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A novel RNA sequencing-based prognostic nomogram to predict survival for patients with cutaneous melanoma: Clinical trial/experimental study.

一种新的基于RNA测序的预后列线图来预测皮肤黑色素瘤患者的生存: 临床试验/实验研究。

  • 影响因子:1.95
  • DOI:10.1097/MD.0000000000018868
  • 作者列表:"Tian J","Yang Y","Li MY","Zhang Y
  • 发表时间:2020-01-01
Abstract

BACKGROUND:Plenty of evidence has suggested that long non-coding RNAs (lncRNAs) have played a vital part may act as prognostic biomarkers in a variety of cancers. The aim of this study was to screen survival-related lncRNAs and to construct a lncRNA-based prognostic model in patients with cutaneous melanoma (CM). METHODS:We obtained lncRNAs expression profiles and clinicopathological data from the Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. A lncRNA-based prognostic model was established in training set. The established prognostic model was evaluated, and validated in the validation set. Then, a prognostic nomogram combining the lncRNA-based risk score and clinicopathological characteristics was developed in training set, and assessed in the validation set. The accuracy of the model was evaluated by the discrimination and calibration plots. RESULTS:A total of 212 lncRNAs were identified to be differentially expressed in CM. After univariate analysis, LASSO penalized regression analysis, and multivariate analysis, 3 lncRNAs were used to construct risk score model. The proposed risk score model could divide patients into high-risk and low-risk groups with significantly different survival in both training set and validation set. The ROC curve showed good performance in survival prediction in both sets. Furthermore, the nomogram for predicting 3-, 5-, and 10-year OS was established based on lncRNA-based risk score and clinicopathologic factors. The prognostic accuracy of the risk model was confirmed by the discrimination and calibration plots in both training set and validation set. CONCLUSIONS:We established a novel three lncRNA-based risk score model and nomogram to predict overall survival of CM. The proposed nomogram may provide information for individualized treatment in CM patients.

摘要

背景: 大量证据表明,长链非编码rna (lncRNAs) 在多种癌症中起着至关重要的作用,可能作为预后生物标志物。本研究的目的是筛选生存相关lncRNA,并构建基于lncRNA的皮肤黑色素瘤 (CM) 患者预后模型。 方法: 我们从癌症基因组图谱 (TCGA) 和基因型-组织表达 (GTEx) 数据库中获得了lncRNAs表达谱和临床病理数据。在训练集中建立了基于lncRNA的预后模型。对建立的预后模型进行评价,并在验证集中进行验证。然后,在训练集中开发了结合基于lncRNA的风险评分和临床病理特征的预后列线图,并在验证集中进行评估。通过判别和校准图评价模型的准确性。 结果: 共鉴定出 212 个lncRNAs在CM中差异表达。经过单变量分析、LASSO惩罚回归分析和多变量分析,使用 3 个lncRNAs构建风险评分模型。所提出的风险评分模型可以将患者分为高风险组和低风险组,在训练集和验证集上的生存率均有显著差异。ROC曲线在两组中显示出良好的生存预测性能。此外,根据基于lncRNA的风险评分和临床病理因素建立了预测 3 、 5 和 10 年OS的列线图。风险模型的预后准确性通过训练集和验证集中的判别和校准图得到证实。 结论: 我们建立了一个新的三种基于lncRNA的风险评分模型和列线图来预测CM的总生存期。提出的列线图可能为CM患者的个体化治疗提供信息。

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影响因子:0.96
发表时间:2020-01-01
DOI:10.1097/DAD.0000000000001459
作者列表:["Lang UE","Love NR","Cheung C","McCalmont TH","Kim J"]

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皮肤肿瘤方向

皮肤肿瘤是发生在皮肤的细胞增生性疾病,是一种常见病。发生于皮内或皮下组织的新生物,种类很多,临床上分良性肿瘤和恶性肿瘤。恶性肿瘤可以不断增殖,引起转移,威胁生命,称为皮肤癌。

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