Wu Yunyang, Yin Shenhui, Li Chunzhen, Zhao Liyuan, Song Mengqi, Yu Yizhi, Tang Ling, Yang Yanlong
School of Traditional Chinese Medicine, Naval Medical University Shanghai, China.
Department of Traditional Chinese Medicine, The First Affiliated Hospital of Naval Medical University Shanghai, China.
Am J Cancer Res. 2024 Apr 15;14(4):1712-1729. doi: 10.62347/LHKW3124. eCollection 2024.
Melanoma is the most aggressive type of skin cancer and has a high mortality rate once metastasis occurs. Hypoxia is a universal characteristic of the microenvironment of cancer and a driver of melanoma progression. In recent years, long noncoding RNAs (lncRNAs) have attracted widespread attention in oncology research. In this study, screening was performed and revealed seven hypoxia-related lncRNAs AC008687.3, AC009495.1, AC245128.3, AL512363.1, LINC00518, LINC02416 and MCCC1-AS1 as predictive biomarkers. A predictive risk model was constructed via univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses. Patients were grouped according to the model risk score, and Kaplan-Meier analysis was performed to compare survival between groups. Functional and pathway enrichment analyses were performed to compare gene set enrichment between groups. Moreover, a nomogram was constructed with the risk score as a variable. In both the training and validation sets, patients in the low-risk group had better overall survival than did those in the high-risk group (P<0.001). The 3-, 5- and 10-year area under the curve (AUC) values for the nomogram model were 0.821, 0.795 and 0.820, respectively. Analyses of immune checkpoints, immunotherapy response, drug sensitivity, and mutation landscape were also performed. The results suggested that the low-risk group had a better response to immunotherapeutic. In addition, the nomogram can effectively predict the prognosis and immunotherapy response of melanoma patients. The signature of seven hypoxia-related lncRNAs showed great potential value as an immunotherapy response biomarker, and these lncRNAs might be treatment targets for melanoma patients.
黑色素瘤是最具侵袭性的皮肤癌类型，一旦发生转移，死亡率很高。缺氧是癌症微环境的一个普遍特征，也是黑色素瘤进展的驱动因素。近年来，长链非编码RNA（lncRNAs）在肿瘤学研究中引起了广泛关注。在本研究中，通过筛选发现了7种与缺氧相关的lncRNAs，即AC008687.3、AC009495.1、AC245128.3、AL512363.1、LINC00518、LINC02416和MCCC1-AS1，作为预测生物标志物。通过单变量Cox回归分析、最小绝对收缩和选择算子（LASSO）以及多变量Cox回归分析构建了预测风险模型。根据模型风险评分对患者进行分组，并进行Kaplan-Meier分析以比较组间生存率。进行功能和通路富集分析以比较组间基因集富集情况。此外，以风险评分为变量构建了列线图。在训练集和验证集中，低风险组患者的总生存率均高于高风险组患者（P<0.001）。列线图模型的3年、5年和10年曲线下面积（AUC）值分别为0.821、0.795和0.820。还进行了免疫检查点、免疫治疗反应、药物敏感性和突变图谱分析。结果表明，低风险组对免疫治疗的反应更好。此外，列线图可以有效预测黑色素瘤患者的预后和免疫治疗反应。7种与缺氧相关的lncRNAs特征作为免疫治疗反应生物标志物具有很大的潜在价值，这些lncRNAs可能是黑色素瘤患者的治疗靶点。
