Wang Anna, Cong Jingjing, Wang Yingjia, Li Xin'ge, Pi Junjian, Liu Kaijing, Zhang Hongjie, Yan Xiaoyan, Li Hongmei
Department of Oncology, The Affiliated Hospital of Qingdao University, Qingdao 266000, China.
College of Basic Medical Sciences, Shandong First Medical University, Jinan 250117, China.
Zhongguo Fei Ai Za Zhi. 2025 May 20;28(5):325-333. doi: 10.3779/j.issn.1009-3419.2025.102.16.
Lung cancer is one of the leading causes of cancer-related mortality worldwide, with above 80% of cases be non-small cell lung cancer (NSCLC), among which lung squamous cell carcinoma (LUSC) occupies a significant proportion. Although comprehensive cancer therapies have considerably improved the overall survival of patients, patients with advanced LUSC have a poorer prognosis. Therefore, there is a need for a biomarker to predict the progress of advanced LUSC in order to improve prognosis through early diagnosis. Previous studies have shown that miRNAs are differentially expressed in lung cancer tissues and play roles as potential oncogenes or tumor suppressors. The aim of this study is to identify differentially expressed miRNAs between early-stage and advanced-stage LUSC, and to establish a set of miRNAs that can predict the progress of advanced LUSC.
Clinical data and miRNA-related data of LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Bioinformatic methods were applied to analyze the data. Receiver operating characteristic (ROC) curves were plotted, and various online tools were used to predict target genes, with subsequent analysis of the potential biological mechanisms of these genes.
A total of 58 differentially expressed miRNAs were identified between the experiment group and the control group. Seven miRNAs were selected for potential construction of a miRNA biomarker through LASSO regression, and based on the area under the curve (AUC) values of each miRNA, four of these miRNAs (miR-377-3p, miR-4779, miR-6803-5p, miR-3960) were ultimately chosen as biomarkers for predicting advanced LUSC. The AUC under the ROC curve for the combined four miRNAs was 0.865. Enrichment analysis showed that these target genes were involved in several pathways, including cancer-related pathways, mitogen-activated protein kinase (MAPK) signaling pathway, serine/threonine kinase, and tyrosine kinase signaling pathways.
The combined use of miR-377-3p, miR-4779, miR-6803-5p and miR-3960 provides a good predictive ability for the progress of advanced LUSC patients, with an AUC of 0.865.
肺癌是全球癌症相关死亡的主要原因之一，超过80%的病例为非小细胞肺癌（NSCLC），其中肺鳞状细胞癌（LUSC）占相当大的比例。尽管综合癌症治疗显著提高了患者的总生存率，但晚期LUSC患者的预后较差。因此，需要一种生物标志物来预测晚期LUSC的进展，以便通过早期诊断改善预后。先前的研究表明，miRNA在肺癌组织中差异表达，并作为潜在的癌基因或肿瘤抑制因子发挥作用。本研究的目的是鉴定早期和晚期LUSC之间差异表达的miRNA，并建立一组能够预测晚期LUSC进展的miRNA。
从癌症基因组图谱（TCGA）数据库下载LUSC患者的临床数据和miRNA相关数据。应用生物信息学方法分析数据。绘制受试者工作特征（ROC）曲线，并使用各种在线工具预测靶基因，随后分析这些基因的潜在生物学机制。
实验组和对照组之间共鉴定出58个差异表达的miRNA。通过LASSO回归选择了7个miRNA用于潜在构建miRNA生物标志物，并根据每个miRNA的曲线下面积（AUC）值，最终选择其中4个miRNA（miR-377-3p、miR-4779、miR-6803-5p、miR-3960）作为预测晚期LUSC的生物标志物。联合这4个miRNA的ROC曲线下AUC为0.865。富集分析表明，这些靶基因参与了多个途径，包括癌症相关途径、丝裂原活化蛋白激酶（MAPK）信号通路、丝氨酸/苏氨酸激酶和酪氨酸激酶信号通路。
联合使用miR-377-3p、miR-4779、miR-6803-5p和miR-3960对晚期LUSC患者的进展具有良好的预测能力，AUC为0.865。
