Abstract
Immune-related genes (IRGs) play considerable roles in tumor immune microenvironment (IME). This research aimed to discover the differentially expressed immune-related genes (DEIRGs) based on the Cox predictive model to predict survival for lung squamous cell carcinoma (LUSC) through bioinformatics analysis. First of all, the differentially expressed genes (DEGs) were acquired based on The Cancer Genome Atlas (TCGA) using the limma R package, the DEIRGs were obtained from the ImmPort database, whereas the differentially expressed transcription factors (DETFs) were acquired from the Cistrome database. Thereafter, a TFs-mediated IRGs network was constructed to identify the candidate mechanisms for those DEIRGs in LUSC at molecular level. Moreover, Gene Ontology (GO), together with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, was conducted for exploring those functional enrichments for DEIRGs. Besides, univariate as well as multivariate Cox regression analysis was conducted for establishing a prediction model for DEIRGs biomarkers. In addition, the relationship between the prognostic model and immunocytes was further explored through immunocyte correlation analysis. In total, 3,599 DEGs, 223 DEIRGs, and 46 DETFs were obtained from LUSC tissues and adjacent non-carcinoma tissues. According to multivariate Cox regression analysis, 10 DEIRGs (including CALCB, GCGR, HTR3A, AMH, VGF, SEMA3B, NRTN, ENG, ACVRL1, and NR4A1) were retrieved to establish a prognostic model for LUSC. Immunocyte infiltration analysis showed that dendritic cells and neutrophils were positively correlated with IRGs, which possibly exerted an important part within the IME of LUSC. Our study identifies a prognostic model based on IRGs, which is then used to predict LUSC prognosis and analyze immunocyte infiltration. This may provide a novel insight for exploring the potential IRGs in the IME of LUSC.
Highlights
Lung cancer remains a leading factor leading to cancer-related deaths worldwide [1]
differentially expressed immune-related genes (DEIRGs) were obtained from differentially expressed genes (DEGs) based on the Immunology Database and Analysis Portal (ImmPort) database, whereas differentially expressed transcription factors (DETFs) were extracted from DEGs using the Cistrome database
According to the set thresholds (P < 0.01 and fold change of >2), 3,599 DEGs, 223 DEIRGs, and 46 DETFs were screened in lung squamous cell carcinoma (LUSC) as well as non-LUSC tissue specimens
Summary
Lung cancer remains a leading factor leading to cancer-related deaths worldwide [1]. Lung cancer is associated with a high mortality compared with that of breast cancer (BC), prostate cancer (PCa), colorectal cancer (CRC), and leukemia [1, 2]. The prognostic biomarkers that can be used in a prediction model for LUSC patients are still lacking [6, 7]. Immunotherapy has been widely recognized to be the efficient therapy for many cancer types [8,9,10,11]. Fan et al had identified reliable markers for predicting the immunotherapy effect on non-small cell lung cancer (NSCLC) [12]. Immunotherapy has been considered as the potentially efficient therapy in tumor patients [12]. Li et al used IRGPs to construct the personalized prognostic model to predict the prognosis for early non-sqNSCLC patients [15]. The prognostic significance of IRGs and clinical relevance in LUSC have not been illustrated so far
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