A novel five-lncRNA signature panel improves high-risk survival prediction in patients with cholangiocarcinoma.
A novel five-lncRNA signature panel improves high-risk survival prediction in patients with cholangiocarcinoma.
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新型五长链非编码RNA特征组可改善胆管癌患者的高风险生存预测
DOI：
10.18632/aging.202446
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发表时间：
2021-01-20
期刊：
影响因子：
--
通讯作者：
Chen G
中科院分区：
文献类型：
--
作者：
Xie X;Wang Y;Zhang S;Li J;Yu Z;Ding X;Ye L;Gong P;Zhu Q;Li J;Chen Z;Yao X;Du Z;Zeng Q;Chen H;Yang Z;Chen G
胆管癌（CCA）是一种生存率低的致命疾病。长链非编码RNA（lncRNA）表达谱作为潜在的预后生物标志物在肿瘤的发生、发展和不良预后中起关键作用。因此，早期检测特异性lncRNA预测CCA患者的预后对于提高患者的生存率具有重要意义。在目前的研究中，我们的目的是建立一个新的风险分层lncRNA签名面板在CCA。最初的lncRNA发现在癌症基因组图谱数据库（TCGA队列）中鉴定。采用考克斯回归分析建立lncRNA预测模型，并进行受试者工作特征（ROC）曲线分析，评价模型的特异性和敏感性。随后对来自温州医科大学第一附属医院的CCA患者（WMU队列）中的lncRNA签名进行独立验证。此外，通过使用Gene Ontology功能和京都百科全书基因和基因组途径富集分析，我们探索了预后lncRNA的潜在功能。最后，筛选了5种lncRNA（HULC; AL359715.5; AC006504.8; AC090114.2; AP00943.4），以建立与不良总生存期显著相关的预测模型（HR：4.879; 95%CI，1.587 -14.996;p=0.006）。该五-lncRNA特征模型在TCGA组群中显示出优异的准确性（AUC=0.938），并且还稳健地预测了验证WMU组群中的存活率（AUC=0.816）。功能富集分析表明，预后lncRNA主要与CCA相关的生物学过程。我们的数据建立了一种新的lncRNA签名模型，用于CCA风险分层和具有不良分子基因型的CCA患者的稳健识别。此外，还揭示了CCA的新的分子机制。
Cholangiocarcinoma (CCA) is a fatal disease with dismal survival rates. Long non-coding RNA (lncRNA) expression profiling as potential prognostic biomarkers play critical roles in tumor initiation, development, and poor prognosis. Identifying specific lncRNA to predict the prognosis of CCA patients in the early stages is very important for improving a patient’s survival. In the current study, we aimed to establish a novel risk-stratification lncRNA signature panel in CCA. The initial lncRNA discovery was identified in The Cancer Genome Atlas database (TCGA cohort). The Cox regression analysis was used to establish the lncRNA prognostic model and the receiver operating characteristic (ROC) curve analysis was performed to assess the specificity and sensitivity of the model. This was followed by independent validation of the lncRNA signature in the CCA patients from the First Affiliated Hospital of Wenzhou Medical University (WMU cohort). Furthermore, by using the Gene Ontology function and Kyoto Encyclopedia Gene and Genome pathway enrichment analysis, we explored the potential function of prognosis lncRNA. Finally, five lncRNA (HULC; AL359715.5; AC006504.8; AC090114.2; AP00943.4) were screened to establish the predictive model that significantly associated with poor overall survival(HR:4.879;95%CI,1.587-14.996;p=0.006). This five-lncRNA signature model showed excellent accuracy in the TCGA cohort (AUC=0.938), and also robustly predicted survival in the validation WMU cohort(AUC=0.816). Functional enrichment analysis suggested prognostic lncRNA was primarily associated with CCA-related biological processes. Our data established a novel lncRNA signature model for CCA risk-stratification and robust identification of CCA patients with poor molecular genotypes. Moreover, it revealed new molecular mechanisms of CCA.
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影响因子：
7
作者：
Harrow J;Frankish A;Gonzalez JM;Tapanari E;Diekhans M;Kokocinski F;Aken BL;Barrell D;Zadissa A;Searle S;Barnes I;Bignell A;Boychenko V;Hunt T;Kay M;Mukherjee G;Rajan J;Despacio-Reyes G;Saunders G;Steward C;Harte R;Lin M;Howald C;Tanzer A;Derrien T;Chrast J;Walters N;Balasubramanian S;Pei B;Tress M;Rodriguez JM;Ezkurdia I;van Baren J;Brent M;Haussler D;Kellis M;Valencia A;Reymond A;Gerstein M;Guigó R;Hubbard TJ
通讯作者：
Hubbard TJ
影响因子：
--
作者：
Lu, Xu;Zhou, Chuang;Zhai, Wenlong
通讯作者：
Zhai, Wenlong
影响因子：
2.3
作者：
Guro, Hanisah;Kim, Jin Won;Han, Ho-Seong
通讯作者：
Han, Ho-Seong
影响因子：
15.9
作者：
Samudio, Ismael;Harmancey, Romain;Andreeff, Michael
通讯作者：
Andreeff, Michael
影响因子：
29.4
作者：
Sia, Daniela;Villanueva, Augusto;Llovet, Josep M.
通讯作者：
Llovet, Josep M.