一种基于恶性细胞分化的新型间皮瘤分子分类。

A novel mesothelioma molecular classification based on malignant cell differentiation.

作者信息

Liu Jun, Liu Yifan, Lu Yuwei, Zhang Wei, Yan Jiale, Lu Bingnan, Yao Yuntao, Xian Shuyuan, Lyu Donghao, Shi Jiaying, Li Yuanan, Wu Xinru, Bai Chenguang, Zhang Jie, Zhang Yuan

机构信息

Department of Anesthesiology, Shanghai Pulmonary Hospital Affiliated to Tongji University School of Medicine, Shanghai, 200000, China.

Department of Urology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, No.1665 Kongjiang Road, Shanghai, 200092, China.

出版信息

Cancer Cell Int. 2025 Jun 24;25(1):235. doi: 10.1186/s12935-025-03816-9.

DOI:10.1186/s12935-025-03816-9

PMID:40555979

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12188665/

Abstract

BACKGROUND

The high heterogeneity and multi-directional poor differentiation of tumor cells in mesothelioma (MESO) contributes to tumor growth and malignant biological behaviors. However, a molecular classification based on differentiated states of tumor cells remains void.

METHODS

We performed dimensionality reduction analysis on the single-cell RNA sequencing profiles available from the GEO database, to visualize the cell types in MESO. Multi-omics analysis was done to supplement the plausibility of classification. We also constructed regulatory networks to detect the function of important tumor cell differential genes (TCDGs) in the MESO.

RESULTS

Following twice dimensionality reduction analysis and clustering, eight malignant cell subtypes in the MESO were visualized. According to the expression of TCDGs, MESO was classified into three subtypes (Malignant differentiation-related MESO, Benign differentiation-related MESO, and Neutral differentiation-related MESO) with prognostic differences. The prediction model was built by 12 key TCDGs (ALDH2, HP, CASP1, RTP4, PDZK1IP1, TOP2A, LOXL2, CKS2, SPARC, TLCD3A, C6orf99, and SERPINH1) and validated with high accuracy. In the regulatory networks of MESO subtypes, RTP4, CASP1, MYO1B, SLC7A5, LOXL2, and GHR were labeled as key genes. A total of 14 potential inhibitors were predicted. Clinical specimens validated the reliability of the clinical subtyping of MESO patients.

CONCLUSION

The novel molecular classification system and the prognostic prediction model might benefit the management of MESO patients.

摘要

背景

间皮瘤（MESO）中肿瘤细胞的高度异质性和多向低分化促成了肿瘤生长和恶性生物学行为。然而，基于肿瘤细胞分化状态的分子分类仍然空白。

方法

我们对来自基因表达综合数据库（GEO数据库）的单细胞RNA测序图谱进行降维分析，以可视化MESO中的细胞类型。进行多组学分析以补充分类的合理性。我们还构建了调控网络，以检测MESO中重要肿瘤细胞差异基因（TCDGs）的功能。

结果

经过两次降维分析和聚类后，可视化了MESO中的八种恶性细胞亚型。根据TCDGs的表达，MESO被分为三种亚型（恶性分化相关MESO、良性分化相关MESO和中性分化相关MESO），具有预后差异。由12个关键TCDGs（醛脱氢酶2、血红蛋白、半胱天冬酶1、受体转运蛋白4、PDZ结构域蛋白1相互作用蛋白1、拓扑异构酶Ⅱα、赖氨酰氧化酶2、细胞周期蛋白依赖性激酶2、富含半胱氨酸的酸性分泌蛋白、TLCD3A、6号染色体开放阅读框99和热休克蛋白47）构建预测模型，并进行了高精度验证。在MESO亚型的调控网络中，受体转运蛋白4、半胱天冬酶1、肌球蛋白1B、溶质载体家族7成员5、赖氨酰氧化酶2和生长激素受体被标记为关键基因。共预测了14种潜在抑制剂。临床标本验证了MESO患者临床分型的可靠性。