Wang Jinsong, Cui Xue, Weng Yiming, Wei Jiayan, Chen Xinyi, Wang Peiwei, Wang Tong, Qin Jian, Peng Min
Department of Oncology, Renmin Hospital of Wuhan University, Wuhan, China.
Central Laboratory, Renmin Hospital, Wuhan University, Wuhan, China.
Front Genet. 2023 Feb 1;14:1092968. doi: 10.3389/fgene.2023.1092968. eCollection 2023.
Lung adenocarcinoma (LUAD) is an essential pathological subtype of non-small cell lung cancer and offers a severe problem for worldwide public health. There is mounting proof that angiogenesis is a crucial player in LUAD progression. Consequently, the purpose of this research was to construct a novel LUAD risk assessment model based on genetic markers related to angiogenesis. We accessed The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases for LUAD mRNA sequencing data and clinical information. Based on machine algorithms and bioinformatics, angiogenic gene-related risk scores (RS) were calculated. Patients in the high-risk category had a worse prognosis ( < 0.001) in the discovery TCGA cohort, and the results were confirmed by these three cohorts (validation TCGA cohort, total TCGA cohort, and GSE68465 cohort). Moreover, risk scores for genes involved in angiogenesis were independent risk factors for lung cancer in all four cohorts. The low-risk group was associated with better immune status and lower tumor mutational load. In addition, the somatic mutation study revealed that the low-risk group had a lower mutation frequency than the high-risk group. According to an analysis of tumor stem cell infiltration, HLA expression, and TIDE scores, the low-risk group had higher TIDE scores and HLA expression levels than the high-risk group, and the amount of tumor stem cell infiltration correlated with the risk score. In addition, high-risk groups may benefit from immune checkpoint inhibitors and targeted therapies. In conclusion, we developed an angiogenesis-related gene risk model to predict the prognosis of LUAD patients, which may aid in the classification of patients with LUAD and select medications for LUAD patients.
肺腺癌(LUAD)是非小细胞肺癌的一种重要病理亚型,给全球公共卫生带来了严重问题。越来越多的证据表明,血管生成在LUAD进展中起着关键作用。因此,本研究的目的是基于与血管生成相关的基因标记构建一种新型的LUAD风险评估模型。我们从癌症基因组图谱(TCGA)和基因表达综合数据库(GEO)中获取了LUAD的mRNA测序数据和临床信息。基于机器学习算法和生物信息学,计算了血管生成基因相关的风险评分(RS)。在发现队列TCGA中,高风险组患者的预后较差(<0.001),并且这一结果在另外三个队列(验证队列TCGA、总队列TCGA和GSE68465队列)中得到了证实。此外,在所有四个队列中,参与血管生成的基因的风险评分都是肺癌的独立危险因素。低风险组与更好的免疫状态和更低的肿瘤突变负荷相关。此外,体细胞突变研究表明,低风险组的突变频率低于高风险组。根据对肿瘤干细胞浸润、HLA表达和TIDE评分的分析,低风险组的TIDE评分和HLA表达水平高于高风险组,并且肿瘤干细胞浸润量与风险评分相关。此外,高风险组可能从免疫检查点抑制剂和靶向治疗中获益。总之,我们开发了一种与血管生成相关的基因风险模型来预测LUAD患者的预后,这可能有助于LUAD患者的分类并为LUAD患者选择药物。