Cell-free DNA testing for the detection and prognosis prediction of pancreatic cancer
Jianmin Wu, Xiongfei Xu, Qingzheng Zhang, Peilong Li, Tong Wu, Shiwei Guo, Lutao Du, Dongdong Xue, Siyun Shen, Fu-Ming Sun, Ji Hu, Lu Zheng, Xuan Wu, Jian Bai, Yin Wang, Lin Wu, Weiwei Liu, Hongyang Wang, Gang Jin, Lei Chen
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. 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.