Department of hepatobiliary surgery, The affiliated hospital of Guizhou medical university, Guiyang, Guizhou Province, China.
Department of Hepatobiliary Surgery, Jiangmen Central Hospital, Jiangmen, Guangdong Province, China.
J Clin Lab Anal. 2022 Jan;36(1):e24107. doi: 10.1002/jcla.24107. Epub 2021 Dec 6.
Metabolic disturbance is closely correlated with intrahepatic cholangiocarcinoma (IHCC), and we aimed to identify metabolic gene marker for the prognosis of IHCC.
We obtained expression and clinical data from 141 patients with IHCC from public databases. Prognostic metabolic genes were selected using univariate Cox regression analysis. Unsupervised cluster analysis was applied to identify IHCC subtypes, and CIBERSORT was used for immune infiltration analysis of different subtypes. Then, the metabolic gene signature was screened using multivariate Cox regression analysis and the LASSO algorithm. The prognostic potential and regulatory network of the metabolic gene signature were further investigated.
We screened 228 prognosis-related metabolic genes. Based on their expression levels, IHCC samples were divided into two subtypes, which showed significant differences in survival and immune cell infiltration. After LASSO analysis, eight metabolic genes including CYP19A1, SCD5, ACOT8, SRD5A3, MOGAT2, PFKFB3, PPARGC1B, and RPL17 were identified as the optimal genes for the prognosis signature. The prognostic model had excellent predictive abilities, with areas under the receiver-operating characteristic curves over 0.8. A nomogram model was also established based on two independent prognostic clinical factors (pathologic stage and prognostic model), and the generated calibration curves and c-indexes determined its excellent accuracy and discriminative ability to predict 1- and 5-year survival status (c-indexes>0.7). Finally, we found that miR-26a-5p, miR-27a-3p, and miR-27b-3p were the upstream regulators that mediate the involvement of gene signatures in metabolic pathways.
We developed eight metabolic gene signatures to predict IHCC prognosis and proposed potential upstream regulatory axes of gene signatures.
代谢紊乱与肝内胆管癌（IHCC）密切相关，本研究旨在确定代谢基因标志物用于预测 IHCC 的预后。
我们从公共数据库中获取了 141 例 IHCC 患者的表达和临床数据。使用单因素 Cox 回归分析筛选预后代谢基因。采用无监督聚类分析识别 IHCC 亚型，并使用 CIBERSORT 分析不同亚型的免疫浸润情况。然后，使用多因素 Cox 回归分析和 LASSO 算法筛选代谢基因特征。进一步研究代谢基因特征的预后潜力和调控网络。
我们筛选出 228 个与预后相关的代谢基因。根据这些基因的表达水平，将 IHCC 样本分为两个亚型，这两个亚型在生存和免疫细胞浸润方面存在显著差异。经过 LASSO 分析，确定了 CYP19A1、SCD5、ACOT8、SRD5A3、MOGAT2、PFKFB3、PPARGC1B 和 RPL17 这 8 个代谢基因作为预后特征的最佳基因。该预后模型具有良好的预测能力，ROC 曲线下面积超过 0.8。我们还基于两个独立的预后临床因素（病理分期和预后模型）建立了列线图模型，生成的校准曲线和 C 指数确定了其预测 1 年和 5 年生存状态的准确性和区分能力（C 指数>0.7）。最后，我们发现 miR-26a-5p、miR-27a-3p 和 miR-27b-3p 是调节基因特征参与代谢途径的上游调控因子。
我们开发了 8 个代谢基因特征来预测 IHCC 的预后，并提出了基因特征潜在的上游调控轴。
