Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence.
Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence.
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竞争性内源性 RNA 网络的综合分析揭示了预测肝细胞癌复发的潜在生物标志物
DOI：
10.1186/s12885-021-08173-0
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发表时间：
2021-04-20
期刊：
影响因子：
3.8
通讯作者：
Wu Z
中科院分区：
文献类型：
--
作者：
Yan P;Huang Z;Mou T;Luo Y;Liu Y;Zhou B;Cao Z;Wu Z
肝细胞癌（Hepatocellular carcinoma，HCC）是世界上最常见、最致命的恶性肿瘤之一，复发率高。本研究旨在探讨HCC进展的潜在机制，并确定复发相关的生物标志物。我们首先分析了132例HCC患者的配对肿瘤和相邻的正常组织样本从基因表达综合数据库（GEO），以确定差异表达基因（DEG）。接下来分析来自癌症基因组图谱（TCGA）数据库的372名HCC患者的表达谱和临床信息，以进一步验证DEG，构建竞争性内源性RNA（ceRNA）网络并发现与复发相关的预后基因。最后，在两个外部队列中评估了几个复发相关基因，分别由52名和49名HCC患者组成。基于ceRNA假说的竞争关系，采用数据挖掘的综合策略，构建了两个潜在的相互作用的ceRNA网络。“上调的”ceRNA网络由6种上调的lncRNA、3种下调的miRNA和5种上调的mRNA组成，而“下调的”网络包括4种下调的lncRNA、12种上调的miRNA和67种下调的mRNA。对ceRNA网络中基因的生存分析表明，20种mRNA与无复发生存（RFS）显著相关。基于预测mRNA，采用最小绝对收缩和选择算子（LASSO）算法建立ADH 4、DNASE 1 L3、HGFAC和MELK四基因签名预测肝癌患者RFS，并通过受试者工作特征曲线评价其性能。该签名也在两个外部队列中得到验证，并显示出对HCC患者RFS的有效区分和预测。总之，本研究阐明了肿瘤发生和进展的潜在机制，提供了两个可视化的ceRNA网络，并成功地确定了几个潜在的生物标志物，用于HCC复发预测和靶向治疗。在线版本包含补充材料，可通过10.1186/s12885-021-08173-0获得。
Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers. We first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively. With the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The ‘upregulated’ ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the ‘downregulated’ network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients. In conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies. The online version contains supplementary material available at 10.1186/s12885-021-08173-0.
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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：
5.2
作者：
Han LL;Yin XR;Zhang SQ
通讯作者：
Zhang SQ
DOI：
10.1002/cjp2.37
发表时间：
2016-04
期刊：
The journal of pathology. Clinical research
影响因子：
--
作者：
Makowska Z;Boldanova T;Adametz D;Quagliata L;Vogt JE;Dill MT;Matter MS;Roth V;Terracciano L;Heim MH
通讯作者：
Heim MH
影响因子：
3.8
作者：
Liu X;Li T;Kong D;You H;Kong F;Tang R
通讯作者：
Tang R
影响因子：
4.1
作者：
Sun, Xiangjun;Ge, Xinfeng;Chen, Dongfeng
通讯作者：
Chen, Dongfeng