Suppr超能文献

铁死亡相关基因SLC1A5是一种新型的预后生物标志物,与胃腺癌中的免疫浸润相关。

Ferroptosis-related gene SLC1A5 is a novel prognostic biomarker and correlates with immune infiltrates in stomach adenocarcinoma.

作者信息

Zhu Dandan, Wu Sifan, Li Yafang, Zhang Yu, Chen Jierong, Ma Jianhong, Cao Lixue, Lyu Zejian, Hou Tieying

机构信息

School of Medicine, South China University of Technology, Guangzhou, 510006, Guangdong, China.

Guangdong Clinical Laboratory Center, Guangdong Provincial People's Hospital; Guangdong Academy of Medical Sciences, Guangzhou, 510080, Guangdong, China.

出版信息

Cancer Cell Int. 2022 Mar 19;22(1):124. doi: 10.1186/s12935-022-02544-8.

Abstract

BACKGROUND

Stomach adenocarcinoma (STAD) is associated with high morbidity and mortality rates. Ferroptosis is an iron-dependent form of cell death, which plays an important role in the development of many cancers. Tumor-associated competing endogenous RNAs (ceRNAs) regulate tumorigenesis and development. Our study aimed to construct ceRNA networks and explore the relationship between ferroptosis-related genes in the ceRNA network and immune infiltration in STAD.

METHODS

Based on the interactions among long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs), a ceRNA network was constructed to illustrate the relationships among lncRNAs, miRNAs, and mRNAs. Subsequently, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) functional enrichment analyses were carried out to explore the functions and interactions of the differentially expressed (DE) mRNAs related to the ceRNA network. Differential expression and prognostic analysis of ferroptosis-related genes in the ceRNA network were performed using the R package "limma" and "survminer." The correlation between ferroptosis-related genes and tumor-infiltrating immune cells was analyzed using Spearman correlation analysis and CIBERSORT. Quantitative real-time PCR (qRT-PCR) was used to validate the expression of ferroptosis-related genes in STAD cells lines.

RESULTS

A ceRNA network consisting of 29 DElncRNAs, 31 DEmiRNAs, and 182 DEmRNAs was constructed. These DEmRNAs were significantly enriched in pathways related to the occurrence and development of STAD. The ferroptosis-related gene SLC1A5 was upregulated in STAD (P < 0.001) and was associated with better prognosis (P = 0.049). The CIBERSORT database and Spearman correlation analysis indicated that SLC1A5 was correlated with eight types of tumor-infiltrating immune cells and immune checkpoints, including PD-L1(CD-274) and PD-1(PDCD1). The SLC1A5 mRNA was found to be highly expressed in STAD cells lines.

CONCLUSIONS

Our study provides insights into the function of ceRNAs in STAD and identifies biomarkers for the development of therapies for STAD. The ferroptosis-related gene SLC1A5 in the ceRNA network was associated with both tumor-infiltrating immune cells and immune checkpoints in the tumor microenvironment, suggesting that SLC1A5 may be a novel prognostic marker and a potential target for STAD immunotherapy in the future.

摘要

背景

胃腺癌(STAD)的发病率和死亡率较高。铁死亡是一种铁依赖性细胞死亡形式,在许多癌症的发展中起重要作用。肿瘤相关的竞争性内源性RNA(ceRNA)调节肿瘤的发生和发展。我们的研究旨在构建ceRNA网络,并探讨ceRNA网络中与铁死亡相关基因和STAD中免疫浸润之间的关系。

方法

基于长链非编码RNA(lncRNA)、微小RNA(miRNA)和信使RNA(mRNA)之间的相互作用,构建ceRNA网络以阐明lncRNA、miRNA和mRNA之间的关系。随后,进行基因本体(GO)和京都基因与基因组百科全书(KEGG)功能富集分析,以探索与ceRNA网络相关的差异表达(DE)mRNA的功能和相互作用。使用R包“limma”和“survminer”对ceRNA网络中与铁死亡相关基因进行差异表达和预后分析。使用Spearman相关性分析和CIBERSORT分析铁死亡相关基因与肿瘤浸润免疫细胞之间的相关性。采用定量实时PCR(qRT-PCR)验证铁死亡相关基因在STAD细胞系中的表达。

结果

构建了一个由29个差异表达lncRNA、31个差异表达miRNA和182个差异表达mRNA组成的ceRNA网络。这些差异表达mRNA在与STAD发生和发展相关的通路中显著富集。铁死亡相关基因SLC1A5在STAD中上调(P < 0.001),且与较好的预后相关(P = 0.049)。CIBERSORT数据库和Spearman相关性分析表明,SLC1A5与八种肿瘤浸润免疫细胞和免疫检查点相关,包括程序性死亡配体1(PD-L1,CD-274)和程序性死亡受体1(PD-1,PDCD1)。发现SLC1A5 mRNA在STAD细胞系中高表达。

结论

我们的研究为ceRNA在STAD中的功能提供了见解,并确定了STAD治疗开发的生物标志物。ceRNA网络中与铁死亡相关的基因SLC1A5与肿瘤微环境中的肿瘤浸润免疫细胞和免疫检查点均相关,表明SLC1A5可能是一种新的预后标志物,也是未来STAD免疫治疗的潜在靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5271/8933927/c11ff00f5515/12935_2022_2544_Fig1_HTML.jpg

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

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验