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恶性细胞受体 - 配体亚型指导肝癌预后预测及个性化免疫治疗。

Malignant cell receptor-ligand subtypes guide the prediction of prognosis and personalized immunotherapy of liver cancer.

作者信息

Wu Junzheng, Wu Chuncheng, Cai Xianhui, Li Peipei, Lin Jianjun, Wang Fuqiang

机构信息

Xiamen Hospital of Traditional Chinese Medicine, Xiamen Hospital, Beijing University of Chinese Medicine, Xiamen, Fujian, China.

Xiamen Xianyue Hospital, Xiamen, Fujian, China.

出版信息

Aging (Albany NY). 2024 Jan 18;16(2):1712-1732. doi: 10.18632/aging.205453.

DOI:10.18632/aging.205453
PMID:38244584
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10866410/
Abstract

OBJECTIVE

Liver cancer is a prevalent disease with a dismal prognosis. The aim of the research is to identify subgroups based on malignant cell receptor ligand gene from single-cell RNA, which might lead to customized immunotherapy for patients with liver cancer.

METHODS

Based on scRNA-seq data, we identified the receptor-ligand genes associated with prognosis and classify patients into molecular subtypes by univariate Cox regression and consensus clustering. LASSO regression was performed to construct a prognostic model, which was validated in TCGA and ICGC datasets. Immune infiltration and prediction of immunotherapy response were analyzed using ssGSEA, ESTIMATE, TIDE, and TRS score calculation. Finally, qPCR and Western blot validation of key genes and protein levels in cell lines.

RESULTS

A risk model using 16-gene expression levels predicted liver cancer patients' prognosis. The RiskScore associated significantly with tumor clinical characteristics and immunity, integrated with clinicopathological features for survival prediction. Differential expression of SRXN1 was verified in hepatocellular carcinoma and normal liver cells.

CONCLUSION

Our study utilizes single-cell analysis to investigate the communication between malignant cells and other cell types, identifying molecular subtypes based on malignant cell receptor ligand genes, offering new insights for the development of personalized immunotherapy and prognostic prediction models.

摘要

目的

肝癌是一种常见疾病，预后不佳。本研究旨在基于单细胞RNA的恶性细胞受体配体基因识别亚组，这可能为肝癌患者带来定制化免疫治疗。

方法

基于scRNA-seq数据，我们识别出与预后相关的受体-配体基因，并通过单变量Cox回归和一致性聚类将患者分为分子亚型。进行LASSO回归以构建预后模型，并在TCGA和ICGC数据集中进行验证。使用ssGSEA、ESTIMATE、TIDE和TRS评分计算分析免疫浸润和免疫治疗反应预测。最后，对细胞系中的关键基因和蛋白水平进行qPCR和Western blot验证。

结果

使用16个基因表达水平的风险模型可预测肝癌患者的预后。风险评分与肿瘤临床特征和免疫显著相关，结合临床病理特征进行生存预测。SRXN1在肝癌细胞和正常肝细胞中的差异表达得到验证。

结论

我们的研究利用单细胞分析来研究恶性细胞与其他细胞类型之间的通讯，基于恶性细胞受体配体基因识别分子亚型，为个性化免疫治疗和预后预测模型的开发提供了新见解。

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Characterization of glycosylation regulator-mediated glycosylation modification patterns and tumor microenvironment infiltration in hepatocellular carcinoma.糖基化调节剂介导的糖基化修饰模式及肝细胞癌肿瘤微环境浸润的特征分析
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SOCS2-enhanced ubiquitination of SLC7A11 promotes ferroptosis and radiosensitization in hepatocellular carcinoma.
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