高级检索
当前位置: 首页 > 详情页

Single-cell transcriptomics reveals the role of Macrophage-Naive CD4+T cell interaction in the immunosuppressive microenvironment of primary liver carcinoma

文献详情

资源类型:
WOS体系:
Pubmed体系:

收录情况: ◇ SCIE

机构: [1]Department of Traditional Chinese Medicine, The First Afliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road II, Guangzhou 510080, Guangdong province, China [2]Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou 310058, Zhejiang province, China [3]Department of Biochemistry, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, Guangdong province, China [4]Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Sun Yat-Sen University, Guangzhou 510080, Guangdong province, China [5]Department of Histology and Embryology, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, Guangdong province, China [6]Guangdong Province Hospital of Chinese Medicine, AMI Key Laboratory of Chinese Medicine in Guangzhou, Guangzhou 510120, Guangdong province, China [7]Department of Experimental Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou 510060, Guangdong province, China
出处:
ISSN:

关键词: Single cell transcriptomic Macrophage Naive CD4+T cell Tumor microenvironment Immunosuppression

摘要:
Background: Liver carcinoma generally presents as an immunosuppressive microenvironment that promotes tumor evasion. The intercellular crosstalk of immune cells significantly influences the construction of an immunosuppressive microenvironment. This study aimed to investigate the important interactions between immune cells and their targeting drugs in liver carcinoma, by using single-cell and bulk transcriptomic data. Methods: Single-cell and bulk transcriptomic data were retrieved from Gene Expression Omnibus (GSE159977, GSE136103, and GSE125449) and The Cancer Genome Atlas (TGCA-LIHC), respectively. Quality control, dimension reduction, clustering, and annotation were performed according to the Scanpy workflow based on Python. Cell-cell interactions were explored using the CellPhone database and CellChat. Trajectory analysis was executed using a partition-based graph abstraction method. The transcriptomic factors (TFs) were predicted using single-cell regulatory network inference and clustering (SCENIC). The target genes from TFs were used to establish a related score based on the TCGA cohort; this score was subsequently validated by survival, gene set enrichment, and immune cell infiltration analyses. Drug prediction was performed based on the Cancer Therapeutics Response Portal and PRISM Repurposing datasets. Results: Thirty-one patients at four different states, including health, hepatitis, cirrhosis, and cancer, were enrolled in this study. After dimension reduction and clustering, twenty-two clusters were identified. Cell-cell interaction analyses indicated that macrophage-naive CD4 + T cell interaction significantly affect cancerous state. In brief, macrophages interact with naive CD4 + T cells via different pathways in different states. The results of SCENIC indicated that macrophages present in cancer cells were similar to those present during cirrhosis. A macrophage-naive CD4 + T cell (MNT) score was generated by the SCENIC-derived target genes. Based on the MNT score, five relevant drugs (inhibitor of polo-like kinase 1, inhibitor of kinesin family member 11, dabrafenib, ispinesib, and epothilone-b) were predicted. Conclusions: This study reveals the crucial role of macrophage-naive CD4 + T cell interaction in the immunosuppressive microenvironment of liver carcinoma. Tumor-associated macrophages may be derived from cirrhosis and can initiate liver carcinoma. Predictive drugs that target the macrophage-naive CD4 + T cell interaction may help to improve the immunosuppressive microenvironment and prevent immune evasion. The relevant mechanisms need to be further validated in experiments and cohort studies.

基金:
语种:
WOS:
PubmedID:
中科院(CAS)分区:
出版当年[2021]版:
大类 | 2 区 医学
小类 | 2 区 医学:研究与实验
最新[2025]版:
大类 | 2 区 医学
小类 | 2 区 医学:研究与实验
JCR分区:
出版当年[2020]版:
Q2 MEDICINE, RESEARCH & EXPERIMENTAL
最新[2023]版:
Q1 MEDICINE, RESEARCH & EXPERIMENTAL

影响因子: 最新[2023版] 最新五年平均 出版当年[2020版] 出版当年五年平均 出版前一年[2019版] 出版后一年[2021版]

第一作者:
第一作者机构: [1]Department of Traditional Chinese Medicine, The First Afliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road II, Guangzhou 510080, Guangdong province, China
共同第一作者:
通讯作者:
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:2018 今日访问量:0 总访问量:645 更新日期:2024-07-01 建议使用谷歌、火狐浏览器 常见问题

版权所有©2020 广东省中医院 技术支持:重庆聚合科技有限公司 地址:广州市越秀区大德路111号