Integrative single-cell and multi-omics analyses reveal ferroptosis-associated gene expression and immune microenvironment heterogeneity in gastric cancer

被引:0
|
作者
Zhang, Shupeng [1 ,2 ]
Li, Zhaojin [1 ]
Hu, Gang [3 ]
Chen, Hekai [1 ]
机构
[1] Tianjin Fifth Cent Hosp, Dept Gen Surg, 41 Zhejiang Rd,Binhai New Area, Tianjin 300450, Peoples R China
[2] Tianjin Univ, Med Sch, 22 Tixiangting Rd, Tianjin 300070, Peoples R China
[3] Chinese Acad Med Sci & Peking Union Med Coll, Natl Clin Res Ctr Canc, Natl Canc Ctr, Dept Colorectal Surg,Canc Hosp, 17 Panjiayuannanli St, Beijing 100021, Peoples R China
关键词
Gastric cancer; Single-cell RNA sequencing; Differentially expressed genes; Gene co-expression network; Immune microenvironment; Biomarkers; SIGNATURE;
D O I
10.1007/s12672-025-01798-8
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Gastric cancer (GC), a prevalent malignancy worldwide, encompasses a multitude of biological processes in its progression. Recently, ferroptosis, a novel mode of cell demise, has become a focal point in cancer research. The microenvironment of gastric cancer is composed of diverse cell populations, yet the specific gene expression profiles and their association with ferroptosis are not well understood. Our study employed single-cell RNA sequencing to thoroughly investigate the transcriptomic profiles and identify differential gene expression in gastric cancer, offering fresh insights into the cellular diversity and underlying molecular mechanisms of this disease. We discovered a set of significantly differentially expressed genes in GC, which may serve as valuable leads for future functional investigations. Subsequent analyses, including gene set intersection and functional enrichment, pinpointed genes implicated in ferroptosis and conducted comprehensive Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses to elucidate their biological roles. In the gene selection and model validation section, critical genes were identified using machine learning algorithms, constructing a model with high predictive accuracy. Besides, distorted immune landscapes were further identified in RBL using ssGSEA analysis such that the complex association of gene expression features and its interaction networks as well as infiltration by various types of immune cells can be more clearly understood. Correlation analysis with different immune cell subtypes showed CTSB as an important regulator in the distributions of cancer infiltrating cells. Single-cell RNA sequencing analysis was utilized to map the cellular composition and gene expression profiles of cells in the gastric cancer microenvironment, which provide critical information for elucidating cellular heterogeneity as well as tumor microenvironment regulation in GC. Moreover, the distribution of FTH1, ZFP36 and CIRBP at different expression levels show new research prospects for functional information of these promoters in tumor microenvironment. In summary, the present study augments our knowledge of molecular mechanisms underlying gastric tumorigenesisa and provide scientific basis for identifing new targets and biomarkers in therapeutic diagnosis.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] A comprehensive analysis of gene expression and the immune landscape in gastric cancer through single-cell and multi-omics approaches
    Peng, Tao
    DISCOVER ONCOLOGY, 2024, 15 (01)
  • [2] Unveiling Lymphoma Microenvironment Heterogeneity through Single-Cell Multi-Omics Analysis
    Abe, Yoshiaki
    CANCER SCIENCE, 2025, 116 : 123 - 123
  • [3] Single-Cell Analyses in the Multi-omics Era
    Kalluri, Raghu
    Mead, Adam J.
    di Magliano, Marina Pasca
    Filbin, Mariella
    Carmeliet, Peter
    Amit, Ido
    CANCER CELL, 2020, 38 (01) : 9 - 10
  • [4] Integrative single-cell omics analyses reveal epigenetic heterogeneity in mouse embryonic stem cells
    Luo, Yanting
    He, Jianlin
    Xu, Xiguang
    Sun, Ming-an
    Wu, Xiaowei
    Lu, Xuemei
    Xie, Hehuang
    PLOS COMPUTATIONAL BIOLOGY, 2018, 14 (03)
  • [5] Multi-omics and single-cell sequencing analyses reveal the potential significance of circadian pathways in cancer therapy
    Lai, Hao
    Xiang, Xiaoyun
    Long, Xingqing
    Chen, Zuyuan
    Liu, Yanling
    Huang, Xiaoliang
    EXPERT REVIEW OF MOLECULAR DIAGNOSTICS, 2024, 24 (1-2) : 107 - 121
  • [6] Integrative Methods and Practical Challenges for Single-Cell Multi-omics
    Ma, Anjun
    McDermaid, Adam
    Xu, Jennifer
    Chang, Yuzhou
    Ma, Qin
    TRENDS IN BIOTECHNOLOGY, 2020, 38 (09) : 1007 - 1022
  • [7] Integration Analysis of Single-Cell Multi-Omics Reveals Prostate Cancer Heterogeneity
    Bian, Xiaojie
    Wang, Wenfeng
    Abudurexiti, Mierxiati
    Zhang, Xingming
    Ma, Weiwei
    Shi, Guohai
    Du, Leilei
    Xu, Midie
    Wang, Xin
    Tan, Cong
    Sun, Hui
    He, Xiadi
    Zhang, Chenyue
    Zhu, Yao
    Zhang, Min
    Ye, Dingwei
    Wang, Jianhua
    ADVANCED SCIENCE, 2024, 11 (18)
  • [8] Application of Single-Cell Multi-Omics in Dissecting Cancer Cell Plasticity and Tumor Heterogeneity
    Pan, Deshen
    Jia, Deshui
    FRONTIERS IN MOLECULAR BIOSCIENCES, 2021, 8
  • [9] Spatially Resolved Multi-Omics Single-Cell Analyses Inform Mechanisms of Immune Dysfunction in Pancreatic Cancer
    Yousuf, Suhail
    Qiu, Mengjie
    von Voithenberg, Lena Voith
    Hulkkonen, Johannes
    Macinkovic, Igor
    Schulz, Axel R.
    Hartmann, Domenic
    Mueller, Florian
    Mijatovic, Margarete
    Ibberson, David
    AlHalabi, Karam T.
    Hetzer, Jenny
    Anders, Simon
    Bruene, Bernhard
    Mei, Henrik E.
    Imbusch, Charles D.
    Brors, Benedikt
    Heikenwalder, Mathias
    Gaida, Matthias M.
    Buechler, Markus W.
    Weigert, Andreas
    Hackert, Thilo
    Roth, Susanne
    GASTROENTEROLOGY, 2023, 165 (04) : 891 - 908.e14
  • [10] Identifying Cancer Biomarkers with Single-Cell Multi-Omics
    Genetic Engineering and Biotechnology News, 2021, 41 (07): : 48 - 53