Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, Jiangsu 210009, P.R. China.
Department of Obstetrics and Gynecology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, P.R. China.
Mol Med Rep. 2018 Jun;17(6):7845-7858. doi: 10.3892/mmr.2018.8846. Epub 2018 Apr 5.
Cervical cancer (CC) is a common gynecological malignancy in women worldwide. Using an RNA sequencing profile from The Cancer Genome Atlas (TCGA) and the CC patient information, the aim of the present study was to identify potential long non‑coding RNA (lncRNA) biomarkers of CC using bioinformatics analysis and building a competing endogenous RNA (ceRNA) co‑expression network. Results indicated several CC‑specific lncRNAs, which were associated with CC clinical information and selected some of them for validation and evaluated their diagnostic values. Bioinformatics analysis identified 51 CC‑specific lncRNAs (fold‑change >2 and P<0.05), and 42 of these were included in ceRNA network consisting of lncRNA‑miRNA‑mRNA interactions. Further analyses revealed that differential expression levels of 19 lncRNAs were significantly associated with different clinical features (P<0.05). A total of 11 key lncRNAs in the ceRNA network for reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR) analysis to detect their expression levels in 31 pairs of CC clinical samples. The results indicated that 7 lncRNAs were upregulated and 4 lncRNAs were downregulated in CC patients. The fold‑changes between the RT‑qPCR experiments and the TCGA bioinformatics analyses were the same. Furthermore, the area under the receiver operating characteristic (ROC) curve of four lncRNAs (EMX20S, MEG3, SYS1‑DBNDD2 and MIR9‑3HG) indicated that their combined use may have a significant diagnostic value in CC (P<0.05). To the best of our knowledge, the present study is the first to have identified CC‑specific lncRNAs to construct a ceRNA network and has also provided new insights for further investigation of a lncRNA‑associated ceRNA network in CC. In additon, the verification results suggested that the method of bioinformatics analysis and screening of lncRNAs was accurate and reliable. To conclude, the use of multiple lncRNAs may thus improve diagnostic efficacy in CC. In addition, these specific lncRNAs may serve as new candidate biomarkers for clinical diagnosis, classification and prognosis of CC.
宫颈癌（CC）是全球女性中常见的妇科恶性肿瘤。本研究通过使用来自癌症基因组图谱（TCGA）的 RNA 测序谱和 CC 患者信息，旨在通过生物信息学分析和构建竞争性内源性 RNA（ceRNA）共表达网络，鉴定 CC 的潜在长非编码 RNA（lncRNA）生物标志物。结果表明了一些与 CC 临床信息相关的 CC 特异性 lncRNA，并选择其中一些进行验证，并评估其诊断价值。生物信息学分析确定了 51 个 CC 特异性 lncRNA（fold-change >2 和 P<0.05），其中 42 个包含在 lncRNA-miRNA-mRNA 相互作用的 ceRNA 网络中。进一步分析表明，19 个 lncRNA 的差异表达水平与不同的临床特征显著相关（P<0.05）。在 ceRNA 网络中，共有 11 个关键 lncRNA 进行逆转录-定量聚合酶链反应（RT-qPCR）分析，以检测其在 31 对 CC 临床样本中的表达水平。结果表明，7 个 lncRNA 在 CC 患者中上调，4 个 lncRNA 下调。RT-qPCR 实验与 TCGA 生物信息学分析之间的倍数变化相同。此外，四个 lncRNA（EMX20S、MEG3、SYS1-DBNDD2 和 MIR9-3HG）的接收器工作特征（ROC）曲线下面积表明，它们的联合使用在 CC 中可能具有显著的诊断价值（P<0.05）。据我们所知，本研究首次鉴定了 CC 特异性 lncRNA 以构建 ceRNA 网络，并为进一步研究 CC 中 lncRNA 相关 ceRNA 网络提供了新的见解。此外，验证结果表明，lncRNA 的生物信息学分析和筛选方法准确可靠。总之，使用多个 lncRNA 可以提高 CC 的诊断效果。此外，这些特定的 lncRNA 可能成为 CC 临床诊断、分类和预后的新候选生物标志物。
