Tanabe Atsushi, Ndzinu Jerry, Sahara Hiroeki
Laboratory of Highly-Advanced Veterinary Medical Technology, Veterinary Teaching Hospital, Azabu University, 1-17-71 Fuchinobe Chuo-ku, Sagamihara 252-5201, Kanagawa, Japan.
Laboratory of Biology, Azabu University School of Veterinary Medicine, 1-17-71 Fuchinobe Chuo-ku, Sagamihara 252-5201, Kanagawa, Japan.
Int J Mol Sci. 2024 Nov 28;25(23):12807. doi: 10.3390/ijms252312807.
Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of non-Hodgkin's lymphoma. Because individual clinical outcomes of DLBCL in response to standard therapy differ widely, new treatment strategies are being investigated to improve therapeutic efficacy. In this study, we identified a novel signature for stratification of DLBCL useful for prognosis prediction and treatment selection. First, 408 prognostic gene sets were selected from approximately 2500 DLBCL samples in public databases, from which four gene-pair signatures consisting of seven prognostic genes were identified by Cox regression analysis. Then, the risk score was calculated based on these gene-pairs and we validated the risk score as a prognostic predictor for DLBCL patient outcomes. This risk score demonstrated independent predictive performance even when combined with other clinical parameters and molecular subtypes. Evaluating external DLBCL cohorts, we demonstrated that the risk-scoring model based the four gene-pair signatures leads to stable predictive performance, compared with nine existing predictive models. Finally, high-risk DLBCL showed high resistance to DNA damage caused by anticancer drugs, suggesting that this characteristic is responsible for the unfavorable prognosis of high-risk DLBCL patients. These results provide a novel index for classifying the biological characteristics of DLBCL and clearly indicate the importance of genetic analyses in the treatment of DLBCL.
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。由于DLBCL个体对标准治疗的临床反应差异很大,因此正在研究新的治疗策略以提高治疗效果。在本研究中,我们确定了一种用于DLBCL分层的新特征,可用于预后预测和治疗选择。首先,从公共数据库中约2500个DLBCL样本中选择408个预后基因集,通过Cox回归分析从中鉴定出由7个预后基因组成的4个基因对特征。然后,基于这些基因对计算风险评分,并将其验证为DLBCL患者预后的预测指标。即使与其他临床参数和分子亚型相结合,该风险评分仍显示出独立的预测性能。通过评估外部DLBCL队列,我们证明与9种现有的预测模型相比,基于4个基因对特征的风险评分模型具有稳定的预测性能。最后,高危DLBCL对抗癌药物引起的DNA损伤表现出高抗性,这表明该特征是高危DLBCL患者预后不良的原因。这些结果为DLBCL生物学特征的分类提供了一个新指标,并明确表明了基因分析在DLBCL治疗中的重要性。