Zhu Lixu, Guo Wenzhi
Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Key Laboratory of Hepatobiliary and Pancreatic Surgery and Digestive Organ Transplantation of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Front Cell Dev Biol. 2021 Aug 11;9:708819. doi: 10.3389/fcell.2021.708819. eCollection 2021.
Hepatocellular carcinoma (HCC) has the highest incidence and mortality of any malignancy in the world. Immunotherapy has been a major breakthrough for HCC treatment, but immune checkpoint inhibitors (ICIs) are effective in only a small percentage of HCC patients. In the present study, we screened programmed cell death protein 1 (PD-1) -negative HCC samples, which are frequently resistant to ICIs, and identified their methylation and transcription characteristics through the assessment of differential gene methylation and gene expression. We also screened for potential targeted therapeutic drugs using the DrugBank database. Finally, we used a LASSO (least absolute shrinkage and selection operator) regression analysis to construct a prognostic model based on three differentially methylated and expressed genes (DMEGs). The results showed that ESTIMATE (Estimation of Stromal and Immune Cells in Malignant Tumors using Expression Data) scores for the tumor samples were significantly lower compared to normal sample ESTIMATE scores. In addition, we identified 31 DMEGs that were able to distinguish PD-1-negative samples from normal samples. A functional enrichment analysis showed that these genes were involved in a variety of tumor-related pathways and immune-related pathways, and the DrugBank screening identified potential therapeutic drugs. Finally, the prognostic model based on three DMEGs (, , and ) demonstrated good predictive power for HCC prognosis and was verified using an independent cohort. The present study demonstrated the methylation characteristics of PD-1-negative HCC samples, identified several potential therapeutic drugs, and proposed a prognostic model based on , , and methylation expression. In conclusion, this work provides an in-depth understanding of methylation in HCC samples that are not sensitive to ICIs.
肝细胞癌（HCC）是全球所有恶性肿瘤中发病率和死亡率最高的。免疫疗法是HCC治疗的一项重大突破，但免疫检查点抑制剂（ICIs）仅对一小部分HCC患者有效。在本研究中，我们筛选了程序性细胞死亡蛋白1（PD-1）阴性的HCC样本（这些样本通常对ICIs耐药），并通过评估差异基因甲基化和基因表达来确定其甲基化和转录特征。我们还使用DrugBank数据库筛选潜在的靶向治疗药物。最后，我们使用最小绝对收缩和选择算子（LASSO）回归分析，基于三个差异甲基化和表达的基因（DMEGs）构建了一个预后模型。结果显示，与正常样本的ESTIMATE（使用表达数据估计恶性肿瘤中的基质和免疫细胞）评分相比，肿瘤样本的ESTIMATE评分显著更低。此外，我们鉴定出31个能够区分PD-1阴性样本与正常样本的DMEGs。功能富集分析表明，这些基因参与了多种肿瘤相关途径和免疫相关途径，并且DrugBank筛选确定了潜在的治疗药物。最后，基于三个DMEGs（ 、 和 ）的预后模型对HCC预后显示出良好的预测能力，并使用独立队列进行了验证。本研究展示了PD-1阴性HCC样本的甲基化特征，鉴定出几种潜在的治疗药物，并提出了基于 、 和 甲基化表达的预后模型。总之，这项工作为深入了解对ICIs不敏感的HCC样本中的甲基化情况提供了依据。
