Introduction: Recent studies have reported that ferroptosis is an iron-dependent cell death process and is a potential therapeutic target in various tumours. The purpose of this study was to establish a new algorithm based on the ferroptosis score to ascertain the prognosis and response to immunotherapy of patients with lung squamous cell carcinoma (LUSC).
Methods: The RNA-seq data of patients with LUSC were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases and merged after removing the inter batch differences. Based on the expression of the ferroptosis-related genes, unsupervised consistent cluster analysis was performed to obtain various ferroptosis-related subgroups. These subgroups were analysed to obtain differentially expressed genes (DEGs). Subsequently, multiple gene clusters were obtained by unsupervised consistent cluster analysis based on the expression of the DEGs. The Boruta algorithm was used to calculate the ferroptosis score.
Results: There were significant differences in prognosis amongst the various ferroptosis-related and gene clusters. In addition, the gene set variation analysis revealed that the different ferroptosis-related clusters and gene clusters demonstrated differences in biological pathways. The ferroptosis scores positively correlated with the tumour mutation burden, and patients with lower scores had a better prognosis. In addition, the ferroptosis score was accurate in predicting the effectiveness of immunotherapy.
Conclusion: There were significant differences in the prognosis and immunotherapy response of patients with LUSC with different ferroptosis scores. Therefore, a comprehensive clinical evaluation of the ferroptosis score of each patient with LUSC is clinically significant.
Keywords: Ferroptosis; Immunotherapy; Lung squamous cell carcinoma; Prognosis.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.