Zhu Shumin, Li Yanming, Mao Yafei, Li Xinyuan, Gao Shichao, Geng Yulan, Ma Jin
Department of Medical Laboratory, The First Hospital of Hebei Medical University, Shijiazhuang, China.
Department of Medical Laboratory, The Third Hospital of Hebei Medical University, Shijiazhuang, China.
J Thorac Dis. 2023 Mar 31;15(3):1267-1278. doi: 10.21037/jtd-23-80. Epub 2023 Mar 29.
Lung cancer (LC) is the most common cancer. Using data from The Cancer Genome Atlas (TCGA), we analyzed the functional roles of M1 macrophage status in LC patients.
Clinical and transcriptome data of LC patients were obtained from the TCGA dataset. We identified M1 macrophage-related genes in LC patients and investigated the underlying molecular mechanisms of these genes in LC patients. After performing a least absolute shrinkage and selection operator (LASSO) Cox regression analysis, the LC patients were divided into two subtypes, and the underlying mechanism of the association between them was further explored. A comparison of immune infiltration was conducted between the two subtypes. Based on gene set enrichment analysis (GSEA), the key regulators associated with subtypes were further explored.
M1 macrophage-related genes were identified using TCGA data, and these genes might be related to the activation of the immune response and cytokine-mediated signaling pathways in LC. A seven M1 macrophage-related gene signature (including , , , , , and ) was identified in LC using LASSO Cox regression analysis. Two subtypes (low risk and high risk) of LC patients were created based on the seven M1 macrophage-related gene signature. Univariate and multivariate survival analyses further confirmed that the subtype classification was an effective independent prognostic factor. Moreover, the two subtypes were correlated with immune infiltration, and GSEA revealed that the pathways of tumor cell proliferation and immune-related biological processes (BPs) might play an important role in LC in the high-risk group and low-risk group, respectively.
M1 macrophage-related subtypes of LC were identified and were closely associated with immune infiltration. The gene signature involved in M1 macrophage-related genes could help make a distinction and predict prognosis for LC patients.
肺癌(LC)是最常见的癌症。利用癌症基因组图谱(TCGA)的数据,我们分析了M1巨噬细胞状态在肺癌患者中的功能作用。
从TCGA数据集中获取肺癌患者的临床和转录组数据。我们在肺癌患者中鉴定出M1巨噬细胞相关基因,并研究了这些基因在肺癌患者中的潜在分子机制。进行最小绝对收缩和选择算子(LASSO)Cox回归分析后,将肺癌患者分为两个亚型,并进一步探讨它们之间关联的潜在机制。对两个亚型之间的免疫浸润进行了比较。基于基因集富集分析(GSEA),进一步探索了与亚型相关的关键调节因子。
利用TCGA数据鉴定出M1巨噬细胞相关基因,这些基因可能与肺癌中免疫反应的激活和细胞因子介导的信号通路有关。通过LASSO Cox回归分析在肺癌中鉴定出一个由七个M1巨噬细胞相关基因组成的特征(包括 、 、 、 、 、 和 )。基于这七个M1巨噬细胞相关基因特征创建了肺癌患者的两个亚型(低风险和高风险)。单因素和多因素生存分析进一步证实,亚型分类是一个有效的独立预后因素。此外,这两个亚型与免疫浸润相关,GSEA显示肿瘤细胞增殖途径和免疫相关生物学过程(BPs)可能分别在高风险组和低风险组的肺癌中起重要作用。
鉴定出了肺癌的M1巨噬细胞相关亚型,且其与免疫浸润密切相关。涉及M1巨噬细胞相关基因的基因特征有助于对肺癌患者进行区分和预后预测。