RP-UHPLC/MS/MS Provides Enhanced Lipidomic Profiling of Human Serum in Pancreatic Cancer

Background

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers, mainly due to the late diagnosis and the lack of reliable biomarkers. Lipidomics provides a promising approach for identifying disease-related alterations, but existing methods are often limited to lipid class profiles with insufficient molecular detail. Reversed-phase ultrahigh-performance liquid chromatography coupled to tandem mass spectrometry (RP-UHPLC/MS/MS) offers the possibility to determine lipids at the fatty acyl/alkyl level. Here, we address the need for a validated quantitative workflow that enables accurate and reproducible lipidomic profiling of human serum in the context of PDAC.

Results

We developed and validated an RP-UHPLC/MS/MS method using multiple reaction monitoring, enabling identification of 455 lipid species from 22 subclasses and quantitation of 381 species. The workflow included a response factor correction for sterol esters, which markedly improved their quantification accuracy. The application to serum samples from 54 PDAC patients and 55 healthy controls yielded highly reproducible data, with clear group separation observed in both unsupervised and supervised statistical analyses. Dysregulation was most prominent in sphingolipids and phospholipids. Very long-chain saturated sphingolipids (≥ C22) were downregulated, while some shorter or unsaturated chains showed mild upregulation. Phospholipid alterations were dominated by species containing polyunsaturated fatty acyls, particularly 18:2 and 20:4, with plasmalogens showing the strongest changes. These structurally resolved findings were further supported by gas chromatography – mass spectrometry analysis of fatty acid methyl esters.

Significance

This validated workflow provides comprehensive quantitative coverage across 22 lipid subclasses with the structural resolution critical for biological interpretation. The detailed mapping of sphingolipid and phospholipid dysregulation in PDAC demonstrates that only the fatty acyl level annotation reveals molecular signatures that may reflect specific enzymatic activities or pathways. The method delivers a robust platform for biomarker discovery and mechanistic studies in cancer lipidomics.

HIGHLIGHTS

• Validated RP-UHPLC/MS/MS method quantifies 381 lipid species from 22 subclasses.

• Response factors improve the accuracy of sterol ester quantification.

• Lipidomic data enables clear discrimination of cancer and control groups.

• Molecular species resolution reveals hidden lipidomic alterations.

• Sphingolipid dysregulation is mainly determined by N -acyl chain composition.

GRAPHICAL ABSTRACT