Gene expression and immune infiltration in melanoma patients with different mutation burden

Abstract

Background: Immunotherapy is a vital component in cancer treatment. However, due to the complex genetic bases of cancer, a clear prediction index for efficacy has not been established. Tumor mutation burden (TMB) is one of the essential factors that affect immunotherapeutic efficacies, but it has not been determined whether the mutation is associated with the survival of Skin Cutaneous Melanoma (SKCM) patients. This study aimed at evaluating the correlation between TMB and immune infiltration.

Methods: Somatic mutation profiles (n = 467), transcriptome data (n = 471), and their clinical information (n = 447) of all SKCM samples were downloaded from The Cancer Genome Atlas (TCGA) database. For each sample, TMB was calculated as the number of variants per megabase. Based on K-M survival analysis, they were allocated into the high-TMB and low-TMB groups (the optimal cutoff was determined by the 'surv_cutpoint' algorithm of survival R package). Then, Gene ontology (GO) and Gene Set Enrichment Analyses (GSEA) were performed, with immune-associated biological pathways found to be significantly enriched in the low-TMB group. Therefore, immune genes that were differentially expressed between the two groups were evaluated in Cox regression to determine their prognostic values, and a four-gene TMB immune prognostic model (TMB-IP) was constructed.

Results: Elevated TMB levels were associated with better survival outcomes in SKCM patients. Based on the cutoff value in OS analysis, they were divided into high-TMB and low-TMB groups. GSEA revealed that the low-TMB group was associated with immunity while intersection analysis revealed that there were 38 differentially expressed immune-related genes between the two groups. Four TMB-associated immune genes were used to construct a TMB-IP model. The AUC of the ROC curve of this model reached a maximum of 0.75 (95%CI, 0.66-0.85) for OS outcomes. Validation in each clinical subgroup confirmed the efficacy of the model to distinguish between high and low TMB-IP score patients.

Conclusions: In SKCM patients, low TMB was associated with worse survival outcomes and enriched immune-associated pathways. The four TMB-associated immune genes model can effectively distinguish between high and low-risk patients.

Keywords: ICB; SKCM; Survival analysis; TCGA; TMB.

Fig. 1

Mutation profile landscape in SKCM samples. a Waterfall plot showing the mutation details of every gene in every sample; b,c,d Various types of mutation classified based on different groups; e, f burden of tumor mutation in particular samples; g Top ten mutated genes. Various types of mutations are represented by different color annotations at the right-bottom

Fig. 2

TMB prognosis and its relationship with clinical features. Higher TMB levels correlated with better OS (a), better DSS (b), and better PFI (c); d-i Wilcoxon and Kruskal-Wallis test in groups of different clinical characteristics

Fig. 3

Differentially expression analysis and Construction of TMB-IP. a Top 50 DEGs were displayed in heatmap plot; b GO results of 504 DEGs; c GSEA revealed the top TMB- associated pathways revealed that low-TMB was correlated with immune-related pathways; d Survival analysis based on the immunescore; e-g Univariate-lasso-multivariate Cox regression of 38 immune-related DEGs; h Survival analysis based on the TMB-IP score; i Multi-year ROC curves based on the TMB-IP score; j-m Survival analysis of four immune-related hub genes based on their RNA expression levels; n-s Survival analysis of six clinical subgroups based on high and low TMB-IP grouping

Fig. 4

Associations mutants with immune cells infiltration of four hub genes. a-d Mutants (Arm-level Deletion, Deep Deletion, High Amplication, Arm-level Gain) of four TMB-associated genes exhibited low level of immune cell infiltration compared with Diploid/Normal

Fig. 5

Twenty-two immune fractions in low vs. high-TMB groups. a Barplot of the 22 immune fractions denoted by different colors: b Wilcoxon test of 22 immune fractions in high- vs. low-TMB group