A novel mesothelioma molecular classification based on malignant cell differentiation.

IF 6 2区医学 Q1 ONCOLOGY

Cancer Cell International Pub Date : 2025-06-24 DOI:10.1186/s12935-025-03816-9

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

{"title":"A novel mesothelioma molecular classification based on malignant cell differentiation.","authors":"Jun Liu, Yifan Liu, Yuwei Lu, Wei Zhang, Jiale Yan, Bingnan Lu, Yuntao Yao, Shuyuan Xian, Donghao Lyu, Jiaying Shi, Yuanan Li, Xinru Wu, Chenguang Bai, Jie Zhang, Yuan Zhang","doi":"10.1186/s12935-025-03816-9","DOIUrl":null,"url":null,"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.","PeriodicalId":9385,"journal":{"name":"Cancer Cell International","volume":"25 1","pages":"235"},"PeriodicalIF":6.0000,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12188665/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Cell International","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12935-025-03816-9","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}

引用次数: 0

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.

查看原文本刊更多论文

一种基于恶性细胞分化的间皮瘤分子分类新方法。

背景：间皮瘤（mesothelioma， MESO）肿瘤细胞异质性高、多向分化差，是影响肿瘤生长和恶性生物学行为的重要因素。然而，基于肿瘤细胞分化状态的分子分类仍然是空白的。方法：对GEO数据库提供的单细胞RNA测序图谱进行降维分析，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来检测重要肿瘤细胞差异基因（TCDGs）在MESO中的功能。结果：经二次降维分析和聚类，可见MESO中8种恶性细胞亚型。根据TCDGs的表达将MESO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），且预后不同。该预测模型由12个关键TCDGs （ALDH2、HP、CASP1、RTP4、PDZK1IP1、TOP2A、LOXL2、CKS2、SPARC、TLCD3A、C6orf99和SERPINH1）构建，并验证具有较高的准确性。在MESO亚型的调控网络中，RTP4、CASP1、MYO1B、SLC7A5、LOXL2和GHR被标记为关键基因。共预测了14种潜在的抑制剂。临床标本验证了MESO患者临床分型的可靠性。结论：新的分子分类系统和预后预测模型可能有助于MESO患者的治疗。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Cancer Cell International ONCOLOGY-

CiteScore

10.90

自引率

1.70%

发文量

360

审稿时长

1 months

期刊介绍： Cancer Cell International publishes articles on all aspects of cancer cell biology, originating largely from, but not limited to, work using cell culture techniques. The journal focuses on novel cancer studies reporting data from biological experiments performed on cells grown in vitro, in two- or three-dimensional systems, and/or in vivo (animal experiments). These types of experiments have provided crucial data in many fields, from cell proliferation and transformation, to epithelial-mesenchymal interaction, to apoptosis, and host immune response to tumors. Cancer Cell International also considers articles that focus on novel technologies or novel pathways in molecular analysis and on epidemiological studies that may affect patient care, as well as articles reporting translational cancer research studies where in vitro discoveries are bridged to the clinic. As such, the journal is interested in laboratory and animal studies reporting on novel biomarkers of tumor progression and response to therapy and on their applicability to human cancers.