Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, Liaoning Province 110122, China; Liaoning Key Laboratory of Molecular Targeted Anti-tumor Drug Development and Evaluation, China Medical University, Shenyang, Liaoning Province 110122, China.
Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, Liaoning Province 110122, China; Liaoning Key Laboratory of Molecular Targeted Anti-tumor Drug Development and Evaluation, China Medical University, Shenyang, Liaoning Province 110122, China.
Int Immunopharmacol. 2020 Dec;89(Pt A):107162. doi: 10.1016/j.intimp.2020.107162. Epub 2020 Nov 7.
Skin cutaneous melanoma (SKCM) is the most invasive form of skin cancer with poor prognosis. Growing evidence has demonstrated that tumor immune microenvironment plays a key contributing role in tumorigenesis and predicting clinical outcomes. The aim of this study was to recognize immune classification and a reliable prognostic signature for patients with SKCM. By using single-sample gene set enrichment (ssGSEA) and hierarchical clustering analyses, we evaluated the immune infiltration landscape of SKCM afflicted patients from The Cancer Genome Atlas (TCGA) dataset and named two SKCM subtypes: Immunity-high and Immunity-low. The Immunity-high subgroup was characterized by up-regulation of immune response and favorable survival probability. Seven candidate small molecule drugs which potentially reverse SKCM immune status were identified by using Connectivity map (CMap) database. A prognostic five-immune-associated gene (IAG) signature consisting IFITM1, TNFSF13B, APOBEC3G, CCL8 and KLRK1 with high predictive value was established using the LASSO Cox regression analysis in training set, and validated in testing set as well as Gene Expression Omnibus (GEO) external validation cohort (P < 0.05). Lower tumor purity and active immune-related signaling pathways were obviously presented in low-risk group. Furthermore, a novel composite nomogram based upon the five-IAG signature and other clinical parameters was built with excellent calibration curves. Collectively, comprehensively characterizing the SKCM subtypes based upon immune microenvironment landscape and development of a survival-related IAG signature may provide a promising avenue for improving individualized treatment design and prognosis prediction for patients with SKCM.
皮肤皮肤黑色素瘤(SKCM)是预后最差的侵袭性皮肤癌。越来越多的证据表明,肿瘤免疫微环境在肿瘤发生和预测临床结局中起着关键作用。本研究旨在识别 SKCM 患者的免疫分类和可靠的预后特征。通过使用单样本基因集富集(ssGSEA)和层次聚类分析,我们评估了来自癌症基因组图谱(TCGA)数据集的 SKCM 患者的免疫浸润景观,并将其命名为两个 SKCM 亚型:免疫高和免疫低。免疫高亚组的特征是免疫反应上调和有利的生存概率。通过使用连接图谱(CMap)数据库,我们确定了七种可能逆转 SKCM 免疫状态的候选小分子药物。使用训练集中的 LASSO Cox 回归分析建立了一个由 5 个免疫相关基因(IAG)组成的预后签名,包括 IFITM1、TNFSF13B、APOBEC3G、CCL8 和 KLRK1,在验证集和基因表达综合(GEO)外部验证队列中均具有较高的预测价值(P<0.05)。在低风险组中,肿瘤纯度较低且免疫相关信号通路活跃。此外,基于五个 IAG 特征和其他临床参数建立了一种新的综合列线图,其校准曲线良好。总之,基于免疫微环境景观全面描述 SKCM 亚型并开发与生存相关的 IAG 特征,可能为改善 SKCM 患者的个体化治疗设计和预后预测提供有前途的途径。