A Novel Prognostic and Predictive Signature for Lung Adenocarcinoma Derived from Combined Hypoxia and Infiltrating Immune Cell-Related Genes in TCGA Patients

Abstract

Background The hypoxia and immune status of the lung adenocarcinoma (LUAD) microenvironment appear to have combined impacts on prognosis. Therefore, deriving a prognostic signature by integrating hypoxia- and immune infiltrating cell-related genes (H&IICRGs) may add value over prognostic indices derived from genes driving either process alone. Methods Differentially expressed H&IICRGs (DE-H&IICRGs) were identified in The Cancer Genome Atlas transcriptomic data using limma , CIBERSORT, weighted gene co-expression network analysis, and intersection analysis. A stepwise Cox regression model was constructed to identify prognostic genes and to produce a gene signature based on DE-H&IICRGs. The potential biological functions associated with the gene signature were explored using functional enrichment analysis. The prognostic signature was externally validated in a separate cohort from the Gene Expression Omnibus database. Results Five prognostic genes associated with overall survival in LUAD were used in the DE-H&IICRG-based prognostic signature. Patients in the high-risk group had an inferior prognosis, which was validated in an independent external cohort, and had lower expression of most immune checkpoint genes. In multivariate analysis, only risk score and T stage were independent prognostic factors. Differentially expressed genes (DEGs) associated with the risk score were enriched for pathways related to cell cycle, hypoxia regulation, and immune response. TIDE analyses showed that low-risk LUAD patients might also respond better to immunotherapy. Conclusion This study establishes and validates a prognostic profile for LUAD patients that combines hypoxia and immune infiltrating cell-related genes. This signature may have clinical application both for prognostication and guiding individualized immunotherapy.

Construction and validation of a hypoxia-related risk signature identified EXO1 as a prognostic biomarker based on 12 genes in lung adenocarcinoma

“…The risk model promoted individualized treatment and provided potential novel targets for immunotherapy of LUAD patients [25]. Similarly, we also built the predictor based on 12 HRGs and the model performed well with much more higher AUC of ROC than other studies [26,27].…”

Construction of an immune-related gene prognostic model with experimental validation and analysis of immune cell infiltration in lung adenocarcinoma

“…Therefore, the elucidation of immune-related genes with biological significance and assessment of their prognostic value could aid the diagnosis and treatment of patients with LUAD. Previous studies have demonstrated that abnormally expressed genes can be utilized as prognostic LUAD markers (26)(27)(28). However, only a few previous studies have reported the abnormally expressed immune genes and their immune infiltration role (29)(30)(31).…”

Identification of hypoxia‐related gene signatures based on multi‐omics analysis in lung adenocarcinoma

“…Although the role of hypoxia‐related genes in prognosis prediction of LUAD has received extensive attention in recent years, 48–51 the role of hypoxia in LUAD was not fully elucidated. Several studies have combined hypoxia and immunization to predict the prognosis of patients with LUAD, and the constructed models also have good predictive performances 51,52 . Therefore, it is still necessary to construct more accurate prediction models of LUAD from multi‐omics levels.…”

“… 41 Until now, several hypoxia‐related gene features have been built to predict survival rate of certain tumour types, such as ovarian cancer, 42 renal clear cell carcinoma, 43 hepatocellular carcinoma, 44 breast cancer, 45 melanoma 46 and prostate cancer. 47 Although the role of hypoxia‐related genes in prognosis prediction of LUAD has received extensive attention in recent years, 48 , 49 , 50 , 51 the role of hypoxia in LUAD was not fully elucidated. Several studies have combined hypoxia and immunization to predict the prognosis of patients with LUAD, and the constructed models also have good predictive performances.…”

“…Several studies have combined hypoxia and immunization to predict the prognosis of patients with LUAD, and the constructed models also have good predictive performances. 51 , 52 Therefore, it is still necessary to construct more accurate prediction models of LUAD from multi‐omics levels. Considering that tumour hypoxia is a complex biological process which involves complicated regulation networks and multiple signal pathways among beaucoup genes.…”