Zhang Baohui, Tang Bufu, Lv Jiarui, Gao Jianyao, Qin Ling
Department of Physiology, School of Life Science, China Medical University, No. 77 Puhe Road, Shenyang North New Area, Shenyang, Liaoning Province 110122, PR China.
Departmcent of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310058, China.
Clin Immunol. 2022 Aug;241:109073. doi: 10.1016/j.clim.2022.109073. Epub 2022 Jul 9.
Tumor immune microenvironment (TIME) is of critical importance for the development and therapeutic response of hepatocellular carcinoma (HCC). However, limited studies have investigated immune-related indicators for clinical supervision and decision. The current study aimed to develop an improved prognostic signature based on TIME. HCC patients from TCGA and ICGC database were classified into three subtypes (Immunity High, Immunity Medium and Immunity Low) according to ssGSEA scores of 29 immune gene sets. Differentially expressed immune-related genes (DE IRGs) between Immune High and Low groups were screened with an adjusted P < 0.05. Weighted gene co-expression network analysis (WGCNA) was used to establish gene co-expression modules of differentially expressed genes (DEGs) between tumor and normal tissues. 45 survival-related immune genes (SRIGs) were identified at points of intersection between hub genes and DE IRGs. By performing Cox regression and LASSO analysis, 3 of the 45 SRIGs were screened to establish a prognostic model. Patients with high risk scores exhibited worse survival outcome and poorer response to chemotherapy. Potential mechanisms of chemotherapy resistance also have been discussed. More significantly, high -risk patients showed increased immune cell infiltration and checkpoints, which suggested a benefit of immunotherapy. In addition, knockdown of IGF2BP3 was determined to significantly inhibit cell proliferation and migration in HCC. Our immune-related model may be an effective tool for precise diagnosis and treatment of HCC. It may help to select patients suitable for chemotherapy, and immunotherapy.
肿瘤免疫微环境(TIME)对肝细胞癌(HCC)的发展和治疗反应至关重要。然而,目前很少有研究探讨免疫相关指标用于临床监测和决策。本研究旨在基于 TIME 构建一种改良的预后标志物。根据 29 个免疫基因集的 ssGSEA 评分,将 TCGA 和 ICGC 数据库中的 HCC 患者分为三组(免疫高、免疫中、免疫低)。采用调整后的 P 值<0.05 筛选免疫高组和免疫低组之间差异表达的免疫相关基因(DEIRGs)。采用加权基因共表达网络分析(WGCNA)鉴定肿瘤组织和正常组织之间差异表达基因(DEGs)的基因共表达模块。在枢纽基因和 DEIRGs 的交点处确定了 45 个与生存相关的免疫基因(SRIGs)。通过 Cox 回归和 LASSO 分析,筛选出 45 个 SRIGs 中的 3 个,构建预后模型。高风险评分患者的生存结局较差,对化疗的反应较差。还讨论了化疗耐药的潜在机制。更重要的是,高危患者表现出更高的免疫细胞浸润和检查点,这表明免疫治疗可能有益。此外,IGF2BP3 的敲低显著抑制 HCC 细胞的增殖和迁移。我们的免疫相关模型可能是 HCC 精确诊断和治疗的有效工具。它有助于选择适合化疗和免疫治疗的患者。