Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
Pathol Res Pract. 2021 Dec;228:153654. doi: 10.1016/j.prp.2021.153654. Epub 2021 Oct 13.
Lung cancer, a malignant tumor, has the highest mortality and second most common morbidity worldwide. Non-small cell lung cancer (NSCLC) is the most common pathological subtype of lung cancer. This study aimed to identify the gene signature associated with the NSCLC prognosis using bioinformatics analysis.
The dataset GSE103512 was utilized to construct co-expression networks using weighted gene co-expression network analysis (WGCNA). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed using Database for Annotation, Visualization, and Integrated Discovery. Gene set enrichment analysis was conducted to ascertain the function of the hub genes more accurately. The relationship between the hub genes and immune infiltration was investigated using a single sample gene set enrichment analysis. Hub genes were screened and validated by other datasets and online websites.
The results of WGCNA demonstrated that the blue module was most significantly related to tumor progression in NSCLC. Functional enrichment analysis showed that the blue module was associated with DNA replication, cell division, mitotic nuclear division, and cell cycle. A total of five hub genes (RFC5, UBE2S, CHAF1A, FANCI, and TMEM194A) were chosen to be identified and validated at transcriptional and translational levels. Receiver operating characteristic curve verified that the mRNA levels of these five genes can excellently discriminate between normal and tumor tissues. Survival analysis was also performed. Additionally, the protein levels of these five genes were also significantly different between tumor and normal tissues. Immune infiltration analysis showed that the expression levels of the hub genes had a negative correlation with the infiltration levels of many cells related to innate immune response, antigen-presenting process, humoral immune response, or T cell-mediated immune responses.
We identified five hub genes associated with the NSCLC tumorigenesis. NSCLC patients with higher expressions of each hub gene had a worse prognosis than those with lower expressions. Moreover, the hub genes might serve as biomarkers and therapeutic targets for precise diagnosis, target therapy, and immunotherapy of NSCLC in the future.
肺癌是一种恶性肿瘤,其死亡率居全球首位,发病率居全球第二位。非小细胞肺癌(NSCLC)是肺癌最常见的病理亚型。本研究旨在通过生物信息学分析鉴定与 NSCLC 预后相关的基因特征。
利用加权基因共表达网络分析(WGCNA)构建共表达网络,使用数据集 GSE103512。使用数据库进行基因本体论和京都基因与基因组百科全书富集分析,用于注释、可视化和综合发现。基因集富集分析用于更准确地确定枢纽基因的功能。使用单个样本基因集富集分析研究枢纽基因与免疫浸润的关系。通过其他数据集和在线网站筛选和验证枢纽基因。
WGCNA 的结果表明,蓝色模块与 NSCLC 肿瘤进展最显著相关。功能富集分析表明,蓝色模块与 DNA 复制、细胞分裂、有丝分裂核分裂和细胞周期有关。共选择了 5 个枢纽基因(RFC5、UBE2S、CHAF1A、FANCI 和 TMEM194A)在转录和翻译水平上进行鉴定和验证。接收者操作特征曲线验证了这 5 个基因的 mRNA 水平可以极好地区分正常组织和肿瘤组织。生存分析也进行了。此外,这 5 个基因的蛋白水平在肿瘤组织和正常组织之间也有显著差异。免疫浸润分析表明,枢纽基因的表达水平与与先天免疫反应、抗原呈递过程、体液免疫反应或 T 细胞介导的免疫反应相关的许多细胞的浸润水平呈负相关。
我们鉴定了与 NSCLC 肿瘤发生相关的 5 个枢纽基因。每个枢纽基因表达水平较高的 NSCLC 患者的预后比表达水平较低的患者差。此外,这些枢纽基因可能作为未来 NSCLC 精确诊断、靶向治疗和免疫治疗的生物标志物和治疗靶点。