Liu Chen, Liu Lin
Department of Hematology, First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Front Genet. 2022 Oct 14;13:1037716. doi: 10.3389/fgene.2022.1037716. eCollection 2022.
Due to the high heterogeneity of diffuse large B-cell lymphoma (DLBCL), traditional chemotherapy treatment ultimately failed in one-third of the patients. Big challenges existed in finding how to accurately predict prognosis and provide individualized treatment. Hypoxia, although being a key factor in the development and progression of DLBCL, plays its role in DLBCL prognosis, which has yet to be fully explored. Data used in the current study were sourced from the Gene Expression Omnibus (GEO) database. DLBCL patients were divided according to different hypoxia-related subtypes based on the expressions of hypoxia-related genes (HRGs) relevant to survival. Differentially expressed genes (DEGs) between subtypes were identified using the limma package. Using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses, the prognostic signature was established to calculate risk scores. The tumor microenvironment (TME) in low- and high-risk groups was evaluated by single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE. The chemotherapeutic sensitivity in two groups was assessed by IC50 values. DLBCL patients were clustered into two hypoxia-related subtype groups according to different gene survival and expressions associated with increasing oxygen delivery and reducing oxygen consumption, and these two subtype groups were compared. Based on the differential expression, a risk model was established using univariate cox and LASSO regression analyses, FNDC1, ANTXR1, RARRES2, S100A9, and MT1M. The performance of the risk signature in predicting the prognosis of DLBCL patients was validated in the internal and external datasets, as evidenced by receiver operating characteristic (ROC) curves. In addition, we observed significant differences in the tumor microenvironment and chemotherapeutic response between low- and high-risk groups. Our study developed novel hypoxia-related subtypes in DLBCL and identified five prognostic signatures for DLBCL patients. These findings may enrich our understanding of the role of hypoxia in DLBCL and help improve the treatment of DLBCL patients.
由于弥漫性大B细胞淋巴瘤（DLBCL）具有高度异质性，传统化疗最终有三分之一的患者治疗失败。在如何准确预测预后并提供个体化治疗方面存在巨大挑战。缺氧虽是DLBCL发生发展的关键因素，但其在DLBCL预后中的作用尚未得到充分探索。本研究使用的数据来自基因表达综合数据库（GEO）。根据与生存相关的缺氧相关基因（HRGs）表达，将DLBCL患者分为不同的缺氧相关亚型。使用limma软件包鉴定亚型之间的差异表达基因（DEGs）。通过单变量Cox回归和最小绝对收缩和选择算子（LASSO）分析，建立预后特征以计算风险评分。通过单样本基因集富集分析（ssGSEA）和ESTIMATE评估低风险和高风险组的肿瘤微环境（TME）。通过IC50值评估两组的化疗敏感性。根据与增加氧输送和减少氧消耗相关的不同基因生存和表达，将DLBCL患者聚类为两个缺氧相关亚型组，并对这两个亚型组进行比较。基于差异表达，使用单变量Cox和LASSO回归分析建立了一个风险模型，包括FNDC1、ANTXR1、RARRES2、S100A9和MT1M。风险特征在预测DLBCL患者预后方面的表现在内外部数据集中得到验证，如受试者操作特征（ROC）曲线所示。此外，我们观察到低风险和高风险组之间在肿瘤微环境和化疗反应方面存在显著差异。我们的研究在DLBCL中发现了新的缺氧相关亚型，并为DLBCL患者鉴定了五个预后特征。这些发现可能会丰富我们对缺氧在DLBCL中作用的理解，并有助于改善DLBCL患者的治疗。
