ArticleBMC cancer2025
Novel mRNA biomarker-based liquid biopsy for the detection of resectable pancreatic cancer.
Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- [Liquid Biopsy Revolutionizes the Precise Management of Tumors Across the Entire Course: Current Situation and Future Prospects].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026Pooled it
- Machine learning and artificial intelligence in liquid biopsy-based early detection of pancreatic cancer: a scoping review.BJC reports · 2026Review
- Catching pancreatic cancer early: Are we there yet?Journal of the National Cancer Center · 2026Review
- Artificial intelligence in pancreatic cancer histopathology and diagnostics - implications for clinical decisions and biomarker discovery?Cell division · 2025Review
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
backgroundPancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies and most often diagnosed at an advanced stage. Identification of markers for the early diagnosis of PDAC is crucial. In this study, we aimed to identify novel mRNA biomarkers for diagnosing PDAC, focusing on early-stage tumorigenesis and associated immunological changes.
methodsBlood samples and clinical information from 1,963 individuals were obtained from a single tertiary hospital between 2015 and 2021. Candidate mRNA biomarkers were identified through literature review, and their expression levels in buffy coat samples were measured using reverse-transcription quantitative polymerase chain reaction. Machine learning-based feature selection confirmed the final biomarker panel, which was tested using an independent dataset for diagnostic performance.
resultsIn total, 1,504 individuals (417 patients with PDAC and 1,087 non-disease controls) were eligible for the study. Among the 55 candidate biomarkers identified, 15 mRNAs (CCL5, CCR5, CLEC7A, CXCL8, CXCR2, CXCR4, FOXP3, IFNA1, IFNL1, PTGES, PTGES2, PTGS2, SLC27A2, TNF, and VEGFA) were selected based on their diagnostic performance in distinguishing PDAC from control groups. The final model, HELP-15 (Human Early Liquid biopsy for PDAC), identified all PDAC stages (area under the curve [AUC] = 0.956) in the test set. For resectable pancreatic cancer (RPC), the AUC was 0.968, compared to 0.910 for carbohydrate antigen 19 - 9 (CA19-9). The combined model of the panel and CA19-9 achieved an AUC of 0.985 in patients with RPC. For all PDAC stages in patients with normal CA19-9 levels, the AUC of the panel was 0.967, whereas CA19-9 alone or in combination with the panel had AUCs of 0.658 and 0.885, respectively.
conclusionCompared to CA19-9, the mRNA biomarker panel, HELP-15, improved diagnostic performance in patients with RPC, particularly in those with normal CA19-9 levels.
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