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Systemic Analysis of the Prognosis-Related RNA Alternative Splicing Signals in Melanoma.

黑色素瘤预后相关RNA选择性剪接信号的系统分析。

  • 影响因子:2.03
  • DOI:10.12659/MSM.921133
  • 作者列表:"Xue D","Cheng P","Jiang J","Ren Y","Wu D","Chen W
  • 发表时间:2020-03-21
Abstract

:BACKGROUND Alternative splicing (AS), the mechanism underlying the occurrence of protein diversity, may result in cancer genesis and development when it becomes out of control, as suggested by a growing number of studies. However, systemically analyze of AS events at the genome-wide level for skin cutaneous melanoma (SKCM) is still in a preliminary phase. This study aimed to systemically analyze the bioinformatics of the AS events at a genome-wide level using The Cancer Genome Atlas (TCGA) SKCM data. MATERIAL AND METHODS The SpliceSeq tool was used to analyze the AS profiles for SKCM clinical specimens from the TCGA database. The association between AS events and overall survival was analyzed by Cox regression analysis. AS event intersections and a gene interaction network were established by UpSet plot. A multivariate survival model was used to establish a feature genes prognosis model. RESULTS A total of 103 SKCM patients with full clinical parameters available were included in this study. We established an AS network that investigated the relationship between AS events and clinical prognosis information. Furthermore, 4 underlying feature genes of SKCM (MCF2L, HARS, TFR2, and RALGPS1) were found in the AS network. We performed function analysis as well as correlation analysis of AS events with gene expression. Using the multivariate survival model, we further confirmed the 4 genes that impacted the classifying SKCM prognosis at the level of AS events as well as gene expression, especially in wild-type SKCM. CONCLUSIONS AS events could be ideal indicators for SKCM prognosis. The key feature gene MCF2L played an important role in wild-type SKCM.

摘要

背景选择性剪接 (AS) 是蛋白质多样性发生的潜在机制,如越来越多的研究表明,当它失去控制时,可能导致癌症的发生和发展。然而,在皮肤皮肤黑色素瘤 (SKCM) 的全基因组水平上系统分析AS事件仍处于初步阶段。本研究旨在利用癌症基因组图谱 (TCGA) SKCM数据在全基因组水平系统分析AS事件的生物信息学。材料和方法使用SpliceSeq工具分析TCGA数据库中SKCM临床标本的AS图谱。通过Cox回归分析AS事件与总生存率之间的相关性。作为事件交叉点和基因相互作用网络,通过打乱图建立起来。采用多变量生存模型建立特征基因预后模型。结果本研究共纳入 103 例具有完整临床参数的SKCM患者。我们建立了一个AS网络,研究AS事件与临床预后信息之间的关系。此外,在AS网络中发现了SKCM的 4 个潜在特征基因 (MCF2L、HARS、TFR2 和RALGPS1)。我们进行了功能分析以及as事件与基因表达的相关性分析。使用多变量生存模型,我们进一步证实了在AS事件水平以及基因表达水平上影响分类SKCM预后的 4 个基因,尤其是在野生型SKCM中。结论AS事件可能是SKCM预后的理想指标。关键特征基因MCF2L在野生型SKCM中发挥重要作用。

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影响因子:2.93
发表时间:2020-01-01
DOI:10.1016/j.jaad.2019.04.067
作者列表:["Pham CT","Juhasz M","Sung CT","Mesinkovska NA"]

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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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