Lv Yufeng, Wei Wenhao, Huang Zhong, Chen Zhichao, Fang Yuan, Pan Lili, Han Xueqiong, Xu Zihai
Department of Medical Oncology, Affiliated Langdong Hospital of Guangxi Medical University, Nanning, China.
Department of Medical Oncology, The First People's Hospital of Nanning, Nanning, China.
Hepatol Res. 2018 Dec;48(13):1140-1148. doi: 10.1111/hepr.13220. Epub 2018 Jul 17.
The aim of this study was to develop a novel long non-coding RNA (lncRNA) expression signature to accurately predict early recurrence for patients with hepatocellular carcinoma (HCC) after curative resection.
Using expression profiles downloaded from The Cancer Genome Atlas database, we identified multiple lncRNAs with differential expression between early recurrence (ER) and non-early recurrence (non-ER) groups of patients with HCC. Least absolute shrinkage and selection operator for logistic regression models were used to develop an lncRNA-based classifier for predicting ER in the training set. An independent test set was used to validate the predictive value of this classifier. Furthermore, a co-expression network based on these lncRNAs and its highly related genes was constructed and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of genes in the network were carried out.
We identified 10 differentially expressed lncRNAs, including three that were upregulated and seven that were downregulated in the ER group. The lncRNA-based classifier was constructed based on seven lncRNAs (AL035661.1, PART1, AC011632.1, AC109588.1, AL365361.1, LINC00861, and LINC02084), and its accuracy was 0.83 in the training set, 0.87 in the test set, and 0.84 in the total set. Receiver operating characteristic curve analysis showed the area under the curve was 0.741 in the training set, 0.824 in the test set, and 0.765 in the total set. A functional enrichment analysis suggested that the genes highly related to four lncRNAs are involved in the immune system.
The expression profile of seven lncRNAs can effectively predict ER after surgical resection for HCC.
本研究旨在开发一种新型长链非编码RNA（lncRNA）表达特征，以准确预测肝细胞癌（HCC）患者根治性切除术后的早期复发。
利用从癌症基因组图谱数据库下载的表达谱，我们在HCC患者的早期复发（ER）组和非早期复发（非ER）组之间鉴定出多个差异表达的lncRNA。使用逻辑回归模型的最小绝对收缩和选择算子来开发基于lncRNA的分类器，用于预测训练集中的ER。使用独立测试集来验证该分类器的预测价值。此外，构建了基于这些lncRNA及其高度相关基因的共表达网络，并对网络中的基因进行了基因本体论和京都基因与基因组百科全书通路富集分析。
我们鉴定出10个差异表达的lncRNA，其中ER组中有3个上调，7个下调。基于7个lncRNA（AL035661.1、PART1、AC011632.1、AC109588.1、AL365361.1、LINC00861和LINC02084）构建了基于lncRNA的分类器，其在训练集中的准确率为0.83，在测试集中为0.87，在总集中为0.84。受试者工作特征曲线分析显示，训练集中曲线下面积为0.741，测试集中为0.824，总集中为0.765。功能富集分析表明，与4个lncRNA高度相关的基因参与免疫系统。
7个lncRNA的表达谱可有效预测HCC手术切除后的ER。
