Cai Dong, Zhao Zhibo, Hu Jiejun, Dai Xin, Zhong Guochao, Gong Jianping, Qi Feng
Department of Hepatobiliary Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Front Surg. 2022 Mar 22;9:836080. doi: 10.3389/fsurg.2022.836080. eCollection 2022.
Hepatocellular carcinoma (HCC) is one of the most prevalent malignant tumors with poor prognosis. Increasing evidence has revealed that immune cells and checkpoints in the tumor microenvironment (TME) and aging are associated with the prognosis of HCC. However, the association between aging and the tumor immune microenvironment (TIME) in HCC is still unclear.
RNA expression profiles and clinical data concerning HCC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Based on differentially expressed aging-related genes (DEAGs), unsupervised clustering was used to identify a novel molecular subtype in HCC. The features of immune cell infiltration and checkpoints were further explored through CIBERSORTx. Enrichment analysis and both univariate and multivariate Cox analyses were conducted to construct a 3-gene model for predicting prognosis and chemosensitivity. Finally, the mRNA and protein expression levels of the 3 genes were verified in HCC and other cancers through database searches and experiments.
Eleven differentially expressed AGs (GHR, APOC3, FOXM1, PON1, TOP2A, FEN1, HELLS, BUB1B, PPARGC1A, PRKDC, and H2AFX) correlated with the prognosis of HCC were used to divide HCC into two subtypes in which the prognosis was different. In cluster 2, which had a poorer prognosis, the infiltration of naive B cells and monocytes was lower in the TCGA and GEO cohorts, while the infiltration of M0 macrophages was higher. In addition, the TCGA cohort indicated that the microenvironment of cluster 2 had more immunosuppression through immune checkpoints. Enrichment analysis suggested that the MYC and E2F targets were positively associated with cluster 2 in the TCGA and GEO cohorts. Additionally, 3 genes (HMGCS2, SLC22A1, and G6PD) were screened to construct the prognostic model through univariate/multivariate Cox analysis. Then, the model was validated through the TCGA validation set and GEO dataset (GSE54236). Cox analysis indicated that the risk score was an independent prognostic factor and that patients in the high-risk group were sensitive to multiple targeted drugs (sorafenib, gemcitabine, rapamycin, etc.). Finally, significantly differential expression of the 3 genes was detected across cancers.
We systematically described the immune differences in the TME between the molecular subtypes based on AGs and constructed a novel three-gene signature to predict prognosis and chemosensitivity in patients with HCC.
肝细胞癌（HCC）是最常见的恶性肿瘤之一，预后较差。越来越多的证据表明，肿瘤微环境（TME）中的免疫细胞和检查点以及衰老与HCC的预后相关。然而，衰老与HCC肿瘤免疫微环境（TIME）之间的关联仍不清楚。
从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）下载有关HCC的RNA表达谱和临床数据。基于差异表达的衰老相关基因（DEAG），采用无监督聚类法在HCC中鉴定一种新的分子亚型。通过CIBERSORTx进一步探索免疫细胞浸润和检查点的特征。进行富集分析以及单因素和多因素Cox分析，构建一个用于预测预后和化疗敏感性的三基因模型。最后，通过数据库检索和实验验证这3个基因在HCC和其他癌症中的mRNA和蛋白表达水平。
11个与HCC预后相关的差异表达衰老基因（GHR、APOC3、FOXM1、PON1、TOP2A、FEN1、HELLS、BUB1B、PPARGC1A、PRKDC和H2AFX）被用于将HCC分为两种预后不同的亚型。在预后较差的2型聚类中，TCGA和GEO队列中的幼稚B细胞和单核细胞浸润较低，而M0巨噬细胞浸润较高。此外，TCGA队列表明，2型聚类的微环境通过免疫检查点具有更强的免疫抑制作用。富集分析表明，在TCGA和GEO队列中，MYC和E2F靶点与2型聚类呈正相关。此外，通过单因素/多因素Cox分析筛选出3个基因（HMGCS2、SLC22A1和G6PD）构建预后模型。然后，通过TCGA验证集和GEO数据集（GSE54236）对该模型进行验证。Cox分析表明，风险评分是一个独立的预后因素，高危组患者对多种靶向药物（索拉非尼、吉西他滨、雷帕霉素等）敏感。最后，在各种癌症中检测到这3个基因有显著差异表达。
我们系统地描述了基于衰老基因的分子亚型之间TME中的免疫差异，并构建了一种新的三基因特征来预测HCC患者的预后和化疗敏感性。
Zotero 插件
