Melanoma long non-coding RNA signature predicts prognostic survival and directs clinical risk-specific treatments
Melanoma long non-coding RNA signature predicts prognostic survival and directs clinical risk-specific treatments
复制标题
黑色素瘤长非编码 RNA 特征可预测预后生存并指导临床风险特异性治疗
DOI：
10.1016/j.jdermsci.2016.12.006
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发表时间：
2017-03-01
影响因子：
4.6
通讯作者：
Zhu, Liucun
中科院分区：
文献类型：
--
作者：
Chen, Xijia;Guo, Wenna;Zhu, Liucun
背景资料：多项研究表明，Breslow厚度、肿瘤溃疡和有丝分裂指数可作为皮肤黑色素瘤患者的预后指标。然而，近年来，由于这些临床病理标志物缺乏对黑色素瘤内源性机制的有效解释，对黑色素瘤预后的研究重点已转向肿瘤分子标志物。目的：本研究旨在鉴定与生存相关的长链非编码RNA（lncRNA），并根据这些lncRNA的不同表达，对黑色素瘤患者进行临床风险特异性诊断和辅助治疗，方法：从The Cancer Genome Atlas数据集和Gene Expression Omnibus数据集（GSE 65904）获得临床信息和相应的RNA表达数据。所有样本被分类为一个训练数据集和两个验证数据集。然后使用考克斯比例风险回归分析来鉴定存活相关lncRNA，并在训练数据集中构建风险评估签名。Kaplan-Meier方法用于估计该特征在训练数据集和两个验证数据集中预测患者生存期的效用。结果：该签名用于危险分层是有效的，Kaplan-Meier分析表明高危组患者的生存期明显短于低危组。受试者工作特征曲线下面积为0.711（95%置信区间：0.618-0.804）和0.698在两个验证数据集上分别用该特征预测患者的生存期时，其95%可信区间为0.614-0.782，表明该特征具有较好的上级特异性和敏感性。我们确定了一个四IncRNA预后标志与黑色素瘤患者的风险分层的能力。从该特征中获得的风险评分，结合鉴别诊断和鉴别辅助治疗，可能会改善患者的预后生活质量，特别是处于疾病早期的患者或Breslow厚度不超过2 mm的患者。（C）2016年日本皮肤病研究学会。由Elsevier爱尔兰有限公司出版。保留所有权利。
Background: Various studies have demonstrated that the Breslow thickness, tumor ulceration and mitotic index could serve as prognostic markers in patients with cutaneous melanoma. Recently, however, as these clinicopathological biomarkers lack efficient interpretation of endogenous mechanism of melanoma, the emphasis on the prognosis of melanoma has transformed to molecular tumor markers.Objective: This study was designed to identify survival-related long non-coding RNAs (IncRNAs), and based on the different expressions of these lncRNAs, clinical risk-specific diagnosis and adjuvant therapy could be employed on melanoma patients, especially patients in the early course of disease or patients with a Breslow thickness no more than 2 mm.Methods: The clinical information and corresponding RNA expression data were obtained from The Cancer Genome Atlas dataset and Gene Expression Omnibus dataset (GSE65904). All samples were categorized into one training dataset and two validation datasets. Cox proportional hazard regression analysis was then used to identify survival-related lncRNAs and risk assessment signature was constructed in training dataset. Kaplan-Meier method was used to estimate the utility of this signature in predicting the duration of survival of patients both in the training dataset and two validation datasets. Meanwhile receiver operating characteristic analyses were used to evaluate the predictive effectiveness of this signature in two validation datasets.Results: It was found that the signature was effective while used for risk stratification, and Kaplan-Meier analyses indicated that the duration of survival of patients in high-risk groups were significantly shorter than that of low-risk groups. Moreover, areas under the receiver operating characteristic curve were 0.711 (95% confidence interval: 0.618-0.804) and 0.698 (95% confidence interval: 0.614-0.782) when this signature was used to predict the patients' duration of survival in two validation datasets respectively, indicating the superior specificity and sensitivity of this signature.Conclusion: We identified a four-IncRNA prognostic signature with the ability of risk stratification for melanoma patients. Risk score acquired from this signature, combining with differential diagnosis and differential adjuvant therapy, could potentially improve the prognosis quality of life for patients, especially patients in the early course of disease or patients with a Breslow thickness no more than 2 mm. (C) 2016 Japanese Society for Investigative Dermatology. Published by Elsevier Ireland Ltd. All rights reserved.