[Predictive Value of A miRNA Signature for Distant Metastasis in Lung Cancer].

• DOI: 10.3779/j.issn.1009-3419.2024.102.43
• Publication Date: 2024-12-20
• Authors: Jing Cong; Anna Wang; Yijun Wang; Xinge Li; Jiangheng Pi; Kaijing Liu; Hongjie Zhang; Xiaoyan Yan; Hongmei Li
• Keywords: Signature (topology); Value (mathematics); Distant metastasis

Lung cancer represents the main cause of cancer-related deaths worldwide, and non-small cell lung (NSCLC) is most subtype. More than half NSCLC patients have already developed distant metastasis (DM) at time diagnosis a poor prognosis. Therefore, it necessary to find new biomarkers for predicting DM in order guide subsequent treatment thus improve prognosis patients. Numerous studies shown that microRNAs (miRNAs) are abnormally expressed tissues play an important role tumorigenesis progression. The aim this study identify differentially miRNAs adenocarcinoma with group compared those non-distant (NDM) group, construct miRNA signature adenocarcinoma. We first obtained clinical data from Cancer Genome Atlas (TCGA) database. Subsequently, bioinformatics analysis, which included different R packages, Kaplan-Meier receiver operating characteristic (ROC) curve, range online analysis tools, was performed analyze data. A total 12 were identified between NDM groups, 8 (miR-377-5p, miR-381-5p, miR-490-5p, miR-519d-5p, miR-3136-5p, miR-320e, miR-2355-5p, miR-6784-5p) screened constructing signature. efficacy good area under curve (AUC) 0.831. Logistic regression showed independent risk factor Next, target genes eight predicted, enrichment these enriched variety pathways, including pathways cancer, herpes simplex virus I infection, PI3K-Akt pathway, MAPK Ras etc. CONCLUSIONS: This has potential be predictor