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乳腺癌微环境中潜在枢纽基因及分子机制的鉴定:一种综合转录组学方法

Identification of potential hub genes and molecular mechanisms in breast cancer microenvironment: A comprehensive transcriptomics approach.

作者信息

Noman Abdullah Al, Saba Abdullah Al, Sayem Mohammad, Yasmin Tahirah, Nabi A H M Nurun

机构信息

Department of Biochemistry and Molecular Biology, Laboratory of Population Genetics, University of Dhaka, Dhaka, Bangladesh.

出版信息

Medicine (Baltimore). 2025 Aug 29;104(35):e44142. doi: 10.1097/MD.0000000000044142.

Abstract

Breast cancer, a major health concern worldwide, involves diverse molecular subtypes and complex gene expression patterns. This study conducted a comprehensive bioinformatics analysis of breast cancer, analyzing 10 gene expression datasets from the Gene Expression Omnibus archive to find common genes that exhibit differential expression (DEGs). Then, we conducted pan-cancer and functional enrichment analyses, including single-cell level investigations of DEGs. To identify potential hub genes, we built protein-protein interaction networks, which were further analyzed for methylation patterns and expression in various cancer stages. The study also explored interactions between these hub genes with microRNAs and transcription factors, along with their correlation with cytokine expression and infiltration of immune cells in the tumor microenvironment. The TCGA BRCA dataset was used for hub gene survival analysis. Key findings include the identification of 36 shared DEGs, with distinct expression patterns in principal component analysis, suggesting their potential as molecular signatures for diagnosis and prognosis. Investigation at the single-cell level revealed upregulated DEGs mainly expressed by tumor-associated fibroblast cells. Gene ontology unveiled upregulated genes mainly involved in the extracellular matrix, but most of the downregulated genes are tumor suppressors. The protein-protein interaction network analysis highlighted 7 hub genes: CAV1, FN1, BGN, CXCL12, SPTBN1, COL11A1, and INHBA. Methylation analysis revealed intricate epigenetic regulation of these genes. MicroRNA and transcription factor interaction analysis underscored the complex regulatory networks influencing gene expression. Cytokine profile analysis in tumor microenvironment and its correlation with hub gene expression provided insights into the immunological landscape of breast cancer. Survival analysis indicated that both upregulated and downregulated hub genes are linked with patient overall survival outcomes, although it is not statistically significant. This study provides a detailed view of the underlying molecular mechanisms in breast cancer, suggesting potential biomarkers and therapeutic targets. Its findings can contribute significantly to understanding the complexity of the breast cancer microenvironment, leading to the development of more sophisticated and targeted treatment strategies.

摘要

乳腺癌是全球主要的健康问题,涉及多种分子亚型和复杂的基因表达模式。本研究对乳腺癌进行了全面的生物信息学分析,分析了来自基因表达综合数据库的10个基因表达数据集,以寻找表现出差异表达的共同基因(差异表达基因)。然后,我们进行了泛癌和功能富集分析,包括在单细胞水平上对差异表达基因的研究。为了识别潜在的枢纽基因,我们构建了蛋白质-蛋白质相互作用网络,并进一步分析了这些基因在不同癌症阶段的甲基化模式和表达情况。该研究还探索了这些枢纽基因与微小RNA和转录因子之间的相互作用,以及它们与肿瘤微环境中细胞因子表达和免疫细胞浸润的相关性。使用癌症基因组图谱(TCGA)的乳腺癌(BRCA)数据集进行枢纽基因生存分析。主要发现包括鉴定出36个共享的差异表达基因,这些基因在主成分分析中具有独特的表达模式,表明它们作为诊断和预后分子标志物的潜力。单细胞水平的研究表明,上调的差异表达基因主要由肿瘤相关成纤维细胞表达。基因本体分析揭示,上调基因主要参与细胞外基质,但大多数下调基因是肿瘤抑制因子。蛋白质-蛋白质相互作用网络分析突出了7个枢纽基因:CAV1、FN1、BGN、CXCL12、SPTBN1、COL11A1和INHBA。甲基化分析揭示了这些基因复杂的表观遗传调控。微小RNA和转录因子相互作用分析强调了影响基因表达的复杂调控网络。肿瘤微环境中的细胞因子谱分析及其与枢纽基因表达的相关性为乳腺癌的免疫格局提供了见解。生存分析表明,上调和下调的枢纽基因均与患者的总生存结果相关,尽管在统计学上不显著。本研究详细阐述了乳腺癌潜在的分子机制,提示了潜在的生物标志物和治疗靶点。其研究结果可为理解乳腺癌微环境的复杂性做出重大贡献,并推动更精准、靶向治疗策略的发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/81d2/12401218/9c0fad94d0e1/medi-104-e44142-g001.jpg

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