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<p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月18日

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  • Jianmin Wu,
  • Xiongfei Xu,
  • Qingzheng Zhang,
  • Peilong Li,
  • Tong Wu,
  • Shiwei Guo,
  • Lutao Du,
  • Dongdong Xue,
  • Siyun Shen,
  • Fuming Sun,
  • Ji Hu,
  • Lu Zheng,
  • Xuan Wu,
  • Jian Bai,
  • Yin Wang,
  • Lin Wu,
  • Weiwei Liu,
  • Hongyang Wang,
  • Gang Jin,
  • Lei Chen

摘要

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.