bioRxivBiochemistryPreprint
Early detection of pancreatic ductal adenocarcinoma by single-molecule profiling of pancreatic enzyme activities
Shingo X. SakamotoiD, Hideto HiraideiD, Junpei Hatakeyama, Takashi Kobayashi, Kazuki TakahashiiD, Takashi InagakiiD, Shizuka Takagi‐Niidome, Mayano Minoda, Tatsuya KawaguchiiD, Toru Shibayama, Nozomi Iwakura, Masami Kawana, Tadahaya MizunoiD, Mitsuyasu KawaguchiiD, H Nakagawa, Kyohhei FujitaiD, Yasuteru UranoiD, Atsuhiro MasudaiD, Juri IkemotoiD, Yasutaka IshiiiD, Shiro Oka, Keiji HanadaiD, Yuzo Kodama, Toru KomatsuiD, Yu KagamiiD
Abstract
Pancreatic ductal adenocarcinoma (PDAC) remains a leading cause of cancer-related mortality, largely due to diagnosis at advanced stages. Early detection through minimally invasive liquid biopsy holds promise for improving patient outcomes. Here, we report a blood-based liquid biopsy platform based on single-molecule enzyme activity profiling (SEAP), which detects proteoform-level alterations in circulating pancreatic enzymes at single-molecule resolution. Using a tissue-centric biomarker discovery strategy, we identified activity signatures of pancreas-specific digestive enzymes associated with PDAC. A combinatorial classifier detected PDAC (stage I-IV) with 95.5% specificity and 75.0% sensitivity (74.2% for stage I-II) across 690 blood samples collected from multiple hospitals and biobanks. Performance was further validated in an independent cohort enriched for early-stage disease, where 54.2% (13/24) of stage IA, 64.3% (9/14) of stage IB, and 21.4% (3/14) of stage 0 lesions were classified as positive. These findings support the clinical potential of SEAP for early detection of PDAC.
- organism: human
- assay: proteomics
- research focus: differential expression
- approach: deep learning
- approach: statistical model
- Citations
- 2
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