Pan-cancer analysis identifies telomerase-associated signatures and cancer subtypes
Pan-cancer analysis identifies telomerase-associated signatures and cancer subtypes
复制标题
泛癌分析识别端粒酶相关特征和癌症亚型
DOI：
10.1186/s12943-019-1035-x
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发表时间：
2019-06-10
期刊：
影响因子：
37.3
通讯作者：
Xiong, Yuanyan
中科院分区：
文献类型：
--
作者：
Luo, Zhenhua;Wang, Weixu;Xiong, Yuanyan
背景癌细胞通过端粒维持机制（如端粒酶逆转录酶（telomerase reverse transcriptase，TERT）激活）而永生化.除了维持端粒长度外，TERT还激活多种细胞存活信号通路。然而，端粒酶相关的基因签名在cancer.MethodsWe进行了系统的分析端粒酶高（TERThigh）和低（TERTlow）癌症使用多维数据从癌症基因组图谱（TCGA）。多维数据采用倾向评分匹配权重算法进行分析。采用加权基因共表达网络分析法（WGCNA）构建共表达网络。生成随机森林分类器，以确定癌症subtype.ResultsThe TERThigh特异性mRNA表达签名与跨癌症类型的细胞周期相关的共表达模块。对细胞周期模块中枢纽基因的实验筛选表明TPX 2和EXO 1是端粒酶活性和细胞存活的潜在调节因子。miRNA分析显示，TERThigh特异性miR-17-92簇可以靶向TERTlow癌症中富集的生物过程，并且其表达与肿瘤/正常端粒长度比呈负相关。有趣的是，TERThighcancers倾向于在细胞外基质组织基因中发生突变，并放大MAPK信号。通过挖掘临床可操作基因数据库，我们发现了许多TERThigh特异性体细胞突变，扩增和含有治疗靶点的高表达基因。最后，一个随机森林分类整合端粒酶相关的多组学签名确定两种癌症亚型端粒酶活性和患者survival.ConclusionsIn总结，我们的研究结果描绘了端粒酶相关的分子景观在癌症中，并提供治疗癌症的机会。
BackgroundCancer cells become immortalized through telomere maintenance mechanisms, such as telomerase reverse transcriptase (TERT) activation. In addition to maintaining telomere length, TERT activates manifold cell survival signaling pathways. However, telomerase-associated gene signatures in cancer remain elusive.MethodsWe performed a systematic analysis of TERT high (TERThigh) and low (TERTlow) cancers using multidimensional data from The Cancer Genome Atlas (TCGA). Multidimensional data were analyzed by propensity score matching weight algorithm. Coexpression networks were constructed by weight gene coexpression network analysis (WGCNA). Random forest classifiers were generated to identify cancer subtypes.ResultsThe TERThigh-specific mRNA expression signature is associated with cell cycle-related coexpression modules across cancer types. Experimental screening of hub genes in the cell cycle module suggested TPX2 and EXO1 as potential regulators of telomerase activity and cell survival. MiRNA analysis revealed that the TERThigh-specific miR-17-92 cluster can target biological processes enriched in TERTlowcancer and that its expression is negatively correlated with the tumor/normal telomere length ratio. Intriguingly, TERThighcancers tend to have mutations in extracellular matrix organization genes and amplify MAPK signaling. By mining the clinical actionable gene database, we uncovered a number of TERThigh-specific somatic mutations, amplifications and high expression genes containing therapeutic targets. Finally, a random forest classifier integrating telomerase-associated multi-omics signatures identifies two cancer subtypes showed profound differences in telomerase activity and patient survival.ConclusionsIn summary, our results depict a telomerase-associated molecular landscape in cancers and provide therapeutic opportunities for cancer treatment.