Zhang Min, Liu Jian, Zhang Fangxu, Liang Qian, Guo Zhiqiang
Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, 41000, People's Republic of China.
Department of Otolaryngology-Head and Neck Surgery, Shandong Provincial Hospital Affiliated to Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, 250117, People's Republic of China.
Discov Oncol. 2024 Nov 28;15(1):722. doi: 10.1007/s12672-024-01627-4.
Neddylation, as a post-translational modification, has garnered significant attention in various tumor types recently. Few studies have investigated the involvement of neddylation-related genes (NRGs) in cutaneous melanoma (CM). Our study aims to identify prognostic NRGs and investigate their potential roles in CM. The RNA-sequencing data and corresponding clinical data of CM patients were retrieved from The Cancer Genome Atlas (TCGA) database, while the expression profiles of 812 normal skin specimens were obtained from the Genotype-Tissue Expression (GTEx) database. The neddylation-related genes (NRGs) were extracted from the Molecular Signatures Database (MSigDB). We identified differentially expressed NRGs in CM and determined neddylation-related prognostic genes through univariate Cox regression analysis. We constructed a novel NRGs signature using LASSO-COX. The accuracy and utility of the NRGs signature were evaluated via a variety of statistical methods. Bioinformatics tools were employed to investigate the differential biological functions and signaling pathways among distinct risk groups. The expression levels of NRGs were analyzed through RT-qPCR experiments conducted in vitro. Finally, we identified an 8-NRGs signature in CM. Our prognostic model exhibited a high predictive capability for outcomes. The differences in the proportions of immune cells among subgroups were statistically significant. The in vitro experiments indicated significant differences in the expression of our NRGs. The 8-NRGs signature serves as a prognostic model for CM. Importantly, the novel biological prognostic model holds potential for personalized therapy in CM patients.
Neddylation作为一种翻译后修饰，近年来在各种肿瘤类型中受到了广泛关注。很少有研究调查Neddylation相关基因（NRGs）在皮肤黑色素瘤（CM）中的作用。我们的研究旨在识别预后性NRGs，并研究它们在CM中的潜在作用。CM患者的RNA测序数据和相应的临床数据从癌症基因组图谱（TCGA）数据库中获取，而812个正常皮肤样本的表达谱则从基因型-组织表达（GTEx）数据库中获得。Neddylation相关基因（NRGs）从分子特征数据库（MSigDB）中提取。我们在CM中识别出差异表达的NRGs，并通过单变量Cox回归分析确定与Neddylation相关的预后基因。我们使用LASSO-COX构建了一个新的NRGs特征。通过多种统计方法评估NRGs特征的准确性和实用性。利用生物信息学工具研究不同风险组之间的差异生物学功能和信号通路。通过体外进行的RT-qPCR实验分析NRGs的表达水平。最后，我们在CM中识别出一个由8个NRGs组成的特征。我们的预后模型对预后具有较高的预测能力。亚组间免疫细胞比例的差异具有统计学意义。体外实验表明我们的NRGs表达存在显著差异。这个由8个NRGs组成的特征可作为CM的预后模型。重要的是，这个新的生物学预后模型在CM患者的个性化治疗中具有潜力。
