Integrative analyses of a mitophagy-related gene signature for predicting prognosis in patients with uveal melanoma.
Integrative analyses of a mitophagy-related gene signature for predicting prognosis in patients with uveal melanoma.
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用于预测葡萄膜黑色素瘤患者预后的线粒体自噬相关基因特征的综合分析
DOI：
10.3389/fgene.2022.1050341
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发表时间：
2022
影响因子：
3.7
通讯作者：
中科院分区：
文献类型：
--
作者：
我们的目的是通过基因表达谱的数据挖掘来建立一个线粒体自噬相关的风险模型，以预测葡萄膜黑色素瘤（UM）的预后，并开发一种新的方法来改善临床结果的预测。与临床信息一起，从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）收集RNA-seq和微阵列数据。使用ApproximsusosterPlus检测线粒体自噬相关亚组。单因素考克斯回归分析发现线粒体自噬相关基因，并与UM预后相关。在外部人群中，使用最小绝对收缩和选择算子（LASSO）回归构建并验证线粒体自噬风险体征。采用生存研究和受试者工作特征曲线（ROC）分析的数据评价模型的性能，并采用自助法对模型进行检验。检查功能富集和免疫浸润。使用6个线粒体自噬相关基因（ATG 12、CSNK 2B、MTERF 3、TOMM 5、TOMM 40和TOMM 70）建立风险模型，并将UM患者分为低风险和高风险亚组。高风险组的患者比低风险组的患者生存时间更长的机会更低（p < 0.001）。ROC测试表明签名的准确性。此外，预后诺模图和校准图，其中包括线粒体自噬信号，具有较高的预测性能，和风险模型与免疫浸润的控制密切相关。此外，功能富集分析表明，几种线粒体自噬亚型可能与癌症，线粒体代谢和免疫控制信号通路有关。我们开发的线粒体自噬相关风险模型可用于预测UM的临床结局，并强调线粒体自噬相关基因作为UM前瞻性治疗选择的参与。此外，我们的研究强调了线粒体自噬在UM中的重要作用。
We aimed to create a mitophagy-related risk model via data mining of gene expression profiles to predict prognosis in uveal melanoma (UM) and develop a novel method for improving the prediction of clinical outcomes. Together with clinical information, RNA-seq and microarray data were gathered from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. ConsensusClusterPlus was used to detect mitophagy-related subgroups. The genes involved with mitophagy, and the UM prognosis were discovered using univariate Cox regression analysis. In an outside population, a mitophagy risk sign was constructed and verified using least absolute shrinkage and selection operator (LASSO) regression. Data from both survival studies and receiver operating characteristic (ROC) curve analyses were used to evaluate model performance, a bootstrap method was used test the model. Functional enrichment and immune infiltration were examined. A risk model was developed using six mitophagy-related genes (ATG12, CSNK2B, MTERF3, TOMM5, TOMM40, and TOMM70), and patients with UM were divided into low- and high-risk subgroups. Patients in the high-risk group had a lower chance of living longer than those in the low-risk group (p < 0.001). The ROC test indicated the accuracy of the signature. Moreover, prognostic nomograms and calibration plots, which included mitophagy signals, were produced with high predictive performance, and the risk model was strongly associated with the control of immune infiltration. Furthermore, functional enrichment analysis demonstrated that several mitophagy subtypes may be implicated in cancer, mitochondrial metabolism, and immunological control signaling pathways. The mitophagy-related risk model we developed may be used to anticipate the clinical outcomes of UM and highlight the involvement of mitophagy-related genes as prospective therapeutic options in UM. Furthermore, our study emphasizes the essential role of mitophagy in UM.
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影响因子：
14.9
作者：
Ritchie ME;Phipson B;Wu D;Hu Y;Law CW;Shi W;Smyth GK
通讯作者：
Smyth GK
影响因子：
2.9
作者：
HELLERHARRISON, RA;MEISNER, H;CZECH, MP
通讯作者：
CZECH, MP
影响因子：
6
作者：
Pitt AS;Buchanan SK
通讯作者：
Buchanan SK
影响因子：
5.3
作者：
Melin, Jonathan;Schuiz, Christian;Rehling, Peter
通讯作者：
Rehling, Peter
影响因子：
3.8
作者：
Fei, Xifeng;Xie, Xiangtong;Qin, Ruwei;Wang, Anqi;Meng, Xuan;Sun, Fei;Zhao, Yifan;Jiang, Dongyi;Chen, Hanchun;Huang, Qiang;Ji, Xiaoyan;Wang, Zhimin
通讯作者：
Wang, Zhimin