运用生物信息学技术分析多种细胞死亡相关基因在弥漫性大B细胞淋巴瘤中的作用。

Analyzing the involvement of diverse cell death-related genes in diffuse large B-cell lymphoma using bioinformatics techniques.

作者信息

Feng Heyuan, Zhang Xiyuan, Kang Jian

机构信息

Flow Cytometry Room, Beijing Gaobo Boren Hospital, Beijing, China.

Department of Blood Transfusion, No.970 Hospital of PLA Joint Logistics Support Force, Shandong, China.

出版信息

Heliyon. 2024 May 7;10(10):e30831. doi: 10.1016/j.heliyon.2024.e30831. eCollection 2024 May 30.

Abstract

Diffuse large B-cell lymphoma (DLBCL) stands as the most prevalent subtype of non-Hodgkin's lymphoma and exhibits significant heterogeneity. Various forms of programmed cell death (PCD) have been established to have close associations with tumor onset and progression. To this end, this study has compiled 16 PCD-related genes. The investigation delved into genes linked with prognosis, constructing risk models through consecutive application of univariate Cox regression analysis and Lasso-Cox regression analysis. Furthermore, we employed RT-qPCR to validate the mRNA expression levels of certain diagnosis-related genes. Subsequently, the models underwent validation through KM survival curves and ROC curves, respectively. Additionally, nomogram models were formulated employing prognosis-related genes and risk scores. Lastly, disparities in immune cell infiltration abundance and the expression of immune checkpoint-associated genes between high- and low-risk groups, as classified by risk models, were explored. These findings contribute to a more comprehensive understanding of the role played by the 16 PCD-associated genes in DLBCL, shedding light on potential novel therapeutic strategies for the condition.

摘要

弥漫性大B细胞淋巴瘤(DLBCL)是非霍奇金淋巴瘤最常见的亚型,具有显著的异质性。各种形式的程序性细胞死亡(PCD)已被证实与肿瘤的发生和进展密切相关。为此,本研究收集了16个与PCD相关的基因。该研究深入探讨了与预后相关的基因,通过连续应用单变量Cox回归分析和Lasso-Cox回归分析构建风险模型。此外,我们采用RT-qPCR验证了某些诊断相关基因的mRNA表达水平。随后,分别通过KM生存曲线和ROC曲线对模型进行验证。此外,利用与预后相关的基因和风险评分建立了列线图模型。最后,探讨了根据风险模型分类的高风险组和低风险组之间免疫细胞浸润丰度和免疫检查点相关基因表达的差异。这些发现有助于更全面地了解16个与PCD相关的基因在DLBCL中的作用,为该疾病潜在的新治疗策略提供线索。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7db3/11108851/550949586447/gr1.jpg

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