基础医学与临床 ›› 2026, Vol. 46 ›› Issue (6): 815-822.doi: 10.16352/j.issn.1001-6325.2026.06.0815

• 研究论文 • 上一篇    下一篇

肝细胞癌肿瘤边界代谢空间异质性研究

李书翔1, 潘玮瑄2, 保永莉1, 夏婉娉1, 李雪媛1, 郑永昌2*, 陈阳1*   

  1. 1.中国医学科学院北京协和医学院 基础医学研究所 生物化学与分子生物学系 重大疾病共性机制研究全国重点实验室,北京 100005;
    2.中国医学科学院北京协和医院 肝脏外科, 北京 100730
  • 收稿日期:2026-03-09 修回日期:2026-04-10 出版日期:2026-06-05 发布日期:2026-05-27
  • 通讯作者: *zhengyongchang@pumch.cn; yc@ibms.pumc.edu.cn
  • 基金资助:
    国家自然科学基金面上项目(82573269,32570755);中国医学科学院医学与健康科技创新工程(2025-I2M-FGS-003)

Study on metabolic spatial heterogeneity of hepatocellular carcinoma tumor boundary

LI Shuxiang1, PAN Weixuan2, BAO Yongli1, XIA Wanping1, LI Xueyuan1, ZHENG Yongchang2*, CHEN Yang1*   

  1. 1. State Key Laboratory of Common Mechanism Research for Major Diseases, Department of Biochemistry and Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of MedicalSciences & Peking Union Medical College, Beijing 100005;
    2. Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
  • Received:2026-03-09 Revised:2026-04-10 Online:2026-06-05 Published:2026-05-27
  • Contact: *zhengyongchang@pumch.cn; yc@ibms.pumc.edu.cn

摘要: 目的 利用飞行时间二次离子质谱(TOF-SIMS)技术探究肝细胞癌患者肿瘤边界组织代谢的空间异质性,并解析关键代谢物在空间分布上的特征。方法 获取肝细胞癌患者癌旁组织样本后进行速冻包埋,使用冰冻切片技术制成连续组织切片,采用飞行时间二次离子质谱对组织切片进行空间代谢组学分析。利用SEAM算法对质谱数据进行单细胞水平的聚类分析和空间映射。 结果TOF-SIMS结合SEAM算法成功实现了对肝癌边界组织的高分辨空间代谢组分析。结果 显示肿瘤组织内外及肿瘤组织内部均存在明显的代谢异质性,其中肿瘤组织内部可细分为两个具有不同代谢特征的细胞亚群。差异代谢物分析鉴定出两个关键的磷酸根相关离子(m/z=62.97 和 m/z=78.96)。空间分布定量研究显示,高磷酸根代谢(PM+)的细胞群显著富集在靠近肿瘤边界的区域。 结论 肝癌肿瘤边界存在显著的空间代谢重塑,PM+细胞边界富集特征提示肿瘤边界的机械力环境可能调节了癌细胞的代谢状态。

关键词: 肝细胞癌, 空间代谢组, TOF-SIMS, 肿瘤边界, 空间异质性

Abstract: Objective To explore the spatial heterogeneity of tumor boundary tissue metabolism in hepatocellular carcinoma (HCC) patients using time-of-flight secondary ion mass spectrometry (TOF-SIMS), and to analyze the characteristics of key metabolites in spatial distribution. Methods After obtaining adjacent non-tumor tissue samples from HCC patients, the samples were snap-frozen and embedded. Serial tissue sections were prepared using frozen section technology, and spatial metabolomic analysis was performed on the tissue sections using TOF-SIMS. The mass spectrometry data were clustered and spatially mapped at the single-cell level using the SEAM algorithm. Results TOF-SIMS combined with the SEAM algorithm successfully achieved high-resolution spatial metabolomic analysis of HCC boundary tissue. The results showed significant metabolic heterogeneity between the intra-and extra-tumoral regions, as well as within the tumor parenchyma, which could be subdivided into two cell subpopulations with different metabolic characteristics. Differential metabolite analysis identified two key phosphate-related ions (m/z=62.97 and m/z=78.96). Quantitative spatial distribution studies revealed that cell populations with high phosphate metabolism (PM+) were significantly enriched in areas close to the tumor boundary. Conclusions There is significant spatial metabolic remodeling at the HCC tumor boundary, and the boundary enrichment characteristics of PM+ cells suggest that the mechanical force environment at the tumor boundary may regulate the metabolic state of cancer cells.

Key words: hepatocellular carcinoma, spatial metabolomics, TOF-SIMS, tumor boundary, spatial heterogeneity

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