Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.
Department of Nephrology, Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, China.
Comput Math Methods Med. 2020 Nov 16;2020:8836493. doi: 10.1155/2020/8836493. eCollection 2020.
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.
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.
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.
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.
免疫疗法为治疗皮肤黑色素瘤提供了一种新方法，但个体患者的临床疗效不同。考虑到免疫疗法的高成本和不良反应，探索疗效的预测生物标志物至关重要。最近，肿瘤突变负担（TMB）已被提出作为免疫反应的预测预后指标。
从癌症基因组图谱（TCGA）数据库下载 472 例皮肤黑色素瘤患者的 RNA-seq 和体细胞突变数据集，分析突变类型和 TMB。通过 LASSO 和多变量 Cox 回归分析鉴定差异表达基因（DEG）。通过 LASSO 和多变量 Cox 回归分析鉴定 TMB 相关特征。从 TIMER 数据库评估特征突变体与免疫细胞的关联。此外，Wilcox 检验用于评估基于 CIBERSORT 算法计算的风险分组中免疫浸润的差异。
C>T 取代和 TTN 分别是最常见的 SNV 和突变基因。低 TMB 患者预后不良。DEG 主要涉及皮肤发育、细胞周期、DNA 复制和免疫相关的串扰途径。此外，建立了一个由八个 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，低风险组的 CD4+和 CD8+T 细胞、NK 细胞和 M1 巨噬细胞的免疫浸润较高，而高风险组的 M0 和 M2 巨噬细胞的免疫浸润较高。
我们的研究表明，皮肤黑色素瘤中较高的 TMB 与良好的生存结果相关。此外，还确定了预后模型与免疫浸润之间的密切关联，为免疫治疗提供了一个新的潜在靶点。
