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免疫浸润相关基因通过浸润骨髓微环境来调节 AML 的进展。

Immune infiltration-related genes regulate the progression of AML by invading the bone marrow microenvironment.

机构信息

Department of Radio-immunity, Heilongjiang Provincial Hospital, Harbin, China.

Department of Laboratory Diagnosis, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.

出版信息

Front Immunol. 2024 Jul 12;15:1409945. doi: 10.3389/fimmu.2024.1409945. eCollection 2024.

DOI:10.3389/fimmu.2024.1409945
PMID:39072320
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11272452/
Abstract

In this study, we try to find the pathogenic role of immune-related genes in the bone marrow microenvironment of AML. Through WGCNA, seven modules were obtained, among which the turquoise module containing 1793 genes was highly correlated with the immune infiltration score. By unsupervised clustering, the turquoise module was divided into two clusters: the intersection of clinically significant genes in the TCGA and DEGs to obtain 178 genes for mutation analysis, followed by obtaining 17 genes with high mutation frequency. Subsequently, these 17 genes were subjected to LASSO regression analysis to construct a riskscore model of 8 hub genes. The TIMER database, ImmuCellAI portal website, and ssGSEA elucidate that the hub genes and risk scores are closely related to immune cell infiltration into the bone marrow microenvironment. In addition, we also validated the relative expression levels of hub genes using the TCGA database and GSE114868, and additional expression levels of hub genes in AML cell lines . Therefore, we constructed an immune infiltration-related gene model that identify 8 hub genes with good risk stratification and predictive prognosis for AML.

摘要

在这项研究中，我们试图在 AML 的骨髓微环境中寻找免疫相关基因的致病作用。通过 WGCNA，获得了七个模块，其中包含 1793 个基因的绿松石模块与免疫浸润评分高度相关。通过无监督聚类，将绿松石模块分为两个聚类：TCGA 和 DEGs 中临床有意义的基因的交集，以获得 178 个用于突变分析的基因，然后获得高突变频率的 17 个基因。随后，对这 17 个基因进行 LASSO 回归分析，构建了 8 个枢纽基因的风险评分模型。TIMER 数据库、ImmuCellAI 门户网站和 ssGSEA 阐明了枢纽基因和风险评分与骨髓微环境中免疫细胞浸润密切相关。此外，我们还使用 TCGA 数据库和 GSE114868 验证了枢纽基因的相对表达水平，以及 AML 细胞系中枢纽基因的额外表达水平。因此，我们构建了一个与免疫浸润相关的基因模型，确定了 8 个具有良好风险分层和预测预后的枢纽基因，用于 AML。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87d4/11272452/1a37ef1443c5/fimmu-15-1409945-g007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87d4/11272452/7382fe9a9b88/fimmu-15-1409945-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87d4/11272452/4d3680643e4e/fimmu-15-1409945-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87d4/11272452/1a37ef1443c5/fimmu-15-1409945-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87d4/11272452/59af23552231/fimmu-15-1409945-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87d4/11272452/22625074f51c/fimmu-15-1409945-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87d4/11272452/849a981eaaa6/fimmu-15-1409945-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87d4/11272452/0ec20dee33be/fimmu-15-1409945-g004.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87d4/11272452/4d3680643e4e/fimmu-15-1409945-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/87d4/11272452/1a37ef1443c5/fimmu-15-1409945-g007.jpg

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