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一种用于改善胰腺导管腺癌预后预测的长链非编码RNA特征

A Long Non-coding RNA Signature to Improve Prognostic Prediction of Pancreatic Ductal Adenocarcinoma.

作者信息

Zhou Chenhao, Wang Shun, Zhou Qiang, Zhao Jin, Xia Xianghou, Chen Wanyong, Zheng Yan, Xue Min, Yang Feng, Fu Deliang, Yin Yirui, Atyah Manar, Qin Lunxiu, Zhao Yue, Bruns Christiane, Jia Huliang, Ren Ning, Dong Qiongzhu

机构信息

Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China.

Department of General Surgery, Huashan Hospital & Cancer Metastasis Institute, Fudan University, Shanghai, China.

出版信息

Front Oncol. 2019 Nov 8;9:1160. doi: 10.3389/fonc.2019.01160. eCollection 2019.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most aggressive solid malignant tumors worldwide. Increasing investigations demonstrate that long non-coding RNAs (lncRNAs) expression is abnormally dysregulated in cancers. It is crucial to identify and predict the prognosis of patients for the selection of further therapeutic treatment. PDAC lncRNAs abundance profiles were used to establish a signature that could better predict the prognosis of PDAC patients. The least absolute shrinkage and selection operator (LASSO) Cox regression model was applied to establish a multi-lncRNA signature in the TCGA training cohort ( = 107). The signature was then validated in a TCGA validation cohort ( = 70) and another independent Fudan cohort ( = 46). A five-lncRNA signature was constructed and it was significantly related to the overall survival (OS), either in the training or validation cohorts. Through the subgroup and Cox regression analyses, the signature was proven to be independent of other clinic-pathologic parameters. Receiver operating characteristic curve (ROC) analysis also indicated that our signature had a better predictive capacity of PDAC prognosis. Furthermore, ClueGO and CluePedia analyses showed that a number of cancer-related and drug response pathways were enriched in high risk groups. Identifying the five-lncRNA signature (RP11-159F24.5, RP11-744N12.2, RP11-388M20.1, RP11-356C4.5, CTC-459F4.9) may provide insight into personalized prognosis prediction and new therapies for PDAC patients.

摘要

胰腺导管腺癌(PDAC)仍然是全球最具侵袭性的实体恶性肿瘤之一。越来越多的研究表明,长链非编码RNA(lncRNAs)在癌症中的表达异常失调。识别和预测患者的预后对于选择进一步的治疗方案至关重要。利用PDAC的lncRNAs丰度谱建立了一个能够更好地预测PDAC患者预后的特征。应用最小绝对收缩和选择算子(LASSO)Cox回归模型在TCGA训练队列(n = 107)中建立了一个多lncRNA特征。然后在TCGA验证队列(n = 70)和另一个独立的复旦队列(n = 46)中对该特征进行验证。构建了一个包含五个lncRNA的特征,该特征在训练队列和验证队列中均与总生存期(OS)显著相关。通过亚组分析和Cox回归分析,证明该特征独立于其他临床病理参数。受试者工作特征曲线(ROC)分析也表明,我们构建的特征对PDAC预后具有更好的预测能力。此外,ClueGO和CluePedia分析表明,许多癌症相关和药物反应途径在高危组中富集。识别这五个lncRNA特征(RP11-159F24.5、RP11-744N12.2、RP11-388M20.1、RP11-356C4.5、CTC-459F4.9)可能为PDAC患者的个性化预后预测和新疗法提供思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e00/6857660/4e5ab7d8eb39/fonc-09-01160-g0001.jpg

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