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

Abstract

There is a correlation between tumors and immunity with the degree of immune cell infiltration in tumors being closely related to tumor growth and progression. Therefore, the present study identified immune-related prognostic genes and evaluated the immune infiltration level in lung adenocarcinoma (LUAD). This study performed Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and Gene Set Enrichment Analysis (GSEA) enrichment analyses on differential immune-associated genes. A risk model was created and validated using six immune-related prognostic genes. Reverse transcription-quantitative PCR was used to assess the prognostic gene expression in non-small cell lung cancer cells. Immune cell infiltration in LUAD was analyzed using the CIBERSORT method. Single sample GSEA was used to compare Tumor Immune Dysfunction and Exclusion (TIDE) scores between high and low-risk groups and to assess the activation of thirteen immune-related pathways. Multifactor Cox proportional hazards model analysis identified six prognostic risk genes (S100A16, FURIN, FGF2, LGR4, TNFRSF11A and VIPR1) to construct a risk model. The survival and receiver operating characteristic curves indicated that patients with higher risk scores had lower overall survival rates. The expression levels of prognostic genes S100A16, FURIN, LGR4, TNFRSF11A and VIPR1 were significantly increased in LUAD. B cells naive, plasma cells, T cells CD4 memory activated, T cells follicular helper, T cells regulatory, NK cells activated, macrophages M1, macrophages M2, and Dendritic cells resting cells showed elevated expression in LUAD. The prognostic genes were differentially associated with individual immune cells. Immune-related function scores, such as those for antigen presenting cell (APC) co-stimulation, APC co-inhibition, check-point, Cytolytic-activity, chemokine receptor, parainflammation, major histocompatibility complex-class-I, type-I-IFN-reponse and T-cell-co-inhibition, were higher in the high-risk group compared with the low-risk group. Furthermore, the TIDE score of the high-risk group was significantly lower than the low-risk group. This immune-related gene prognostic model has the potential to predict the prognosis of LUAD patients, supporting the development of a personalized clinical diagnosis and treatment plan.

Keywords: bioinformatics; immune cell infiltration; immune-related genes; lung adenocarcinoma; prognosis.

Figure 1.

The differential expression and enrichment analysis of immune-related genes among lung adenocarcinoma patients. (A) Volcano map of immune-related genes. Green indicates downregulated differential immune-related genes and red indicates upregulated differential immune-related genes. (B) Immune-related gene intersection presented in a Venn diagram. (C) Gene Ontology, (D) Kyoto Encyclopedia of Genes and Genomes, and (E) Gene Set Enrichment Analysis enrichment analysis. DEGs, differently expressed genes; BP, biological processes; CC, cellular component; MF, molecular function.

Figure 2.

Prognostic model construction. (A) Forest diagram of seven differentially expressed immune genes. (B) The risk score curve with patients ordered by increased risk score. (C) The survival status diagram. (D) The survival heat map for high-risk and low-risk groups. Red represents increased expression and green indicates reduced expression.

Figure 3.

Analysis of prognostic models. (A) Survival curve for high and low risk groups. (B): ROC curve, (C) Nomogram, (D) univariate Cox regression analysis and (E) multivariate Cox regression analysis of the prognostic models. ROC, receiver operating characteristic; AUC, area under the curve.

Figure 4.

Prognostic gene expression and survival analysis. Expression of (A) S100A16, (B) FURIN, (C) LGR4, (D) TNFRSF11A, (E) VIPR1 and (F) FGF2 in normal and tumor tissues. Survival analysis of patients with high and low expression levels of (G) S100A16, (H) FURIN, (I) LGR4, (J) TNFRSF11A, (K) VIPR1 and (L) FGF2.

Figure 5.

Reverse transcription-quantitative PCR and staining analysis. (A) S100A16, FURIN, FGF2, LGR4, TNFRSF11A and VIPR1 mRNA expression levels in MRC5, H1975 and A549 cells. (B) S100A16, FURIN, (C) FGF2, LGR4, (D) TNFRSF11A, and VIPR1 protein expression in normal alveolar and tumor cells. The immunohistochemistry images were downloaded from the Human Protein Atlas database (https://www.proteinatlas.org/ENSG00000188643-S100A16/pathology/lung+cancer; https://www.proteinatlas.org/ENSG00000140564-FURIN/pathology/lung+cancer; https://www.proteinatlas.org/ENSG00000205213-LGR4/pathology/lung+cancer; https://www.proteinatl-as.org/ENSG00000141655-TNFRSF11A/pathology/lung+cancer; and http://www.proteina-tlas.org/ENSG00000114812-VIPR1/pathology/lung+cancer). **P<0.01, ***P<0.001 and ****P<0.0001.

Figure 6.

Analysis of immune cell infiltration. (A) Immune cell types involved in lung adenocarcinoma represented using a heat map. Red indicates high expression and green indicates low expression. (B) Differential expression of immune cells. blue indicates normal tissue and red indicates tumor tissue. (C) Correlation between prognostic genes and infiltrating immune cells. *P<0.05, **P<0.01 and ***P<0.001.

Figure 7.

Immune cell survival analysis. Survival analysis of patients with high and low expression of (A) macrophages M1, (B) T cells CD4 memory activated, (C) NK cells resting, (D) T cells CD8, (E) plasma cells, (F) mast cells resting and (G) monocytes.

Figure 8.

Immune-related functional analysis. (A) The scores of 13 immune-related functions among high and low-risk groups of LUAD. (B) TIDE, (C) Dysfunction, (D) Exclusion and (E) MSI scores for high and low-risk groups of patients with LUAD. TIDE, Tumor Immune Dysfunction and Exclusion; MSI, microsatellite instability; LUAD, lung adenocarcinoma. *P<0.05, **P<0.01 and ***P<0.001.