Citation: Guosheng He, Qingce Zang, Zhenran Si, Xiaojing Zhang, Lingzhi Wang, Zhijun Qin, Jingshu Hu, Fei Li, Can Wang, Hengyu Wang, Kexin Chang, Ruiping Zhang, Xiuwei Chen. Spatially resolved profiling of reprogrammed metabolism in ovarian cancer using ambient mass spectrometry imaging[J]. Chinese Chemical Letters, ;2026, 37(11): 112564. doi: 10.1016/j.cclet.2026.112564 shu

Spatially resolved profiling of reprogrammed metabolism in ovarian cancer using ambient mass spectrometry imaging

Guosheng He ^{a, 1} ,
Qingce Zang ^{b, 1} ,
Zhenran Si ^b ,
Xiaojing Zhang ^b ,
Lingzhi Wang ^b ,
Zhijun Qin ^a ,
Jingshu Hu ^a ,
Fei Li ^b ,
Can Wang ^a ,
Hengyu Wang ^a ,
Kexin Chang ^a ,
Ruiping Zhang ^{b, *,} ,
Xiuwei Chen ^{a, *,}

a.
Department of Gynecologic Oncology, Harbin Medical University Cancer Hospital, Harbin 150000, China
b.
State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China

rpzhang@imm.ac.cn

1427@hrbmu.edu.cn

Received Date: 15 August 2025
Revised Date: 22 January 2026
Accepted Date: 28 February 2026
Available Online: 1 March 2026

Figures(4)

Ovarian cancer is a lethal gynecological malignancy in adult women. Metabolic reprogramming not only facilitates the survival and proliferation of ovarian cancer cells but also contributes to metastasis and chemoresistance acquisition. Spatially resolved profiling of aberrant metabolic patterns in ovarian cancer tissues can reveal tumor-specific metabolic alterations underlying cancer development and progression. Here, we employed ambient airflow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) to characterize the metabolic profiles of high-grade serous ovarian carcinoma and normal ovarian tissues. AFADESI-MSI enabled clear visualization of a broad range of small molecules, spanning from polar metabolites to lipids. Spatial mapping revealed tumor-specific metabolite accumulation or depletion, with distinct patterns aligned to histological boundaries. Tumor and non-tumor regions were distinctly demarcated based exclusively on region-specific metabolite distributions. Spatially resolved metabolomics analysis identified 127 differential metabolites, predominantly lipids (69.29%), including fatty acyls, glycerophospholipids, steroids, and glycerolipids. The dysregulated metabolic pathways encompassed unsaturated fatty acid biosynthesis, steroid hormone metabolism, glycerophospholipid metabolism, and amino acid metabolism. Overall, this technique uncovered tumor-associated metabolic alterations, demonstrating potential to augment histological diagnosis and identify therapeutic metabolic vulnerabilities in ovarian cancer.
- Mass spectrometry imaging,
- Spatial metabolomics,
- Ovarian cancer,
- Metabolic reprogramming,
- Dysregulated metabolic pathway
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