Untargeted massspectrometry based lipidomics analysis reveals altered lipid profiles in a scribble knockdown-induced colorectal cancer model of Drosophila

Abstract

Abstract Cancer alters host metabolism to meet its nutritional demands. The role of lipids and their association with colorectal cancer (CRC) remains elusive. Scribble (Scrib) is a cell polarity regulator protein that also functions as a tumor suppressor. Scrib dysregulation has been reported in various advanced cancers, including CRC.In this study, we used tissue-specific GAL4-UASRNAi to knockdown Scrib in the Drosophila hindgut. Scrib knockdown led to the development of a CRC-like phenotype. Lipid droplets were enlarged in the adult fat body with tumor induction. We employed LC-MS-based untargeted lipidomics to explore global lipid changes in Scrib knockdown flies.Our analysis revealed alterations in total lipids, with 63 lipids upregulated, 48 downregulated, and 120 unaffected. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) revealed striking differences between wild-type and Scrib knockdown flies. Volcano plot analysis revealed that TAG 54:2, PIP2 35:6, PIP2 34:5, FFA 6:1, and PIP 37:2 were the top five significantly upregulated lipids, while TAG 52:1, GM3 38:2;3, GlcdE 2:6, PIP2 37:4, and PIP2 37:2 were the top five significantly downregulated lipids.Receiver operating characteristic (ROC) curve analysis identified TAG 54:2, PIP2 35:6, and PIP 42:2 as promising biomarker candidates.In summary, our results highlight the value of integrating LC-MS-based lipidomics with machine learning algorithms to explore significant lipid alterations at an organismal level in Scrib knockdown flies. These findings open avenues to investigate cancer-lipid interactions in CRC and related human cancers, potentially shedding light on new diagnostic and therapeutic opportunities.