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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. Pancreatic cancer detection can be challenging, and is often diagnosed at a late stage. Here, the authors present a cfDNA-based liquid biopsy model that enables early detection and prognosis prediction of pancreatic cancer.
Wu et al. (Fri,) studied this question.