Han Li, Wang Maolong, Yang Yuling, Xu Hanlin, Wei Lili, Huang Xia
Department of Nursing, Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Department of Thoracic Surgery, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
J Clin Transl Hepatol. 2022 Feb 28;10(1):80-89. doi: 10.14218/JCTH.2020.00144. Epub 2021 May 18.
The prognosis of hepatocellular carcinoma (HCC) is extremely poor; therefore, there is an urgent need for novel prognostic molecular biomarkers of HCC. The current investigation utilized circular (circ)RNA-associated competing endogenous (ce)RNAs analysis in order to identify significant prognostic biomarkers of HCC.
CircRNAs and mRNAs that were differentially expressed between normal and HCC tissues were identified. Their respective functions were predicted with Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. A nomogram was used for model verification.
A ceRNA network composed of differentially expressed circRNAs and mRNAs was constructed. Significant hub nodes in the ceRNA network were hsa_circ_0004662, hsa_circ_0005735, hsa_circ_0006990, hsa_circ_0018403 and hsa_circ_0100609. By using this information, a prognostic risk assessment tool was developed based on the expressions of seven genes (PLOD2, TARS, RNF19B, CCT2, RAN, C5orf30 and MCM10). Furthermore, multivariate Cox regression analysis revealed risk and T-stage parameters as independent prognostic factors. The nomograms that were constructed from risk and T-stage groups were used to further assess the prediction of HCC patient survival rates. The nomogram, which consisted of risk and T-stage scores assessment models, was found to be an independent factor for predicting prognosis of HCC.
Five circRNAs, including hsa_circ_0004662, hsa_circ_0005735, hsa_circ_0006990, hsa_circ_0018403 and hsa_circ_0100609, that may play key roles in the progression of HCC were identified. Seven gene signatures were identified, which were associated with the aforementioned circRNAs, including PLOD2, TARS, RNF19B, CCT2, RAN, C5orf30 and MCM10, all of which were significant genes involved in the pathophysiology of HCC. These genes may be used as a prognosticating tool in HCC patients.
肝细胞癌（HCC）的预后极差；因此，迫切需要新的HCC预后分子生物标志物。本研究利用环状（circ）RNA相关的竞争性内源性（ce）RNA分析来识别HCC的重要预后生物标志物。
鉴定正常组织与HCC组织之间差异表达的circRNA和mRNA。通过基因本体论富集分析和京都基因与基因组百科全书富集分析预测它们各自的功能。使用列线图进行模型验证。
构建了一个由差异表达的circRNA和mRNA组成的ceRNA网络。ceRNA网络中的重要枢纽节点有hsa_circ_0004662、hsa_circ_0005735、hsa_circ_0006990、hsa_circ_0018403和hsa_circ_0100609。利用这些信息，基于7个基因（PLOD2、TARS、RNF19B、CCT2、RAN、C5orf30和MCM10）的表达开发了一种预后风险评估工具。此外，多因素Cox回归分析显示风险和T分期参数是独立的预后因素。由风险和T分期组构建的列线图用于进一步评估HCC患者生存率的预测。由风险和T分期评分评估模型组成的列线图被发现是预测HCC预后的独立因素。
鉴定出5种circRNA，包括hsa_circ_0004662、hsa_circ_0005735、hsa_circ_0006990、hsa_circ_0018403和hsa_circ_0100609，它们可能在HCC进展中起关键作用。鉴定出7个基因特征，它们与上述circRNA相关，包括PLOD2、TARS、RNF19B、CCT2、RAN、C5orf30和MCM10，所有这些都是参与HCC病理生理学的重要基因。这些基因可作为HCC患者的预后评估工具。
