Wu Wenqi, Wang Jinhuan, Jiang Yanan, Hu Xin, Tian Ye, Chen Long, Sun Huimeng, Li Yuhang, Liu Su, Lv Yangyang, Guo Jing, Xu Hong, Xing Donghui, Zhai Yixin, Tian Linyan, Li Cheng, He Xiang, Luo Kaiping, Pan Yuan, Zhao Zhigang
Department of Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, 300060, China.
Department of Medical Oncology, Tianjin First Central Hospital, School of Medicine. Nankai University, Tianjin, 300192, China.
J Cancer. 2023 Jan 22;14(3):403-416. doi: 10.7150/jca.80926. eCollection 2023.
The diffuse large B-cell lymphoma (DLBCL) is a heterogeneous lymphoma with a dismal outcome, due to approximately 40% patients will be relapsed or refractory to the standard therapy of rituximab plus cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP). Therefore, we need urgently to explore the approach to classify the risk of DLBCL patients accurately and accurately targeting therapy. The ribosome is a vital cellular organelle that is mainly responsible for translation mRNA into protein, moreover, more and more reports revealed that ribosome was associated with cellular proliferation and tumorigenesis. Therefore, our study aimed to construct a prognostic model of DLBCL patients using ribosome-related genes (RibGs). We screened differentially expressed RibGs between healthy donors' B cells and DLBCL patients' malignant B cells in GSE56315 dataset. Next, we performed analyses of univariate Cox regression, the least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses to establish the prognostic model consisting of 15 RibGs in GSE10846 training set. Then, we validated the model by a range of analyses including Cox regression, Kaplan-Meier survival, ROC curve, and nomogram in training and validation cohorts. The RibGs model showed a reliably predictive capability. We found the upregulated pathways in high-risk group most associated with innate immune reaction such as interferon response, complement and inflammatory responses. In addition, a nomogram including age, gender, IPI score and risk score was constructed to help explain the prognostic model. We also discovered the high-risk patients were more sensitive to some certain drugs. Finally, knocking out the NLE1 could inhibit the proliferation of DLBCL cell lines. As far as we know, it is the first time to predict the prognosis of DLBCL using the RibGs and give a new sight for DLBCL treatment. Importantly, the RibGs model could be acted as a supplementary to the IPI in classifying the risk of DLBCL patients.
弥漫性大B细胞淋巴瘤（DLBCL）是一种异质性淋巴瘤，预后不佳，因为约40%的患者会对利妥昔单抗联合环磷酰胺、阿霉素、长春新碱和泼尼松（R-CHOP）的标准治疗复发或难治。因此，我们迫切需要探索准确分类DLBCL患者风险并精准靶向治疗的方法。核糖体是一种重要的细胞器，主要负责将mRNA翻译成蛋白质，此外，越来越多的报道显示核糖体与细胞增殖和肿瘤发生有关。因此，我们的研究旨在使用核糖体相关基因（RibGs）构建DLBCL患者的预后模型。我们在GSE56315数据集中筛选了健康供体B细胞与DLBCL患者恶性B细胞之间差异表达的RibGs。接下来，我们进行了单变量Cox回归、最小绝对收缩和选择算子（LASSO）回归以及多变量Cox回归分析，以在GSE10846训练集中建立由15个RibGs组成的预后模型。然后，我们通过一系列分析，包括Cox回归、Kaplan-Meier生存分析、ROC曲线和列线图，在训练和验证队列中验证了该模型。RibGs模型显示出可靠的预测能力。我们发现高危组中上调的通路与先天免疫反应最相关，如干扰素反应、补体和炎症反应。此外，构建了一个包括年龄、性别、国际预后指数（IPI）评分和风险评分的列线图，以帮助解释预后模型。我们还发现高危患者对某些特定药物更敏感。最后，敲除NLE1可抑制DLBCL细胞系的增殖。据我们所知，这是首次使用RibGs预测DLBCL的预后，并为DLBCL治疗提供了新的视角。重要的是，RibGs模型可作为IPI在分类DLBCL患者风险方面的补充。
