ArticleScientific reports2026
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors.
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Abstract
Pancreatic cancer (PC) remains one of the most aggressive malignancies, characterized by late-stage diagnosis and poor prognosis. Identifying reliable biomarkers for early detection is crucial to improving survival outcomes. This study utilizes proton nuclear magnetic resonance (1H-NMR) metabolomics to analyze serum metabolic profiles and identify potential biomarkers differentiating PC patients from healthy controls (HC). Serum samples were collected from PC patients and matched HC individuals. 1H-NMR spectroscopy was employed to profile circulatory metabolites. Multivariate statistical analyses, including Principal Component Analysis (PCA) and Partial Least Squares Discriminates Analysis (PLS-DA), were conducted to distinguish between PC and HC groups. Receiver Operating Characteristic (ROC) curve analysis was performed to evaluate the diagnostic potential of key metabolites. Pathway enrichment analysis further elucidated the metabolic alterations associated with PC progression. The metabolomic profiling revealed distinct differences in metabolite composition between PC and HC groups. Amino acids, crucial for cellular metabolism and protein synthesis, were significantly reduced in the PC group (12.02%) compared to the HC group (18.43%). Conversely, carbohydrate metabolites, including glucose and lactate, were elevated in PC (56.92%) relative to HC (47.38%), indicating enhanced glycolytic activity. PCA and PLS-DA analyses confirmed clear metabolic separation between groups (PERMANOVA p = 0.001, PLS-DA R2 = 0.87, Q2 = 0.73). Key metabolites differentiating PC from HC included methanol, glycine, and lactate for PC, and valine, alanine, and methylhistidine for HC. ROC analysis identified alanine (AUC = 0.96), isoleucine (AUC = 0.92), and valine (AUC = 0.93) as potential diagnostic biomarkers. Pathway analysis revealed significant alterations in amino acid metabolism, notably the alanine, aspartate, and glutamate metabolism pathway. This study demonstrates the utility of 1H-NMR-based serum metabolomics in distinguishing PC from HC and identifies potential biomarkers for metabolic alterations associated with PC. The findings underscore the critical role of metabolic reprogramming in PC and offer promising avenues for developing non-invasive diagnostic tools. Further validation in larger cohorts is warranted to confirm the diagnostic potential of the identified biomarkers.
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