClearNote Hlth, San Diego, CA USA

[2] ClearNote Hlth, San Mateo, CA USA

[3] ClearNote Hlth, 10578 Sci Ctr Dr,Suite 210, San Diego, CA 92121 USA

来源：

CLINICAL GASTROENTEROLOGY AND HEPATOLOGY | 2023年 / 21卷 / 07期

关键词：

Liquid Biopsy; Early Cancer Detection; Pancreatic Cancer; Machine Learning; Epigenomic Profiling; New-Onset Diabetes; 5-HYDROXYMETHYLCYTOSINE SIGNATURES; METHYLATION; RISK;

D O I：

10.1016/j.cgh.2023.03.016

中图分类号：

R57 [消化系及腹部疾病];

学科分类号：

摘要：

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.

引用

页码：1802 / +

页数：14

共 27 条

[1]

Bachmann Jeannine, 2006, HPB (Oxford), V8, P346, DOI 10.1080/13651820600803981

[2] Epigenetic IVD Tests for Personalized Precision Medicine in Cancer [J].