Background. Immunotherapy offers a novel approach for the treatment of cutaneous melanoma, but the clinical efficiency varies for individual patients. In consideration of the high cost and adverse effects of immunotherapy, it is essential to explore the predictive biomarkers of outcomes. Recently, the tumor mutation burden (TMB) has been proposed as a predictive prognosticator of the immune response. Method. RNA-seq and somatic mutation datasets of 472 cutaneous melanoma patients were downloaded from The Cancer Genome Atlas (TCGA) database to analyze mutation type and TMB. Differently expressed genes (DEGs) were identified for functional analysis. TMB-related signatures were identified via LASSO and multivariate Cox regression analysis. The association between mutants of signatures and immune cells was evaluated from the TIMER database. Furthermore, the Wilcox test was applied to assess the difference in immune infiltration calculated by the CIBERSORT algorithm in risk groupings. Results. C>T substitutions and TTN were the most common SNV and mutated gene, respectively. Patients with low TMB presented poor prognosis. DEGs were mainly implicated in skin development, cell cycle, DNA replication, and immune-associated crosstalk pathways. Furthermore, a prognostic model consisting of eight TMB-related genes was developed, which was found to be an independent risk factor for treatment outcome. The mutational status of eight TMB-related genes was associated with a low level of immune infiltration. In addition, the immune infiltrates of CD4+ and CD8+ T cells, NK cells, and M1 macrophages were higher in the low-risk group, while those of M0 and M2 macrophages were higher in the high-risk group. Conclusion. Our study demonstrated that a higher TMB was associated with favorable survival outcome in cutaneous melanoma. Moreover, a close association between prognostic model and immune infiltration was identified, providing a new potential target for immunotherapy.

中文翻译：

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基于肿瘤突变负荷分析的皮肤黑色素瘤预后生物标志物的鉴定

背景。免疫疗法为治疗皮肤黑色素瘤提供了一种新方法，但临床效率因患者而异。考虑到免疫治疗的高成本和副作用，有必要探索预后的预测生物标志物。最近，肿瘤突变负荷 (TMB) 已被提议作为免疫反应的预测指标。方法. 从癌症基因组图谱 (TCGA) 数据库下载了 472 名皮肤黑色素瘤患者的 RNA-seq 和体细胞突变数据集，以分析突变类型和 TMB。鉴定了不同表达的基因（DEG）用于功能分析。通过 LASSO 和多变量 Cox 回归分析确定 TMB 相关特征。从 TIMER 数据库评估了特征突变体与免疫细胞之间的关联。此外，应用 Wilcox 检验来评估通过 CIBERSORT 算法计算的风险分组中免疫浸润的差异。结果. C>T 替换和 TTN 分别是最常见的 SNV 和突变基因。TMB低的患者预后较差。DEG 主要与皮肤发育、细胞周期、DNA 复制和免疫相关的串扰通路有关。此外，还开发了一个由 8 个 TMB 相关基因组成的预后模型，该模型被发现是治疗结果的独立危险因素。八个 TMB 相关基因的突变状态与低水平的免疫浸润有关。此外，CD4+和CD8+ T细胞、NK细胞和M1巨噬细胞的免疫浸润在低风险组中较高，而M0和M2巨噬细胞在高风险组中较高。结论. 我们的研究表明，较高的 TMB 与皮肤黑色素瘤的良好生存结果相关。此外，确定了预后模型与免疫浸润之间的密切关联，为免疫治疗提供了新的潜在靶点。