文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

利用单细胞RNA测序分析影响肺癌风险的LGR5+细胞的癌症干细胞特征

The cancer stem cells characteristics analysis of LGR5 + cells that influence lung cancer risk by using single cell RNA-seq analysis.

作者信息

Wen Ge, Niu Shaoqing, Mei Shiqi, Wang Senming

机构信息

Department of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, 510280, China.

Department of Radiation Oncology, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510150, China.

出版信息

Sci Rep. 2025 May 8;15(1):16085. doi: 10.1038/s41598-025-00585-3.


DOI:10.1038/s41598-025-00585-3
PMID:40341189
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12062498/
Abstract

Lung adenocarcinoma (LUAD) is the most popular lung cancer type with highly mortality. We performed a single cell RNA-seq analysis to explore characteristic of cancer stem cells in LUAD. We downloaded the single cell RNA-seq data (GSE149655) from the GEO database, the scRNA-seq analysis was performed by using the "Seurat" and "harmony" R package. The FindMarkers function and "ClusterProlifer" package was used for differentially expressed genes (DEGs) and function enrichment analysis. The protein-protein interaction and transcriptional regulatory network were performed by STRING and ChIPBase database. Immunohistochemistry tests to be used to observe differences in the expression of specific genes in LUAD and paracancerous tissue samples. BEAS-2B and A549 cells was used for vitro assay and the qRT-PCR, western blotting, wound healing, trans-well assays, EdU tests, and flow cytometry were performed. A total of 9 cell clusters were obtained after scRNA-seq analysis, in which the cancer stem cells had higher proportion in LUAD samples. Subsequently, function enrichment analysis revealed that the amino sugar and nucleotide sugar metabolism and DNA replication pathways were activated in cancer stem cells (CSCs), which were further sub-divided into 3 subtypes, the LGR5 + stem cell is a major contributor to cancer progression, its hub genes, such as HLA-DPB1, CD74, CTSH and HLA-DRB5 mediated the unique transcriptional state. In addition, the marker genes of three CSCs were also overexpressed in LUAD cells and the CXCL3 played an important role in mediating cell proliferation, apoptosis, migration and invasion of tumor. We performed a scRNA-seq analysis and identified the LGR5 + stem cell as a major contributor in LUAD progression, our findings are expected to provide new insights into the pathogenesis of LUAD.

摘要

肺腺癌(LUAD)是最常见且死亡率极高的肺癌类型。我们进行了单细胞RNA测序分析,以探究LUAD中癌症干细胞的特征。我们从GEO数据库下载了单细胞RNA测序数据(GSE149655),使用“Seurat”和“harmony”R包进行scRNA-seq分析。利用FindMarkers函数和“ClusterProlifer”包进行差异表达基因(DEG)和功能富集分析。通过STRING和ChIPBase数据库构建蛋白质-蛋白质相互作用和转录调控网络。采用免疫组织化学检测观察LUAD和癌旁组织样本中特定基因表达的差异。使用BEAS-2B和A549细胞进行体外实验,并进行qRT-PCR、蛋白质免疫印迹、伤口愈合、Transwell实验、EdU检测和流式细胞术。scRNA-seq分析后共获得9个细胞簇,其中癌症干细胞在LUAD样本中的比例更高。随后的功能富集分析表明,氨基糖和核苷酸糖代谢以及DNA复制途径在癌症干细胞(CSC)中被激活,这些细胞进一步细分为3个亚型,LGR5 +干细胞是癌症进展的主要贡献者,其枢纽基因如HLA-DPB1、CD74、CTSH和HLA-DRB5介导了独特的转录状态。此外,三种CSC的标记基因在LUAD细胞中也过表达,且CXCL3在介导肿瘤细胞增殖、凋亡、迁移和侵袭中起重要作用。我们进行了scRNA-seq分析,并确定LGR5 +干细胞是LUAD进展的主要贡献者,我们的研究结果有望为LUAD的发病机制提供新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a448/12062498/c45b84d6984a/41598_2025_585_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a448/12062498/c009fc2c34d2/41598_2025_585_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a448/12062498/a37845dec714/41598_2025_585_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a448/12062498/783f9d3828a4/41598_2025_585_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a448/12062498/9f7d458213d5/41598_2025_585_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a448/12062498/c51ad322d3a6/41598_2025_585_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a448/12062498/c54eb4fbcb2d/41598_2025_585_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a448/12062498/c45b84d6984a/41598_2025_585_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a448/12062498/c009fc2c34d2/41598_2025_585_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a448/12062498/a37845dec714/41598_2025_585_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a448/12062498/783f9d3828a4/41598_2025_585_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a448/12062498/9f7d458213d5/41598_2025_585_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a448/12062498/c51ad322d3a6/41598_2025_585_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a448/12062498/c54eb4fbcb2d/41598_2025_585_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a448/12062498/c45b84d6984a/41598_2025_585_Fig7_HTML.jpg

相似文献

[1]
The cancer stem cells characteristics analysis of LGR5 + cells that influence lung cancer risk by using single cell RNA-seq analysis.

Sci Rep. 2025-5-8

[2]
Identification of differentially expressed genes in lung adenocarcinoma cells using single-cell RNA sequencing not detected using traditional RNA sequencing and microarray.

Lab Invest. 2020-4-23

[3]
Integration of single-cell and bulk RNA sequencing to identify a distinct tumor stem cells and construct a novel prognostic signature for evaluating prognosis and immunotherapy in LUAD.

J Transl Med. 2025-2-22

[4]
B-cell signatures characterize the immune landscape and predict LUAD prognosis via the integration of scRNA-seq and bulk RNA-seq.

Sci Rep. 2025-2-14

[5]
Identification of a novel therapeutic candidate, NRK, in primary cancer-associated fibroblasts of lung adenocarcinoma microenvironment.

J Cancer Res Clin Oncol. 2021-4

[6]
RNA-seq and bulk RNA-seq data analysis of cancer-related fibroblasts (CAF) in LUAD to construct a CAF-based risk signature.

Sci Rep. 2024-10-6

[7]
Integrated analysis of single-cell RNA-seq and bulk RNA-seq reveals immune suppression subtypes and establishes a novel signature for determining the prognosis in lung adenocarcinoma.

Cell Oncol (Dordr). 2024-10

[8]
Single-cell RNA sequencing reveals immune microenvironment niche transitions during the invasive and metastatic processes of ground-glass nodules and part-solid nodules in lung adenocarcinoma.

Mol Cancer. 2024-11-23

[9]
Predictions of the dysregulated competing endogenous RNA signature involved in the progression of human lung adenocarcinoma.

Cancer Biomark. 2020

[10]
Ligand-receptor interaction atlas within and between tumor cells and T cells in lung adenocarcinoma.

Int J Biol Sci. 2020

本文引用的文献

[1]
Sanguinarine Attenuates Lung Cancer Progression via Oxidative Stress-induced Cell Apoptosis.

Curr Mol Pharmacol. 2024

[2]
Cancer statistics, 2024.

CA Cancer J Clin. 2024

[3]
The Mediating Role of miR-451/ETV4/MMP13 Signaling Axis on Epithelialmesenchymal Transition in Promoting Non-small Cell Lung Cancer Progression.

Curr Mol Pharmacol. 2024

[4]
Candidate pathway analysis of surfactant proteins identifies CTSH and SFTA2 that influences lung cancer risk.

Hum Mol Genet. 2023-9-5

[5]
KRT17 Promotes T-lymphocyte Infiltration Through the YTHDF2-CXCL10 Axis in Colorectal Cancer.

Cancer Immunol Res. 2023-7-5

[6]
Comprehensive analysis of scRNA-Seq and bulk RNA-Seq reveals dynamic changes in the tumor immune microenvironment of bladder cancer and establishes a prognostic model.

J Transl Med. 2023-3-27

[7]
Single-cell analysis of multiple cancer types reveals differences in endothelial cells between tumors and normal tissues.

Comput Struct Biotechnol J. 2022-12-30

[8]
ChIPBase v3.0: the encyclopedia of transcriptional regulations of non-coding RNAs and protein-coding genes.

Nucleic Acids Res. 2023-1-6

[9]
KEGG for taxonomy-based analysis of pathways and genomes.

Nucleic Acids Res. 2023-1-6

[10]
The heterogeneous immune landscape between lung adenocarcinoma and squamous carcinoma revealed by single-cell RNA sequencing.

Signal Transduct Target Ther. 2022-8-26

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索