Predictive Value of miRNAs Markers for Advanced Lung Squamous Cell Carcinoma.
10.3779/j.issn.1009-3419.2025.102.16
- Author:
Anna WANG
1
;
Jingjing CONG
1
;
Yingjia WANG
2
;
Xin'ge LI
3
;
Junjian PI
4
;
Kaijing LIU
1
;
Hongjie ZHANG
1
;
Xiaoyan YAN
1
;
Hongmei LI
1
Author Information
1. Department of Oncology, The Affiliated Hospital of Qingdao University, Qingdao 266000, China.
2. College of Basic Medical Sciences, Shandong First Medical University, Jinan 250117, China.
3. College of Medicine, Hainan Vocational University of Science
and Technology, Haikou 570000, China.
4. Qingdao Medical College, Qingdao University, Qingdao 266071, China.
- Publication Type:Journal Article
- Keywords:
Advanced lung squamous cell carcinoma;
Biomarkers;
Enrichment analysis;
Lung neoplasms;
miRNAs
- MeSH:
Humans;
MicroRNAs/metabolism*;
Lung Neoplasms/metabolism*;
Biomarkers, Tumor/metabolism*;
Carcinoma, Squamous Cell/pathology*;
Gene Expression Regulation, Neoplastic;
Male;
Female;
Prognosis;
ROC Curve;
Middle Aged
- From:
Chinese Journal of Lung Cancer
2025;28(5):325-333
- CountryChina
- Language:Chinese
-
Abstract:
BACKGROUND: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.
METHODS: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.
RESULTS: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.
CONCLUSIONS: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.
