Identification of immune-related genes and integrated analysis of immune-cell infiltration in melanoma

Abstract

Objective: This study was conducted to screen out immune-related genes in connection with the prognosis of melanoma, construct a prognosis model and explore the relevant mechanisms.

Methods and materials: 1973 genes associated with immune system were derived from the Immport database, and RNA-seq data of melanoma and information of patients were searched from the Xena database. Cox univariate analysis, Lasso analysis and Cox multivariate analysis were used to screen out six genes to construct the model. Then the risk scores were estimated for patients based on our constructed prognosis model. Estimate was used to affirm that the model was about immune infiltration, and CIBERSORT was used to screen out immune cells associated with prognosis. TIDE was applied to predict the efficacy of immunotherapy. Finally, GSE65904 and GSE19234 were used to confirm the effectiveness of the model.

Results: ADCYAP1R1, GPI, NTS might cause poor prognosis while IFITM1, KIR2DL4, LIF were more likely conductive to prognosis of melanoma patients and a model of prognosis was constructed on the basis of these six genes. The effectiveness of the model has been proven by the ROC curve, and the miRNAs targeting the screened genes were found out, suggesting that the immune system might impact on the prognosis of melanoma by T cell CD8⁺, T cell CD4⁺ memory and NK cells.

Conclusions: In this study, the screened six genes were associated with the prognosis of melanoma, which was conductive to clinical prognostic prediction and individualized treatment strategy.

Keywords: immune infiltration; melanoma; prognostic model.

Figure 1

Forest plot and survival analysis of biomarkers. (A) The Cox proportional hazards model based on ADCYAP1R1, GPI, IFITM1, KIR2DL4, LIF and NTS. (B) Survival analysis of KIR2DL4 in melanoma (P<0.0001). (C) Survival analysis of IFITM1 in melanoma (P<0.0001). (D) Survival analysis of GPI in melanoma (P=0.0026). (E) Survival analysis of LIF in melanoma (P=0.0006). (F) Survival analysis of ADCYAP1R1 in melanoma (P=0.00049). (G) Survival analysis of NTS in melanoma (P=0.0065).

Figure 2

Risk score and ROC curve of melanoma. (A) Risk score of melanoma patients distributed in ascending order. (B) Survival time and status of melanoma patients in order of increasing risk score. The red dots represent the surviving patients and the blue dots represent dead. (C) The heatmap shows the expression of these six biomarkers in melanoma in order of increasing risk scores. (D) The ROC curve for 1, 2, 5-year survival prediction with AUC value.

Figure 3

Enrichment analysis of DEGs. (A) Biological process of DEGs. (B) Molecular function of DEGs. (C) Cellular component of DEGs. (D) KEGG pathways of DEGs.

Figure 4

Identification of DEmiRNAs and ceRNA network. (A) Volcano plot of miRNAs between high RS and low RS groups. (B) Heatmap plot of miRNAs between high RS and low RS groups. (C) Differential expression of miRNAs-mRNAs network in melanoma.

Figure 5

Somatic mutation analysis. (A) Boxplot of VAF in high RS group. (B) Boxplot of VAF in low RS group. (C) Forestplot of mutant genes in different groups.

Figure 6

ESTIMATE analysis. (A) Immune score of high RS samples and low RS samples by ESTIMATE. (B) Stromal score of high RS samples and low RS samples by ESTIMATE. (C) ESTIMATE score of high RS samples and low RS samples by ESTIMATE. (D) Tumor purity of high RS samples and low RS samples by ESTIMATE. (E) Risk scores for four TME subtypes in samples of GSE22153. (F) Risk scores for four TME subtypes in melanoma samples of TCGA.

Figure 7

CIBERSORT analysis. (A) The heatmap of immune cell infiltration in high RS samples and low RS samples. Red represents low RS samples, and blue represents high-risk samples. (B) Correlation analysis between different immune cells and biomarkers.

Figure 8

TIDE analysis and validation. (A) TIDE score of high RS samples and low RS samples. (B) CAF score of high RS samples and low RS samples. (C) MDSC score of high RS samples and low RS samples. (D) TAM M2 score of high RS samples and low RS samples. (E) Survival analysis of risk score in GSE65904. (F) The ROC curve for 4, 6, 8, 10-year survival prediction with AUC value. (G) Survival analysis of risk score in GSE19234. (H) The ROC curve for 10, 20, 30-month survival prediction with AUC value.