Abstract 118MO
Background
PDAC is a cancer of high mortality and low survival. Its early detection is critical due to symptoms often occur only at advanced stages. However, there is no reliable screening tool to identify high-risk patients. ctDNA methylation has recently emerged as a promising new target to differentiate PDAC plasma from normal plasma for its early detection.
Methods
Reduced representation bisulfite sequencing libraries were made in 46 PDAC tissues, 30 para-PDAC tissues and 20 PDAC plasmas to screen PDAC-specific markers, which was done by quantifying and comparing methylation levels of genomic regions and individual CpG sites between those groups. Markers were validated in plasma samples from 84 PDAC patients and 64 normal controls to propose a blood classifier. The best-performing markers were developed into a targeted sequencing panel, which was tested on a larger collection of plasma samples from patients of a variety of pancreatic diseases to build and validate a PDAC-predicting model.
Results
We profiled genome-wide methylation patterns of tissues samples to identify 171 PDAC-specific markers. We reiterated training and cross-validating PDAC classification models using SVM method and achieved an average sensitivity of 86% and specificity of 88%. To prove the feasibility of a non-invasive detection in plasma, a targeted methylation assay using those markers was tested on PDAC and normal plasmas and yielded an average sensitivity of 68.4% and a specificity of 85.8%. We refined the panel by selecting the most discriminatory markers and built a smaller panel for a more efficient target capture, which is validated in an independent cohort of 200 plasma samples that included PDAC, chronic pancreatitis (CP) and normals from multiple centers. The smaller panel achieved an AUC above 0.90 when classifying PDAC from normals, and an AUC of 0.88 when separating PDAC from CPs.
Conclusions
We have developed an NGS based target assay covering PDAC-specific DNA methylation targets by screening and validation on PDAC tissues and plasmas. It has shown encouraging results to classify PDAC plasma from non-malignant diseases, demonstrating its potential to be optimized into non-invasive diagnostics for blood-based early PDAC screening.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Peking Union Hospital.
Funding
Intergovernmental Cooperation Fund of China Science and Technology Exchange Center.
Disclosure
Q. He, Z. Su: Shareholder/Stockholder/Stock options, Full/Part-time employment: Singlera Genomics. C. Ma, Z. Xie: Full/Part-time employment: Singlera Genomics. R. Liu: Leadership role, Shareholder/Stockholder/Stock options, Full/Part-time employment: Singlera Genomics. All other authors have declared no conflicts of interest.
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