Identification of Prognostic miRNAs Associated With Immune Cell Tumor Infiltration Predictive of Clinical Outcomes in Patients With Non-Small Cell Lung Cancer.

Yuepeng Zhang,Meiyu Lv,Shoude Jin,Ligong Yuan,Kai Mi,Lixia Qiang,Yushan Wu,Zhiheng Li

doi:10.3389/fonc.2021.705869

Abstract

BackgroundA 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.MethodsThe 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 was used for constructing the miRNA-target interactions.ResultsThe 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 prognostic value in both lung squamous cell carcinoma and adenocarcinoma.ConclusionsWe concluded that the immune-related miRNAs demonstrated a potential value in clinical prognosis.

Highlights

The most malignant and most commonly encountered lung cancer subtype is non-small cell lung cancer (NSCLC) [1]
least absolute shrinkage and selection operator (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
We concluded that the immune-related miRNAs demonstrated a potential value in clinical prognosis

Summary

Introduction

The most malignant and most commonly encountered lung cancer subtype is non-small cell lung cancer (NSCLC) [1]. The NSCLC subtype can further be classified as either lung adenocarcinoma (LUAD) or lung squamous cell carcinoma (LUSC). Forty percent of all lung cancers are of the LUAD subtype, with LUSC reported as the second leading cause of lung malignancy-related death, resulting in an average of 400,000 deaths worldwide annually [2]. More effective prognostic biomarkers for risk stratification in NSCLC are required. A detailed means of prognostic stratification in patients with non-small cell lung cancer (NSCLC) is urgently needed to support individualized treatment plans. 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

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Conclusion