Author(s)

Youjanya G Dongardive

  • Manuscript ID: 140175
  • Volume: 2
  • Issue: 3
  • Pages: 86–104

Subject Area: Computer Science

DOI: https://doi.org/10.64643/JATIRV2I3-140175-001
Abstract

Background: Pancreatic cancer is among the most lethal malignancies, with a five-year survival rate of approximately 13%. This poor prognosis is mainly due to the absence of reliable strategies for early detection. Current diagnostic approaches depend largely on imaging techniques, which are often expensive, invasive, and insufficient for identifying disease at an early stage. Consequently, the development of a sensitive and specific non-invasive blood-based screening method could significantly improve early diagnosis and patient survival.
Methods: In this study, lipid concentrations in plasma and serum samples were analyzed using ultra-high-performance supercritical fluid chromatography coupled with mass spectrometry (UHPSFC-MS). Multivariate statistical analysis was applied to evaluate lipidomic patterns and to distinguish between different study groups.
Results: This pilot investigation included prospectively collected samples from patients diagnosed with Pancreatic ductal adenocarcinoma (PDAC; n = 177), healthy individuals (n = 218), and participants considered at high risk for pancreatic cancer (n = 93). Lipidomic profiling successfully differentiated PDAC patients from healthy controls with an accuracy exceeding 95%. The method also demonstrated strong capability for detecting early-stage cases and identifying individuals with low secretion of CA 19-9. The sensitivity of the lipidomic approach was approximately 30% higher than that of CA 19-9. In the high-risk cohort, the method achieved a specificity greater than 96% (95% CI: 89–99%), comparable to established imaging-based diagnostic strategies.
Conclusion: The findings from this pilot study highlight the potential of lipidomic profiling as a non-invasive blood-based screening approach for pancreatic cancer. The technique demonstrates improved diagnostic performance compared with conventional biomarkers and maintains high accuracy in early-stage disease as well as in high-risk populations. These results support the need for larger clinical trials to further validate lipidomic testing for early detection of PDAC.

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