Department of General Surgery, Huashan Hospital, Fudan University, Shanghai 200040, China.
Key Laboratory of Whole-Period Monitoring and Precise Intervention of Digestive Cancer, Shanghai Municipal Health Commission (SMHC), Institute of Fudan-Minhang Academic Health System, Minhang Hospital, Fudan University, Shanghai 200437, China.
Int J Mol Sci. 2023 Feb 7;24(4):3324. doi: 10.3390/ijms24043324.
Among cancer-related deaths worldwide, hepatocellular carcinoma (HCC) ranks second. The hypervascular feature of most HCC underlines the importance of angiogenesis in therapy. This study aimed to identify the key genes which could characterize the angiogenic molecular features of HCC and further explore therapeutic targets to improve patients' prognosis. Public RNAseq and clinical data are from TCGA, ICGC, and GEO. Angiogenesis-associated genes were downloaded from the GeneCards database. Then, we used multi-regression analysis to generate a risk score model. This model was trained on the TCGA cohort (n = 343) and validated on the GEO cohort (n = 242). The predicting therapy in the model was further evaluated by the DEPMAP database. We developed a fourteen-angiogenesis-related gene signature that was distinctly associated with overall survival (OS). Through the nomograms, our signature was proven to possess a better predictive role in HCC prognosis. The patients in higher-risk groups displayed a higher tumor mutation burden (TMB). Interestingly, our model could group subsets of patients with different sensitivities to immune checkpoint inhibitors (ICIs) and Sorafenib. We also predicted that Crizotinib, an anti-angiogenic drug, might be more sensitive to these patients with high-risk scores by the DEPMAP. The inhibitory effect of Crizotinib in human vascular cells was obvious in vitro and in vivo. This work established a novel HCC classification based on the gene expression values of angiogenesis genes. Moreover, we predicted that Crizotinib might be more effective in the high-risk patients in our model.
在全球与癌症相关的死亡中,肝细胞癌 (HCC) 位居第二。大多数 HCC 的富血管特征强调了血管生成在治疗中的重要性。本研究旨在确定能够描述 HCC 血管生成分子特征的关键基因,并进一步探索治疗靶点以改善患者的预后。公共 RNAseq 和临床数据来自 TCGA、ICGC 和 GEO。血管生成相关基因从 GeneCards 数据库下载。然后,我们使用多回归分析生成风险评分模型。该模型在 TCGA 队列 (n=343) 上进行训练,并在 GEO 队列 (n=242) 上进行验证。模型中的预测治疗作用进一步通过 DEPMAP 数据库进行评估。我们开发了一个由 14 个与血管生成相关的基因组成的特征,该特征与总生存期 (OS) 明显相关。通过列线图,我们的特征被证明在 HCC 预后预测中具有更好的作用。高风险组的患者肿瘤突变负担 (TMB) 更高。有趣的是,我们的模型可以将具有不同免疫检查点抑制剂 (ICIs) 和索拉非尼敏感性的患者分组。我们还预测,通过 DEPMAP,一种抗血管生成药物克唑替尼可能对这些高风险评分的患者更敏感。克唑替尼在体外和体内对人血管细胞的抑制作用明显。这项工作基于血管生成基因的基因表达值建立了一种新的 HCC 分类方法。此外,我们预测克唑替尼在我们模型中的高风险患者中可能更有效。