LipidQuan: A Rapid and Comprehensive Targeted Approach Investigating the Lipidome of Bladder Cancer Subjects

Significance of the Topic

A targeted lipidomics strategy enables rapid, sensitive quantification of hundreds of lipid species in plasma. Alterations in lipid metabolism are closely linked to bladder cancer pathogenesis, affecting cell signaling, apoptosis, and drug resistance. Comprehensive profiling of lipid changes can accelerate biomarker discovery and improve understanding of disease mechanisms.

Study Objectives and Overview

This work applied the LipidQuan workflow to compare plasma lipidomes of six bladder cancer patients and six healthy controls. Key goals were to deploy a pre‐configured targeted method, achieve robust quantification of ~500 lipids, and identify lipid signatures that distinguish disease and control cohorts.

Methodology and Instrumentation

Plasma proteins were precipitated with ice‐cold isopropanol spiked with odd‐chain standards. Extracts were analyzed in duplicate using Waters ACQUITY UPLC I-Class PLUS systems coupled to Xevo TQ-XS and TQ-S micro triple quadrupole mass spectrometers. A HILIC BEH Amide column separated lipid classes under a gradient, and MRM transitions targeting two fatty acyl moieties per lipid ensured specificity. Quantification employed nine‐level calibration curves from SPLASH® LIPIDOMIX® internal standards. Data acquisition and processing were performed using TargetLynx Application Manager and Skyline, with statistical evaluation via SIMCA P+ and MetaboAnalyst.

Main Results and Discussion

An eight‐minute LC-MS/MS run enabled identification of over 400 lipids. Unsupervised PCA achieved clear separation between cancer and control samples (R2 = 0.93, Q2 = 0.91). VIP scores and hierarchical clustering indicated elevated lysophosphatidylcholines, phosphatidylcholines, and sphingomyelins in cancer subjects, while plasmalogens and phosphatidylethanolamines were reduced. ANOVA with 1% false discovery rate highlighted statistically significant changes. Calibration curves showed linearity (R2 = 0.97–0.99) across lipid classes.

Benefits and Practical Applications

• Pre‐built method reduces development time and training requirements.
• High throughput with an eight-minute runtime and minimal sample preparation.
• Class‐based HILIC separation lowers the number of isotope standards needed, reducing cost.
• Accurate targeted quantification supports biomarker research, QA/QC, and longitudinal studies.

Future Trends and Opportunities

Expanding targeted panels to include oxidized and minor lipid species will deepen metabolic insights. Integration with proteomics and transcriptomics, advanced machine-learning analytics, and pathway mapping can enhance biological interpretation. Further automation and miniaturization may facilitate routine clinical application for precision diagnostics and therapeutic monitoring.

Conclusion

The LipidQuan targeted workflow provides a rapid, robust, and comprehensive platform for plasma lipid profiling. Its ability to discriminate bladder cancer patients from healthy controls demonstrates its value for biomarker discovery and potential clinical translation.

Reference

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