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鉴定和建立一个四基因铁死亡签名预测弥漫性大 B 细胞淋巴瘤的总生存期。

Identification and Development of a 4-Gene Ferroptosis Signature Predicting Overall Survival for Diffuse Large B-Cell Lymphoma.

机构信息

Medical Big Data Research Center, Medical Innovation Research Division of PLA General Hospital, Beijing, P. R. China.

Intelligent Healthcare Team, Baidu Inc., Beijing, China.

出版信息

Technol Cancer Res Treat. 2023 Jan-Dec;22:15330338221147772. doi: 10.1177/15330338221147772.

Abstract

Diffuse large B-cell lymphoma (DLBCL) is a well-differentiated disease, which makes the diagnosis and therapeutic strategy a difficult problem. While ferroptosis, as an iron-dependent form of regulated cell death, it plays an important role in causing several types of cancer. This study is aimed at exploring the prognostic value of ferroptosis-related genes in DLBCL. In our study, mRNA expression and matching clinical data of DLBCL patients were derived from Gene Expression Omnibus (GEO) database. First, multivariate cox regression model and nomogram which can predict the DLBCL patients' prognosis were built and validated. The multigene signature was constructed and optimized by the least absolute shrinkage and selection operator (LASSO) cox regression model. Also, ferroptosis-related subtypes were developed by consistent cluster. Last but not least, we explored the association between categories of infiltrating immune cells and model genes' expression. Our results showed that 27 gene expressions were correlated with overall survival (OS) in the univariate cox regression analysis. A 4-gene signature was constructed through these genes to stratify patients into high-low risk groups using risk score derived from model (model 1:gene expression model). The OS of patients in the high-risk group was shorter than that of patients in the low-risk group in the TNM stage and clinically distinct subtypes (activated B cell [ABC], germinal center B cell [GCB]) ( < .001). Furthermore, it was shown that the risk score was an independent factor in clinical cox regression model for OS (model 2:clinical model) (HR>1,  < .010). Besides, in consistent cluster analysis, ferroptosis prognosis status was different among 3 subtypes. Moreover, the correlation analysis between 4-gene with immune cells showed dendritic cells may be significantly associated with DLBCL. This research constructed an innovative ferroptosis-related gene signature for prognostic estimation of DLBCL patients. Solutions targeting ferroptosis could be an important therapeutic intervention for DLBCL.

摘要

弥漫性大 B 细胞淋巴瘤 (DLBCL) 是一种分化良好的疾病,这使得诊断和治疗策略成为一个难题。铁死亡作为一种铁依赖性的细胞死亡形式,在引起多种类型的癌症方面发挥着重要作用。本研究旨在探讨铁死亡相关基因在 DLBCL 中的预后价值。

在本研究中,从基因表达综合数据库(GEO)中获取了 DLBCL 患者的 mRNA 表达和匹配的临床数据。首先,构建并验证了可以预测 DLBCL 患者预后的多变量 cox 回归模型和诺模图。通过最小绝对收缩和选择算子(LASSO)cox 回归模型构建和优化了多基因特征。此外,通过一致聚类开发了铁死亡相关亚型。最后,我们探讨了浸润免疫细胞的类别与模型基因表达之间的关系。

我们的研究结果表明,在单变量 cox 回归分析中,有 27 个基因的表达与总生存期(OS)相关。通过这些基因构建了一个 4 基因特征,通过模型(模型 1:基因表达模型)获得的风险评分将患者分为高-低风险组。在 TNM 分期和临床显著亚型(激活 B 细胞[ABC]、生发中心 B 细胞[GCB])中,高风险组患者的 OS 更短(<0.001)。此外,在临床 cox 回归模型中,风险评分是 OS 的独立因素(模型 2:临床模型)(HR>1,<0.010)。此外,在一致聚类分析中,铁死亡预后状态在 3 个亚型之间不同。此外,4 基因与免疫细胞的相关性分析表明树突状细胞可能与 DLBCL 显著相关。

本研究构建了一种创新的铁死亡相关基因特征,用于预测 DLBCL 患者的预后。针对铁死亡的治疗方法可能是 DLBCL 的一种重要治疗干预手段。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf5f/9926004/0e9357d30654/10.1177_15330338221147772-fig1.jpg

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