Prognostic Signature of Response to PD-1 Immune Checkpoint Blockade in Lung Cancer

Abstract

Background: Currently, immunotherapy has shown significant clinical benefits in many cancers but is only beneficial in a subset of patients. With the purpose of ameliorating the diagnosis and treatment of lung cancer, we aimed to establish a prognostic signature of response to programmed cell death protein 1 (PD-1) immune checkpoint blockade (ICB) in lung cancer. Methods: Differentially expressed genes (DEGs) were identified and functional analysis performed. A prognostic signature was constructed and used to build a combined nomogram. In addition, the patients were categorized into high- and low-risk groups and the correlation with tumor immune microenvironment, drug sensitivity, and tumor mutation was analyzed. Results: A total of 449 DEGs were analyzed and found to be involved in cell adhesion, cytokine-cytokine receptor interaction, and antigen processing and presentation pathways. A 12-gene prognostic risk model was constructed, consisting of MTUS1, ID1, KYNU, HOXC5, COL4A2, BARX2, EPHA4, PADI4, CLEC7A, SPP1, PLIN2, and GFI1. A higher percentage of naïve B cells, memory B cells, and CD8 T cells were found in the low-risk group, while resting natural killer cells and neutrophils were found at a lower percentage (p < 0.05). The estimation of stromal and immune cells in malignant tumor tissues using expression data (ESTIMATE) and immune scores were found to be higher in the low-risk group than those in the high-risk group (p < 0.05). The half maximal inhibitory concentration (IC50) values of the six drugs, cisplatin, cyclopamine, docetaxel, doxorubicin, gemcitabine, and vinblastine, were found to be significantly higher in the low-risk group than in the high-risk group (p < 0.05). The tumor mutation burden was greater in the high-risk group compared to that in the low-risk group (p < 0.05). Conclusions: This immunotherapy-related 12-gene prognostic prediction signature could allow clinicians to predict the survival benefit of PD-1 ICB in patients with lung cancer, and these 12 genes could be used as potential markers for improving the response rate of PD-1 ICB in patients with lung cancer.