Identification and Validation of a Tumor Microenvironment-Related Gene Signature in Hepatocellular Carcinoma Prognosis.
Identification and Validation of a Tumor Microenvironment-Related Gene Signature in Hepatocellular Carcinoma Prognosis.
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肝细胞癌预后中肿瘤微环境相关基因特征的鉴定和验证
DOI：
10.3389/fgene.2021.717319
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发表时间：
2021
影响因子：
3.7
通讯作者：
Meng Z
中科院分区：
文献类型：
--
作者：
Huang C;Zhang C;Sheng J;Wang D;Zhao Y;Qian L;Xie L;Meng Z
背景：肝细胞癌（HCC）是一种典型的炎症相关恶性肿瘤，免疫耐受微环境复杂，预后较差。在本研究中，我们旨在构建一种用于 HCC 患者预后的新型免疫相关基因特征，探索肿瘤微环境 (TME) 细胞浸润特征和潜在机制。方法：分析了 TCGA-LIHC 数据集中总共 364 个具有随访信息的 HCC 样本，用于训练预后特征。进行基于 IRG 的最小绝对收缩和选择器操作 (LASSO) 回归，以识别预后基因并建立免疫风险特征。通过 CIBERSORT 方法估计 TME 中的免疫细胞浸润。进行基因集变异分析（GSVA）来比较低风险和高风险群体所涉及的生物学途径。此外，使用复旦大学附属肿瘤医院77例患者的HCC组织微阵列石蜡切片进行IHC染色。收集并总结了 77 例 HCC 患者的临床特征，通过 Kaplan-Meier (KM) 方法进行生存分析验证。结果：最终构建了免疫密切相关的三基因特征（风险评分= EPO * 0.02838 + BIRC5 * 0.02477 + SPP1 * 0.0002044），并被证明是HCC患者的有效预后因素。根据最佳截止值将患者分为高风险组和低风险组，生存分析显示，具有高风险免疫评分的 HCC 样本的预后显着差于低风险组（p < 0.0001）。 CIBERSORT的结果表明，低危组的免疫细胞活化相对较高，预后较好。此外，GSVA分析显示高危组和低危组之间存在多种信号传导差异，表明三基因预后模型可以通过影响免疫相关机制来影响患者的预后。组织微阵列（TMA）结果进一步证实HCC组织中3个基因的表达分别与患者的预后密切相关。结论：在本研究中，我们构建并验证了 HCC 中具有密切免疫相关性的稳健三基因特征，在预测 HCC 患者生存方面具有可靠的性能。
Background: Hepatocellular carcinoma (HCC) is a typical inflammatory-related malignant tumor with complex immune tolerance microenvironment and poor prognosis. In this study, we aimed to construct a novel immune-related gene signature for the prognosis of HCC patients, exploring tumor microenvironment (TME) cell infiltration characterization and potential mechanisms. Methods: A total of 364 HCC samples with follow-up information in the TCGA-LIHC dataset were analyzed for the training of the prognostic signature. The Least Absolute Shrinkage and Selector Operation (LASSO) regression based on the IRGs was conducted to identify the prognostic genes and establish an immune risk signature. The immune cell infiltration in TME was estimated via the CIBERSORT method. Gene Set Variation Analysis (GSVA) was conducted to compare the biological pathways involved in the low-risk and high-risk groups. Furthermore, paraffin sections of HCC tissue microarrays containing 77 patients from Fudan University Shanghai Cancer Center were used for IHC staining. The clinical characteristics of the 77 HCC patients were collected and summarized for survival analysis validation via the Kaplan–Meier (KM) method. Results: Three-gene signature with close immune correlation (Risk score = EPO * 0.02838 + BIRC5 * 0.02477 + SPP1 * 0.0002044) was constructed eventually and proven to be an effective prognostic factor for HCC patients. The patients were divided into a high-risk and a low-risk group according to the optimal cutoff, and the survival analysis revealed that HCC samples with high-risk immuno-score had significantly poorer outcomes than the low-risk group (p < 0.0001). The results of CIBERSORT suggested that the immune cell activation was relatively higher in the low-risk group with better prognosis. Besides, GSVA analysis showed multiple signaling differences between the high- and low-risk group, indicating that the three-gene prognostic model can affect the prognosis of patients by affecting immune-related mechanisms. Tissue microarray (TMA) results further confirmed that the expression of three genes in HCC tissues was closely related to the prognosis of patients, respectively. Conclusion: In this study, we constructed and validated a robust three-gene signature with close immune correlation in HCC, which presented a reliable performance in the prediction of HCC patients’ survival.
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影响因子：
81.5
作者：
Llovet, Josep M.;Zucman-Rossi, Jessica;Gores, Gregory
通讯作者：
Gores, Gregory
DOI：
10.4049/jimmunol.0901296
发表时间：
2010-12-01
期刊：
Journal of immunology (Baltimore, Md. : 1950)
影响因子：
--
作者：
Jones SC;Brahmakshatriya V;Huston G;Dibble J;Swain SL
通讯作者：
Swain SL
影响因子：
5.2
作者：
Jiang, Guangyi;Shi, Liang;Cai, Xiujun
通讯作者：
Cai, Xiujun
影响因子：
82.9
作者：
Binnewies M;Roberts EW;Kersten K;Chan V;Fearon DF;Merad M;Coussens LM;Gabrilovich DI;Ostrand-Rosenberg S;Hedrick CC;Vonderheide RH;Pittet MJ;Jain RK;Zou W;Howcroft TK;Woodhouse EC;Weinberg RA;Krummel MF
通讯作者：
Krummel MF
影响因子：
5.4
作者：
Hackl, Daniela;Loschko, Jakob;Krug, Anne B.
通讯作者：
Krug, Anne B.