A Co-Expression Network Reveals the Potential Regulatory Mechanism of lncRNAs in Relapsed Hepatocellular Carcinoma.
A Co-Expression Network Reveals the Potential Regulatory Mechanism of lncRNAs in Relapsed Hepatocellular Carcinoma.
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共表达网络揭示了lncRNA在复发性肝细胞癌中的潜在调控机制
DOI：
10.3389/fonc.2021.745166
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发表时间：
2021
影响因子：
4.7
通讯作者：
Huang H
中科院分区：
文献类型：
--
作者：
Fang Y;Yang Y;Zhang X;Li N;Yuan B;Jin L;Bao S;Li M;Zhao D;Li L;Zeng Z;Huang H
复发性肝细胞癌（HCC）的机制基础仍然知之甚少。最近的研究强调了长链非编码RNA（lncRNA）在HCC中的重要作用。然而，只有少数研究lncRNA与HCC复发之间的关联。使用edge R软件包分析GSE 101432数据集，鉴定原发性HCC组和复发性HCC组之间差异表达的lncRNA和mRNA。差异表达的lncRNA和mRNA用于构建lncRNA-mRNA共表达网络。对数据库进行加权基因共表达网络分析，然后进行基因本体论（GO）富集分析。此外，使用癌症基因组图谱数据库进行相关性和存活分析，并通过qRT-PCR验证临床样品中的表达。此后，我们将来自两组的基因输入TCGA的HCC TNM分期和肿瘤分级数据库。最后，我们对与复发HCC相关的lncRNA进行Kaplan-Meier生存分析。在这项研究中，确定了与HCC复发相关的lncRNA和mRNA。发现两个基因模块与此密切相关。黄色和黑色模块中的GO术语与细胞增殖、分化和存活以及一些与转录相关的生物过程有关。通过qRT-PCR，我们发现LINC 00941和LINC 00668在复发性HCC中的表达水平高于原发性HCC。此外，LOX、OTX 1、MICB、NDUFA 4L 2、BAIAP 2L 2和KCTD 17的mRNA水平与原发性HCC中的水平相比在复发性HCC中改变。此外，我们证实这些基因可以预测肝癌的总生存率和无复发生存率。此外，我们发现LINC 00668和LINC 00941可以影响肿瘤分级和TNM分期。总之，我们鉴定并验证了与HCC复发相关的两种lncRNA（LINC 00941和LINC 00668）和六种mRNA（LOX、MICB、OTX 1、BAIAP 2L 2、KCTD 17、NDUFA 4L 2）。总之，我们确定了与复发性HCC相关的关键基因模块和中心基因，并构建了与此相关的lncRNA-mRNA网络。这些基因可能对复发性HCC具有潜在的预后价值，并可能为复发性HCC的新生物标志物或诊断靶点提供新的线索。
The mechanistic basis for relapsed hepatocellular carcinoma (HCC) remains poorly understood. Recent research has highlighted the important roles of long non-coding RNAs (lncRNAs) in HCC. However, there are only a few studies on the association between lncRNAs and HCC relapse. Differentially expressed lncRNAs and mRNAs between a primary HCC group and relapsed HCC group were identified using the edge R package to analyze the GSE101432 dataset. The differentially expressed lncRNAs and mRNAs were used to construct a lncRNA–mRNA co-expression network. Weighted gene co-expression network analysis followed by Gene Ontology (GO) enrichment analyses were conducted on the database. Furthermore, correlation and survival analyses were performed using The Cancer Genome Atlas database, and expression in the clinical samples was verified by qRT-PCR. Thereafter, we inputted the genes from the two groups into the HCC TNM stage and tumor grade database from TCGA. Finally, we performed Kaplan–Meier survival analysis on the lncRNAs related to relapsed HCC. In this study, lncRNAs and mRNAs associated with HCC relapse were identified. Two gene modules were found to be closely linked to this. The GO terms in the yellow and black modules were related to cell proliferation, differentiation, and survival, as well as some transcription-related biological processes. Through qRT-PCR, we found that the expression levels of LINC00941 and LINC00668 in relapsed HCC were higher than those in primary HCC. Further, mRNA levels of LOX, OTX1, MICB, NDUFA4L2, BAIAP2L2, and KCTD17 were changed in relapsed HCC compared to levels in primary HCC. In addition, we verified that these genes could predict the overall survival and recurrence-free survival of HCC. Moreover, we found that LINC00668 and LINC00941 could affect tumor grade and TNM stages. In total, we identified and validated two lncRNAs (LINC00941 and LINC00668) and six mRNAs (LOX, MICB, OTX1, BAIAP2L2, KCTD17, NDUFA4L2) associated with HCC relapse. In summary, we identified the key gene modules and central genes associated with relapsed HCC and constructed lncRNA–mRNA networks related to this. These genes are likely to have potential prognostic value for relapsed HCC and might shed new light on novel biomarkers or diagnostic targets for relapsed HCC.
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赖氨酰氧化酶家族成员在肿瘤微环境和肝癌进展中的作用。
影响因子：
5.6
作者：
Lin HY;Li CJ;Yang YL;Huang YH;Hsiau YT;Chu PY
通讯作者：
Chu PY
影响因子：
254.7
作者：
Jemal, Ahmedin;Siegel, Rebecca;Thun, Michael J.
通讯作者：
Thun, Michael J.
DOI：
10.1016/j.omtn.2021.04.016
发表时间：
2021-09-03
期刊：
Molecular therapy. Nucleic acids
影响因子：
--
作者：
Qin M;Meng Y;Luo C;He S;Qin F;Yin Y;Huang J;Zhao H;Hu J;Deng Z;Qiu Y;Hu G;Pan H;Qin Z;Huang Z;Yi T
通讯作者：
Yi T
WGCNA：用于加权相关网络分析的 R 包。
影响因子：
3
作者：
Langfelder P;Horvath S
通讯作者：
Horvath S
影响因子：
4.5
作者：
Li H;Miao Q;Xu CW;Huang JH;Zhou YF;Wu MJ
通讯作者：
Wu MJ