Immunogenomic Gene Signature of Cell-Death Associated Genes with Prognostic Implications in Lung Cancer

Simple Summary The human body consists of trillions of cells and several million of them die daily. These natural processes which determine the fate of a cell in the human body can be broadly defined as programmed cell death (apoptosis and autophagy) and a non-programmed, passive cell death (necrosis). The inherent genetic diversity in humans and differential expression of mRNAs belonging to these cell death pathways can provide clinically actionable information. In this study, we have discovered a differential 21-gene cell death signature that significantly separates lung cancer patients based on their survival. The patients with increased expression of this genomic signature were found to be at higher risk of dying early. Interestingly, this patient group showed significant perturbations in the expression of cytokines and infiltration of immune cells within these tumors. Therefore, the discovery of this novel genomic signature can be used for prognostication of lung cancer patients, and most importantly we can tailor personalized novel immunotherapies for their treatment. Lung cancer is one of the leading causes of death worldwide. Cell death pathways such as autophagy, apoptosis, and necrosis can provide useful clinical and immunological insights that can assist in the design of personalized therapeutics. In this study, variations in the expression of genes involved in cell death pathways and resulting infiltration of immune cells were explored in lung adenocarcinoma (The Cancer Genome Atlas: TCGA, lung adenocarcinoma (LUAD), 510 patients). Firstly, genes involved in autophagy (n = 34 genes), apoptosis (n = 66 genes), and necrosis (n = 32 genes) were analyzed to assess the prognostic significance in lung cancer. The significant genes were used to develop the cell death index (CDI) of 21 genes which clustered patients based on high risk (high CDI) and low risk (low CDI). The survival analysis using the Kaplan-Meier curve differentiated patients based on overall survival (40.4 months vs. 76.2 months), progression-free survival (26.2 months vs. 48.6 months), and disease-free survival (62.2 months vs. 158.2 months) (Log-rank test, p < 0.01). Cox proportional hazard model significantly associated patients in high CDI group with a higher risk of mortality (Hazard Ratio: H.R 1.75, 95% CI: 1.28-2.45, p < 0.001). Differential gene expression analysis using principal component analysis (PCA) identified genes with the highest fold change forming distinct clusters. To analyze the immune parameters in two risk groups, cytokines expression (n = 265 genes) analysis revealed the highest association of IL-15RA and IL 15 (> 1.5-fold, p < 0.01) with the high-risk group. The microenvironment cell-population (MCP)-counter algorithm identified the higher infiltration of CD8+ T cells, macrophages, and lower infiltration of neutrophils with the high-risk group. Interestingly, this group also showed a higher expression of immune checkpoint molecules CD-274 (PD-L1), CTLA-4, and T cell exhaustion genes (HAVCR2, TIGIT, LAG3, PDCD1, CXCL13, and LYN) (p < 0.01). Furthermore, functional enrichment analysis identified significant perturbations in immune pathways in the higher risk group. This study highlights the presence of an immunocompromised microenvironment indicated by the higher infiltration of cytotoxic T cells along with the presence of checkpoint molecules and T cell exhaustion genes. These patients at higher risk might be more suitable to benefit from PD-L1 blockade or other checkpoint blockade immunotherapies.

Automated summary

This study identified a novel 21-gene cell death signature in lung cancer patients, which significantly correlates with patient survival. Patients with higher expression of this genomic signature were found to have increased risk of early mortality. Additionally, the study revealed perturbations in cytokine expression, immune cell infiltration, and immune checkpoint molecule expression in high-risk patients, suggesting a potential for personalized immunotherapies targeting these pathways.