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Abstract
Background
Pancreatic 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.
Methods
Blood 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.
Results
In 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.
Conclusion
Compared 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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