Cell-free DNA testing for the detection and prognosis prediction of pancreatic cancer.

Abstract

Pancreatic cancer is known for its lethal condition, with most cases being diagnosed at advanced stage. Recently, liquid biopsy has emerged as a promising tool in cancer detection. Here we develop both an early detection model and a prognostic model for pancreatic cancer using cell-free DNA (cfDNA) end motif, fragmentation, nucleosome footprint (NF), and copy number alteration (CNA) features from plasma cfDNA. A total of 975 individuals were enrolled in our study. We developed an integrated model that demonstrated superior performance in distinguishing patients with early-stage pancreatic cancer from non-cancer controls. Moreover, we find that cfDNA features are associated with prognostic outcomes among pancreatic cancer patients. In this study, a cfDNA-based liquid biopsy signature is established for the early detection and prognostic prediction of pancreatic cancer. CfDNA may become a valuable tool for enhancing early diagnosis and prognosis assessment in this challenging disease.