Spatial lipidomics with in situ segmentation for profiling doxorubicin drug effect of hepatoma carcinoma cell spheroids

原位 化学 脂类学 球体 阿霉素 癌细胞 仿形(计算机编程) 细胞 癌症研究 抗癌药 药品 分子生物学 分割 细胞培养 生物物理学 体外 药物发现 色谱法 分子探针 计算生物学 原位癌
作者
Xiunan Xu,Luheng Sai,Yuanyuan Zhao,Yuanyuan Tuo,Fujuan Peng,Jinze Li,Qian Wang,Dongsheng Li,Huifang Zhao,Ruiping Zhang
出处
期刊:Analytical and Bioanalytical Chemistry [Springer Science+Business Media]
卷期号:418 (14): 4561-4573
标识
DOI:10.1007/s00216-026-06552-9
摘要

Three-dimensional tumor cell spheroids (3D TCS) with diameters exceeding 500 μm can closely mimic the cell-cell, cell-extracellular interactions, and tissue-specific architecture, which have been proved to serve as the appropriate models for evaluating the effects of anticancer drugs. However, it is challenging to profile the therapeutic effect of doxorubicin (DOX) on hepatocellular carcinoma (HCC) at the spatial molecular level. In our work, we established an effective and operable approach to in situ screen and visualize DOX-treated lipid alterations in each microregion from Hep-G2 cell spheroids by the high-spatial-resolution matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) approach. The 3D TCS showed great abundance and spatial distribution of endogenous lipid species at 10 μm spatial resolution. Based on the segmentation analysis, the core necrotic area, intermediate quiescent area, and outer proliferative area of individual 3D TCS were successfully characterized. Interestingly, we spatially screened and identified 71, 60, and 56 discrepant lipid molecules following the DOX treatment in the necrotic, quiescent, and proliferative areas, respectively. Enrichment analysis showed that the glycerophospholipid metabolism was the most distinct pathway in response to DOX treatment. Meanwhile, the aberrant metabolism was able to promote changes in PA, PC, PI, and SM, limiting the formation of the core necrotic area in the tumor spheroids treated with DOX. Overall, our proposed spatial lipidomics strategy exhibited a comprehensive understanding of the metabolic signatures associated with the DOX processing, which will provide the possibility to study the organoids or tumor tissues for patient-derived therapies.
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