Structural Lipidomics Uncovers CC Location-Specific Lipid Signatures and the Response to Immune Checkpoint Inhibitor...

Area of Science:

• Lipidomics and Cancer Research
• Mass Spectrometry-Based Lipid Analysis
• Biomarker Discovery for Colorectal Cancer

Background:

• Mismatch repair-deficient or microsatellite instability-high (dMMR/MSI-H) status is a predictor of anti-PD-1 therapy response in colorectal cancer (CRC).
• However, approximately half of dMMR/MSI-H CRC patients do not benefit from anti-PD-1 treatment, necessitating improved predictive biomarkers.
• Lipidomics, particularly with advanced techniques like Paternò-Büchi (PB) reaction-based LC-MS/MS, offers high-resolution lipid structural analysis relevant to cancer research.

Purpose of the Study:

• To apply advanced lipidomic techniques to profile serum lipids in dMMR/MSI-H CRC patients undergoing anti-PD-1 treatment.
• To identify novel lipidomic biomarkers that can predict therapeutic efficacy and patient response (complete response vs. progressive disease).
• To explore lipid remodeling patterns associated with anti-PD-1 treatment outcomes in this patient cohort.

Main Methods:

• Serum lipid profiling of 58 dMMR/MSI-H CRC patients using sequential LC-MS, LC-MS/MS, and LC-PB-MS/MS.
• Identification and structural resolution of glycerophospholipids, including C=C location.
• Statistical analysis (p-value, VIP score) and principal component analysis (PCA) to compare lipid profiles between responders and non-responders before and after treatment.

Main Results:

• A total of 814 glycerophospholipids were identified, with 285 resolved to the C=C location level.
• Significant differences in lipid profiles were observed between patients achieving complete response (CR) and progressive disease (PD), with 56 differential lipids pre-treatment and 214 post-treatment (p < 0.05, VIP >1).
• Specific lipids, including various phosphatidylcholines (PC), phosphatidylglycerols (PG), and phosphatidylinositols (PI), were identified as key indicators of treatment response, showing distinct patterns pre- and post-therapy.

Conclusions:

• LC-PB-MS/MS provides deep structural lipidomics, enabling the discovery of lipid signatures for stratifying dMMR/MSI-H CRC patients based on therapeutic outcomes.
• The identified lipid markers demonstrate potential for monitoring treatment response and guiding the development of novel therapeutic strategies in CRC.
• These findings highlight the utility of advanced lipidomics in precision oncology for predicting anti-PD-1 therapy efficacy.