构建用于预测肝细胞癌预后和免疫反应的免疫相关预后特征。

Constructing an immune-related prognostic signature for predicting prognosis and immune response in hepatocellular carcinoma.

作者信息

Cao Lichao, Huang Deliang, Zhang Shenrui, Li Zhiwei, Cai Qingxian, Chen Fang, Zhu Meilan, Ba Ying, Chen Jun, Zhang Hezi

机构信息

Shenzhen Nucleus Gene Technology Co., Ltd., 518071, Shenzhen, Guangdong Province, China.

Department of Liver Diseases, The Third People's Hospital of Shenzhen, The Second Affiliated Hospital of Southern University of Science and Technology, 518100, Shenzhen, Guangdong Province, China.

出版信息

Heliyon. 2024 Jul 3;10(13):e34012. doi: 10.1016/j.heliyon.2024.e34012. eCollection 2024 Jul 15.

DOI:10.1016/j.heliyon.2024.e34012

PMID:39071637

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11282973/

Abstract

BACKGROUND

Currently, there are few studies on immune-related prognostic analysis of hepatocellular carcinoma (HCC). Our aim was to establish an immune-correlated prognostic model for HCC.

METHODS

Immune-associated cells were obtained from the scRNA-seq dataset (GSE149614) of HCC. Differentially expressed genes between normal and tumor cells from immune-associated cells and the immune-related genes from the ImmPort database were used to identify immune-related differentially expressed genes (IRDEGs). Subsequently, the risk model was established in the TCGA-LIHC cohort (n = 438) from the Cancer Genome Atlas (TCGA) database by using Kaplan-Meier (K-M) survival curve, univariate/multivariate Cox regression analysis. Subsequently, we further analyzed tumor immune microenvironment characteristics, somatic mutation, immune checkpoint and its ligand expression levels between high- and low-risk groups, as well as drug sensitivity prediction. ICGC cohort was set as the validation cohort. TCGA-LIHC cohort and three independent the Gene Expression Omnibus (GEO) datasets (GSE54236, GSE14520, and GSE64041) was used to verify IRDEGs expression, as well as PCR assays using clinical samples.

RESULTS

The IRDEGs was composed of 4 genes, namely B2M, SPP1, PPIA, and HRG. The 438 HCC patients were divided into high- and low-risk group. The high-risk group was associated with poor prognosis, including higher T stage, advanced pathological stages, less immune cell infiltration, higher TP53 mutation rate, the high expression of CTLA4 and HAVCR2. Besides, high-risk populations benefit from most chemotherapy drugs. Similarly, the performance of the risk model was validated in the ICGC. All four datasets (TCGA-LIHC cohort, GSE54236, GSE14520, and GSE64041) and clinical q-PCR results demonstrated that, compared with normal samples, the expressions of B2M and HRG were lower in tumor samples, and the expression of SPP1 was higher.

CONCLUSION

In summary, the immune-related prognostic signature had a good predictive performance on prognosis and immunotherapy for HCC patients.

摘要

背景

目前，关于肝细胞癌（HCC）免疫相关预后分析的研究较少。我们的目的是建立一种HCC的免疫相关预后模型。

方法

从HCC的单细胞RNA测序数据集（GSE149614）中获取免疫相关细胞。利用免疫相关细胞中正常细胞与肿瘤细胞之间的差异表达基因以及来自ImmPort数据库的免疫相关基因来鉴定免疫相关差异表达基因（IRDEGs）。随后，通过Kaplan-Meier（K-M）生存曲线、单因素/多因素Cox回归分析，在来自癌症基因组图谱（TCGA）数据库的TCGA-LIHC队列（n = 438）中建立风险模型。随后，我们进一步分析了高风险组和低风险组之间的肿瘤免疫微环境特征、体细胞突变、免疫检查点及其配体表达水平，以及药物敏感性预测。ICGC队列被设为验证队列。使用TCGA-LIHC队列和三个独立的基因表达综合数据库（GEO）数据集（GSE54236、GSE14520和GSE64041）来验证IRDEGs的表达，以及使用临床样本进行PCR检测。

结果

IRDEGs由4个基因组成，即B2M、SPP1、PPIA和HRG。438例HCC患者被分为高风险组和低风险组。高风险组与预后不良相关，包括更高的T分期、晚期病理分期、更少的免疫细胞浸润、更高的TP53突变率、CTLA4和HAVCR2的高表达。此外，高风险人群从大多数化疗药物中获益。同样，风险模型的性能在ICGC中得到验证。所有四个数据集（TCGA-LIHC队列、GSE54236、GSE14520和GSE64041）以及临床q-PCR结果表明，与正常样本相比，肿瘤样本中B2M和HRG的表达较低，而SPP1的表达较高。