Construction of a risk score prognosis model based on hepatocellular carcinoma microenvironment
Construction of a risk score prognosis model based on hepatocellular carcinoma microenvironment
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基于肝癌微环境的风险评分预后模型构建
DOI：
10.3748/wjg.v26.i2.134
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发表时间：
2020-01-14
影响因子：
4.3
通讯作者：
Liu, Chao
中科院分区：
文献类型：
--
作者：
Zhang, Fa-Peng;Huang, Yi-Pei;Liu, Chao
背景：肝细胞癌（HCC）是一种常见的预后较差的癌症。既往研究表明，肿瘤微环境（tumor microenvironment， TME）在HCC的进展、复发和转移中起重要作用，导致预后不良。然而，TME相关基因对HCC患者预后的影响尚不清楚。在这里，我们研究了HCC微环境，以确定HCC的预后基因。目的寻找与HCC微环境相关的稳健基因标记，以提高HCC的预后预测。方法基于ESTIMATE算法计算肝癌患者的免疫/间质评分。此外，基于高和低免疫/基质评分患者之间的差异表达基因（DEGs）建立了风险评分模型。结果构建了由8个基因组成的HCC风险评分模型，并在HCC患者中得到验证。患者被分为高危组和低危组。我们的风险评分模型中涉及的基因（Disabled homolog 2、Musculin、C-X-C基序趋化因子配体8、Galectin 3、b细胞活化转录因子、杀伤细胞凝集素样受体B1、Endoglin和大肠腺瘤病肿瘤抑制因子）被认为是潜在的免疫治疗靶点，它们联合使用可能会提供更好的效果。功能富集分析显示，免疫应答和T细胞受体信号通路分别是高、低危组DEGs中与免疫相关基因相关的主要功能和途径。受试者工作特征（ROC）曲线分析证实了风险评分预后模型的良好效力。此外，我们使用国际癌症基因组联盟和基因表达综合数据库验证了风险评分模型。建立了一个nomogram来预测HCC患者的总生存期。结论肝癌风险评分模型和nomogram个体化免疫治疗将有利于肝癌患者。
BACKGROUND Hepatocellular carcinoma (HCC) is a common cancer with a poor prognosis. Previous studies revealed that the tumor microenvironment (TME) plays an important role in HCC progression, recurrence, and metastasis, leading to poor prognosis. However, the effects of genes involved in TME on the prognosis of HCC patients remain unclear. Here, we investigated the HCC microenvironment to identify prognostic genes for HCC. AIM To identify a robust gene signature associated with the HCC microenvironment to improve prognosis prediction of HCC. METHODS We computed the immune/stromal scores of HCC patients obtained from The Cancer Genome Atlas based on the ESTIMATE algorithm. Additionally, a risk score model was established based on Differentially Expressed Genes (DEGs) between high‐ and low‐immune/stromal score patients. RESULTS The risk score model consisting of eight genes was constructed and validated in the HCC patients. The patients were divided into high- or low-risk groups. The genes (Disabled homolog 2, Musculin, C-X-C motif chemokine ligand 8, Galectin 3, B-cell-activating transcription factor, Killer cell lectin like receptor B1, Endoglin and adenomatosis polyposis coli tumor suppressor) involved in our risk score model were considered to be potential immunotherapy targets, and they may provide better performance in combination. Functional enrichment analysis showed that the immune response and T cell receptor signaling pathway represented the major function and pathway, respectively, related to the immune-related genes in the DEGs between high- and low-risk groups. The receiver operating characteristic (ROC) curve analysis confirmed the good potency of the risk score prognostic model. Moreover, we validated the risk score model using the International Cancer Genome Consortium and the Gene Expression Omnibus database. A nomogram was established to predict the overall survival of HCC patients. CONCLUSION The risk score model and the nomogram will benefit HCC patients through personalized immunotherapy.