Construction of a prognostic immune-related lncRNA model and identification of the immune microenvironment in middle- or advanced-stage lung squamous carcinoma patients
Qianqian Xue, Yue Wang, Qiang Zheng, Lijun Chen, Yan Jin, Xuxia Shen, Yuan Li
Abstract
Background: Globally, non-small-cell lung cancer (NSCLC) has a high incidence, and NSCLC patients have poor prognoses. Lung squamous carcinoma (LUSC) is a major pathological type of NSCLC. LncRNAs play important roles in tumor progression and immune system functions. The aim of this study was to construct a predictive model with immune-related lncRNAs and to assess the immune microenvironment in middle- or advanced-stage LUSC patients. Methods: RNA sequencing data and corresponding clinical LUSC data were downloaded from The Cancer Genome Atlas. Immune genes were obtained from the Molecular Signatures Database. Immune-related lncRNAs were identified by Pearson correlation analysis in R. The model was constructed using univariate and multivariate Cox regression analyses. Finally, we validated the prognostic immune-related lncRNA model in a cohort from the Fudan University Shanghai Cancer Center. Results: of gemcitabine. Gene set enrichment analysis suggested that these lncRNAs may participate in tumor progression and immune processes. Validation with the clinical cancer cohort demonstrated that higher risk scores were associated with a higher, but not statistically significant, likelihood of recurrence. Conclusion: We established a risk score model including four immune-related lncRNAs. The model accurately predicts the prognosis of middle- or advanced-stage LUSC patients and provides an important reference for individualized treatment.