Hu Bingqian, Hounye Alphonse Houssou, Wang Zheng, Qi Min, Zhang Jianglin
Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
School of Mathematics and Statistics, Central South University, Changsha, China.
Front Oncol. 2023 Feb 6;13:1108128. doi: 10.3389/fonc.2023.1108128. eCollection 2023.
Melanoma is a common and aggressive cutaneous malignancy characterized by poor prognosis and a high fatality rate. Recently, due to the application of Immune-checkpoint inhibitors (ICI) in melanoma treatment, melanoma patients' prognosis has been tremendously improved. However, the treatment effect varies quite differently from patient to patient. In this study, we aim to construct and validate a Cuproptosis-related risk model to improve outcome prediction of ICIs in melanoma and divide patients into subtypes with different Cuproptosis-related genes.
Here, according to differentially expressed genes from four melanoma datasets in GEO (Gene Expression Omnibus), and one in TCGA (The Cancer Genome Atlas) database, a novel signature was developed through LASSO and Cox regression analysis. We used 781 melanoma samples to examine the molecular subtypes associated with Cuproptosis-related genes and studied the related gene mutation and TME cell infiltration. Patients with melanoma can be divided into at least three subtypes based on gene expression profile. Survival pan-cancer analysis was also conducted for melanoma patients.
The Cuproptosis risk score can predict tumor immunity, subtype, survival, and drug sensitivity for melanoma. And Cuproptosis-associated subtypes can help predict therapeutic outcomes.
Cuproptosis risk score is a promising potential biomarker in cancer diagnosis, molecular subtypes determination, TME cell infiltration characteristics, and therapy response prediction in melanoma patients.
黑色素瘤是一种常见且侵袭性强的皮肤恶性肿瘤，预后较差，死亡率高。近年来，由于免疫检查点抑制剂（ICI）应用于黑色素瘤治疗，黑色素瘤患者的预后有了极大改善。然而，治疗效果在患者之间差异很大。在本研究中，我们旨在构建并验证一种铜死亡相关风险模型，以改善黑色素瘤中ICI的疗效预测，并将患者分为具有不同铜死亡相关基因的亚型。
在此，根据来自基因表达综合数据库（GEO）中四个黑色素瘤数据集以及癌症基因组图谱（TCGA）数据库中一个数据集的差异表达基因，通过LASSO和Cox回归分析开发了一种新的特征。我们使用781个黑色素瘤样本检查与铜死亡相关基因相关的分子亚型，并研究相关基因突变和肿瘤微环境（TME）细胞浸润。黑色素瘤患者可根据基因表达谱至少分为三种亚型。还对黑色素瘤患者进行了生存泛癌分析。
铜死亡风险评分可预测黑色素瘤的肿瘤免疫、亚型、生存和药物敏感性。并且铜死亡相关亚型有助于预测治疗结果。
铜死亡风险评分在黑色素瘤患者的癌症诊断、分子亚型确定、TME细胞浸润特征及治疗反应预测方面是一种有前景的潜在生物标志物。
