综合单细胞和多组学分析揭示胃癌中铁中毒相关基因表达和免疫微环境异质性。

IF 2.8 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM
Shupeng Zhang, Zhaojin Li, Gang Hu, Hekai Chen
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引用次数: 0

摘要

胃癌(GC)是一种世界范围内普遍存在的恶性肿瘤,在其发展过程中包含了多种生物学过程。近年来,铁下垂作为一种新的细胞死亡模式,已成为癌症研究的热点。胃癌的微环境是由不同的细胞群组成的,但具体的基因表达谱及其与铁下垂的关系尚不清楚。我们的研究采用单细胞RNA测序技术,深入研究胃癌的转录组学特征,鉴定胃癌的差异基因表达,为胃癌的细胞多样性和潜在的分子机制提供新的见解。我们在GC中发现了一组显著差异表达的基因,这可能为未来的功能研究提供有价值的线索。随后的分析,包括基因集交叉和功能富集,确定了与铁死亡有关的基因,并进行了全面的基因本体(GO)和京都基因与基因组百科全书(KEGG)分析,以阐明它们的生物学作用。在基因选择和模型验证部分,使用机器学习算法识别关键基因,构建具有较高预测精度的模型。此外,利用ssGSEA分析进一步鉴定了RBL中扭曲的免疫景观,从而更清楚地了解基因表达特征及其相互作用网络的复杂关联以及各种免疫细胞的浸润。与不同免疫细胞亚型的相关性分析表明,CTSB是肿瘤浸润细胞分布的重要调节因子。利用单细胞RNA测序分析绘制胃癌微环境中细胞组成及基因表达谱,为阐明胃癌细胞异质性及肿瘤微环境调控提供重要信息。此外,FTH1、ZFP36和CIRBP在不同表达水平上的分布,为这些启动子在肿瘤微环境中的功能信息研究提供了新的前景。总之,本研究增加了我们对胃肿瘤发生的分子机制的认识,为寻找新的靶点和治疗诊断的生物标志物提供了科学依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Integrative single-cell and multi-omics analyses reveal ferroptosis-associated gene expression and immune microenvironment heterogeneity in gastric cancer.

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.

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来源期刊
Discover. Oncology
Discover. Oncology Medicine-Endocrinology, Diabetes and Metabolism
CiteScore
2.40
自引率
9.10%
发文量
122
审稿时长
5 weeks
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