Identification of Prognostic miRNAs Associated With Immune Cell Tumor Infiltration Predictive of Clinical Outcomes in Patients With Non-Small Cell Lung Cancer - Zhang, Yuepeng; Mi, Kai; Li, Zhiheng; Qiang, Lixia; Lv, Meiyu; Wu, Yushan; Yuan, Ligong; Jin, Shoude (Frontiers in Oncology, 2021)
Background: A detailed means of prognostic stratification in patients with non-small cell lung cancer (NSCLC) is urgently needed to support individualized treatment plans. Recently, microRNAs (miRNAs) have been used as biomarkers due to their previously reported prognostic roles in cancer. This study aimed to construct an immune-related miRNA signature that effectively predicts NSCLC patient prognosis. Methods: The miRNAs and mRNA expression and mutation data of NSCLC was obtained from The Cancer Genome Atlas (TCGA). Immune associated miRNAs were identified using immune scores calculated by the ESTIMATE algorithm. Lasso-penalized multivariate survival models were using for development of a tumor immune-related miRNA signature (TIM-Sig), which was evaluated in several public cohorts from the Gene Expression Omnibus (GEO) and the CellMiner database. The miRTarBase is used for constructing the miRNA-target interactions. Results: TIM-Sig including 10 immune-related miRNAs was constructed and successfully predicted overall survival (OS) in the validation cohorts. TIM-Sig score negatively correlated with CD8+ T cell infiltration, IFN-γ expression, CYT activity and tumor mutation burden. The correlation between TIM-Sig score and genomic mutation and cancer chemotherapeutics was also evaluated. A miRNA-target network of 10 miRNAs in TIM-Sig was constructed. Further analysis revealed that these target genes showed the prognostic value in both lung squamous cell carcinoma and adenocarcinomas. Conclusions: We concluded that the immune-related miRNAs demonstrated a potential value in clinical prognostication.