Zhou Peng, Gao Shanshan, Hu Bin
Department of Pediatric, Maternal and Child Health Hospital, Zibo, China.
Department of Ultrasound, Zibo Forth People's Hospital, Zibo, China.
Evid Based Complement Alternat Med. 2022 Jul 31;2022:2417134. doi: 10.1155/2022/2417134. eCollection 2022.
This study aimed to investigate the immune landscape in hepatoblastoma (HB) based on deconvolution methods and identify a biomarkers panel for diagnosis based on a machine learning algorithm. Firstly, we identified 277 differentially expressed genes (DEGs) and differentiated and functionally identified the modules in DEGs. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and GO (gene ontology) were used to annotate these DEGs, and the results suggested that the occurrence of HB was related to DNA adducts, bile secretion, and metabolism of xenobiotics by cytochrome P450. We selected the top 10 genes for our final diagnostic panel based on the random forest tree method. Interestingly, TNFRSF19 and TOP2A were significantly down-regulated in normal samples, while other genes (TRIB1, MAT1A, SAA2-SAA4, NAT2, HABP2, CYP2CB, APOF, and CFHR3) were significantly down-regulated in HB samples. Finally, we constructed a neural network model based on the above hub genes for diagnosis. After cross-validation, the area under the ROC curve was close to 1 (AUC = 0.972), and the AUC of the validation set was 0.870. In addition, the results of single-sample gene-set enrichment analysis (ssGSEA) and deconvolution methods revealed a more active immune responses in the HB tissue. In conclusion, we have developed a robust biomarkers panel for HB patients.
本研究旨在基于反卷积方法研究肝母细胞瘤（HB）的免疫格局，并基于机器学习算法鉴定用于诊断的生物标志物面板。首先，我们鉴定了277个差异表达基因（DEG），并对DEG中的模块进行了区分和功能鉴定。使用京都基因与基因组百科全书（KEGG）分析和基因本体（GO）对这些DEG进行注释，结果表明HB的发生与DNA加合物、胆汁分泌以及细胞色素P450对外源生物的代谢有关。我们基于随机森林树方法为最终诊断面板选择了前10个基因。有趣的是，TNFRSF19和TOP2A在正常样本中显著下调，而其他基因（TRIB1、MAT1A、SAA2 - SAA4、NAT2、HABP2、CYP2CB、APOF和CFHR3）在HB样本中显著下调。最后，我们基于上述核心基因构建了用于诊断的神经网络模型。经过交叉验证，ROC曲线下面积接近1（AUC = 0.972），验证集的AUC为0.870。此外，单样本基因集富集分析（ssGSEA）和反卷积方法的结果显示HB组织中的免疫反应更为活跃。总之，我们为HB患者开发了一个强大的生物标志物面板。
