Suppr超能文献

与肝细胞癌相关的预后和治疗性免疫特征的鉴定。

Identification of a prognostic and therapeutic immune signature associated with hepatocellular carcinoma.

作者信息

Peng Yanan, Liu Chang, Li Mengting, Li Wenjie, Zhang Mengna, Jiang Xiang, Chang Ying, Liu Lan, Wang Fan, Zhao Qiu

机构信息

Department of Gastroenterology, Zhongnan Hospital of Wuhan University, Wuhan, China.

Hubei Clinical Center and Key Lab of Intestinal and Colorectal Diseases, Wuhan, China.

出版信息

Cancer Cell Int. 2021 Feb 10;21(1):98. doi: 10.1186/s12935-021-01792-4.

Abstract

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most prevalent and inflammation-associated cancers. The tumor microenvironment (TME) plays an essential role in HCC development and metastasis, leading to poor prognosis. The overall TME immune cells infiltration characterizations mediated by immune-related genes (IRGs) remain unclear. In this study, we aimed to investigate whether immune-related genes could be indicators for the prognosis of HCC patients and TME cell infiltration characterization as well as responses to immunotherapy.

METHODS

We obtained differentially expressed immune-related genes (DE IRGs) between normal liver tissues and liver cancer tissues from The Cancer Genome Atlas (TCGA) database. To identify the prognostic genes and establish an immune risk signature, we performed univariable Cox regression survival analysis and the Least Absolute Shrinkage and Selector Operation (LASSO) regression based on the DE IRGs by robust rank aggregation method. Cox regression analysis was used to identify independent prognostic factors in HCC. We estimated the immune cell infiltration in TME via CIBERSORT and immunotherapy response through TIDE algorithm.

RESULTS

We constructed an immune signature and validated its predictive capability. The immune signature included 7 differentially expressed IRGs: BIRC5, CACYBP, NR0B1, RAET1E, S100A8, SPINK5, and SPP1. The univariate and multivariate cox analysis showed that the 7-IRGs signature was a robust independent prognostic factor in the overall survival of HCC patients. The 7-IRG signature was associated with some clinical features, including gender, vascular invasion, histological grade, clinical stage, T stage. We also found that the 7-IRG signature could reflect the infiltration characterization of different immunocytes in the tumor microenvironment (TME) and had a good correlation with immune checkpoint molecules, revealing that the poor prognosis might be partly due to immunosuppressive TME. The Tumour Immune Dysfunction and Exclusion (TIDE) analysis data showed that the 7-IRG signature had great potential for indicating the immunotherapy response in HCC patients. The mutation analysis demonstrated a significant difference in the tumor mutation burden (TMB) between the high- and low-risk groups, partially explaining this signature's predictive value.

CONCLUSION

In a word, we constructed and validated a novel, immune-related prognostic signature for HCC patients. This signature could effectively indicate HCC patients' survival and immunotherapy response. And it might act as potential immunotherapeutic targets for HCC patients.

摘要

背景

肝细胞癌(HCC)是最常见的与炎症相关的癌症之一。肿瘤微环境(TME)在HCC的发生和转移中起重要作用,导致预后不良。由免疫相关基因(IRGs)介导的整体TME免疫细胞浸润特征仍不清楚。在本研究中,我们旨在探讨免疫相关基因是否可作为HCC患者预后、TME细胞浸润特征以及免疫治疗反应的指标。

方法

我们从癌症基因组图谱(TCGA)数据库中获取了正常肝组织和肝癌组织之间差异表达的免疫相关基因(DE IRGs)。为了鉴定预后基因并建立免疫风险特征,我们基于DE IRGs通过稳健秩聚合方法进行单变量Cox回归生存分析和最小绝对收缩和选择算子(LASSO)回归。Cox回归分析用于确定HCC的独立预后因素。我们通过CIBERSORT估计TME中的免疫细胞浸润,并通过TIDE算法评估免疫治疗反应。

结果

我们构建了一个免疫特征并验证了其预测能力。该免疫特征包括7个差异表达的IRGs:BIRC5、CACYBP、NR0B1、RAET1E、S100A8、SPINK5和SPP1。单变量和多变量cox分析表明,7-IRGs特征是HCC患者总生存的一个稳健独立预后因素。7-IRG特征与一些临床特征相关,包括性别、血管侵犯、组织学分级、临床分期、T分期。我们还发现,7-IRG特征可以反映肿瘤微环境(TME)中不同免疫细胞的浸润特征,并且与免疫检查点分子有良好的相关性,揭示预后不良可能部分归因于免疫抑制性TME。肿瘤免疫功能障碍和排除(TIDE)分析数据表明,7-IRG特征在指示HCC患者免疫治疗反应方面具有很大潜力。突变分析表明高风险组和低风险组之间的肿瘤突变负担(TMB)存在显著差异,部分解释了该特征的预测价值。

结论

总之,我们构建并验证了一种针对HCC患者的新型免疫相关预后特征。该特征可以有效地指示HCC患者的生存和免疫治疗反应。并且它可能成为HCC患者潜在的免疫治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/226e/7877064/21fe15b04cd6/12935_2021_1792_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验