Gu Changcong, Guo Shuai, Li Haoxiang
Department of Radiology, The First Hospital of Qinhuangdao, Qinhuangdao, Hebei, China.
Department of Ultrasound, The First Hospital of Qinhuangdao, Qinhuangdao, Hebei, China.
Discov Oncol. 2025 Jun 4;16(1):999. doi: 10.1007/s12672-025-02822-7.
The hypoxic microenvironment affects the development of many types of tumors. It also triggers a series of immune response, and affects the level of immune cells infiltration. Here, the study aims to develop a gene marker based on hypoxia for prognosis evaluation in lung adenocarcinoma (LUAD), and investigate the relationship between hypoxia and immune cell infiltration in the tumor microenvironment (TME).
Retrieving LUAD cases from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Through bioinformatics analysis, we screened out the hypoxia genes correlated with the prognosis of LUAD. A hypoxia risk score model was established by using gene expression level and expression coefficient. Using the median risk score value, we divided the patients in the two databases into high-risk and low-risk groups. The hypoxic model was then validated using survival analysis and receiver operating characteristic (ROC) curves. The CIBERSORT calculation method was employed to analyze the infiltration of immune cells. Finally, we analyzed the correlation between immune genes and hypoxia.
Patients in the high-risk group, characterized by higher hypoxia risk scores, exhibited significantly poorer prognosis compared to those in the low-risk group. In addition, we found significant differences in the infiltration rates of these five types of immune cells (M0 macrophages, M1 macrophages, resting mast cells, activated mast cells, monocytes, resting NK cells and activated CD4 memory T cells) in both groups of tissues. After screening, the expression levels of the four immune genes (CCR7, CXCL10, CXCL11, and CCL19) were significantly associated with hypoxia risk in both groups.
We discovered that the hypoxia risk score was related to prognosis and immune cell infiltration rate of LUAD. This finding may provide new ideas for LUAD immunotherapy.
缺氧微环境影响多种肿瘤的发展。它还引发一系列免疫反应，并影响免疫细胞浸润水平。在此，本研究旨在开发一种基于缺氧的基因标志物，用于肺腺癌（LUAD）的预后评估，并研究缺氧与肿瘤微环境（TME）中免疫细胞浸润之间的关系。
从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）中检索LUAD病例。通过生物信息学分析，我们筛选出与LUAD预后相关的缺氧基因。利用基因表达水平和表达系数建立缺氧风险评分模型。使用中位风险评分值，将两个数据库中的患者分为高风险组和低风险组。然后使用生存分析和受试者工作特征（ROC）曲线对缺氧模型进行验证。采用CIBERSORT计算方法分析免疫细胞的浸润情况。最后，我们分析了免疫基因与缺氧之间的相关性。
高风险组患者的缺氧风险评分较高，与低风险组患者相比，其预后明显较差。此外，我们发现两组组织中这五种免疫细胞（M0巨噬细胞、M1巨噬细胞、静息肥大细胞、活化肥大细胞、单核细胞、静息自然杀伤细胞和活化CD4记忆T细胞）的浸润率存在显著差异。筛选后，四个免疫基因（CCR7、CXCL10、CXCL11和CCL19）的表达水平在两组中均与缺氧风险显著相关。
我们发现缺氧风险评分与LUAD的预后和免疫细胞浸润率有关。这一发现可能为LUAD免疫治疗提供新的思路。
