DataSheet1_Ultrahigh resolution lipid mass spectrometry imaging of high-grade serous ovarian cancer mouse models.DOCX

No effective screening tools for ovarian cancer (OC) exist, making it one of the deadliest cancers among women. Considering that little is known about the detailed progression and metastasis mechanism of OC at a molecular level, it is crucial to gain more insights into 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 triple mutant mouse models (n = 4) of high-grade serous ovarian cancer (HGSOC). Lipids belonging to a total of 15 different classes were annotated and their abundance changes were 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 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.

目前尚无有效的卵巢癌（Ovarian Cancer, OC）筛查工具，使其成为女性群体中致死率最高的恶性肿瘤之一。鉴于目前在分子层面对卵巢癌的具体进展与转移机制尚缺乏深入了解，解析其发生发展过程中伴随的代谢与信号通路改变具有重要意义。本研究采用超高分辨傅里叶变换离子回旋共振-基质辅助激光解吸电离（Matrix-assisted Laser Desorption/Ionization, MALDI）质谱成像（Mass Spectrometry Imaging, MSI）技术，对高级别浆液性卵巢癌（High-grade Serous Ovarian Cancer, HGSOC）的双基因敲除（n=4）与三突变小鼠模型（n=4）的卵巢组织开展分析，以探究脂质在该类组织中的空间分布与含量变化。本研究共注释了15个不同类别的脂质，并将其丰度变化与健康小鼠生殖组织（n=4）的脂质丰度进行对比，同时将变化映射至与卵巢癌进展相关的主要脂质代谢通路中。从卵巢癌中期进展至高级别浆液性卵巢癌晚期阶段，本研究实现了脂质分布的直接可视化，并揭示了其与炎症反应、细胞应激、细胞增殖等生物学过程的关联。此外，本研究证实可通过多种高特异性脂质生物标志物区分不同分期的肿瘤组织与健康组织，为未来可用于临床诊断的脂质检测组合提供了潜在靶点。