Language
English
Publication Date
11-2-2023
Journal
bioRxiv
DOI
10.1101/2023.10.30.564760
PMID
37961688
PMCID
PMC10634942
PubMedCentral® Posted Date
11-2-2023
PubMedCentral® Full Text Version
Pre-Print
Abstract
No effective screening tools for ovarian cancer (OC) exist, making it one of the deadliest cancers among women. Considering little is known about the detailed progression and metastasis mechanism of OC at a molecular level, it is crucial to gain more insights on how metabolic and signaling alterations accompany its development. Herein, we present a comprehensive study using ultra-high-resolution Fourier transform ion cyclotron resonance matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to investigate the spatial distribution and alterations of lipids in ovarian tissues collected from double knockout (n = 4) and a triple mutant mouse models (n = 4) of high-grade serous ovarian cancer (HGSC). Lipids belonging to a total of 15 different classes were annotated and their abundance changes compared to those in healthy mouse reproductive tissue (n = 4), mapping onto major lipid pathways involved in OC progression. From intermediate-stage OC to advanced HGSC, we provide a direct visualization of lipid distributions and their biological links to inflammatory response, cellular stress, cell proliferation, and other processes. We also show the ability to distinguish tumors at different stages from healthy tissues via a number of highly specific lipid biomarkers, providing targets for future panels that could be useful in diagnosis.
Keywords
Mass spectrometry imaging, matrix-assisted laser desorption/ionization, high-grade serous ovarian cancer, lipidomics, biomarkers
Published Open-Access
yes
Recommended Citation
Ma, Xin; Botros, Andro; Yun, Sylvia R; et al., "Ultrahigh Resolution Lipid Mass Spectrometry Imaging of High-Grade Serous Ovarian Cancer Mouse Models" (2023). Faculty, Staff and Students Publications. 8164.
https://digitalcommons.library.tmc.edu/baylor_docs/8164