Stage-specific lipidomic signatures as biomarkers in progression of cervical cancer.

Authors

Akshata Kishore Karekar, Sandhya Kaustubh Kamat, Padmaja Yashwant Samant, Sucheta Prakash Dandekar, Dinesh Amrith Uchil, Mayuri Nalinkumar Gandhi, Jayanti Mania-Pramanik, Shilpa Chandrakant Kerkar

Published in

The Indian journal of medical research. Volume 164. Issue 3. Pages 349-356.

Abstract

Background and objectives Lipidomics has advanced cancer research by uncovering biomarkers that reveal key mechanisms of tumourigenesis. By analysing endpoint lipid metabolites influenced by genetic and environmental factors, the lipidome closely reflects a cell's functional state. Mass spectrometry, strengthened by modern bioinformatics and biostatistics, now enables precise detection of cancer-related lipid changes, motivating us to adopt this approach. Methods We have applied advanced mass spectrometry and machine-learning methods to develop a novel tool for cervical cancer screening, the second most common cancer in India. The study included cervical cancer patients diagnosed through cytology, HPV testing, histopathology, or imaging, along with healthy volunteers as controls. Serum samples from all participants were analysed using Ultra High Performance Liquid Chromatography coupled with high-resolution Orbitrap Mass Spectrometry using a targeted approach for lipid biomarker discovery. Results A comprehensive evaluation of controls and cervical cancer patients across clinical stages revealed distinct lipidomic patterns and biomarker differences. We identified a 3-biomarker panel [LPE (22:6)+H, PE (18:1_20:4)+H, and MG (20:0)+H] effective for early-stage detection and a 4-biomarker panel (LPE (22:6)+H, PE (18:1_20:4)+H, PC (16:1_20:5)+H, and TG (16:0_18:1_18:3)+H) suitable for comprehensive cervical cancer screening. The combined ROC for the 3-biomarker panel showed 88% sensitivity, 93% specificity, 90% accuracy, and an area under the curve (AUC) of 0.945, while the 4-biomarker panel achieved 87% sensitivity, 84% specificity, 86% accuracy, and an AUC of 0.946. Interpretation and conclusions Our study demonstrates a clear link between altered lipid metabolism and cervical cancer, paving the way for future research to identify new diagnostic and prognostic markers and ultimately enabling earlier detection and timely intervention.

PMID:
42690850
Bibliographic data and abstract were imported from PubMed on 04 Sep 2026.

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