首页> 美国卫生研究院文献>Scientific Reports >The distinct clinical features and prognosis of the CD10+MUM1+ and CD10−Bcl6−MUM1− diffuse large B-cell lymphoma
【2h】

The distinct clinical features and prognosis of the CD10+MUM1+ and CD10−Bcl6−MUM1− diffuse large B-cell lymphoma

机译:CD10 + MUM1 +和CD10-Bcl6-MUM1-弥漫性大B细胞淋巴瘤的独特临床特征和预后

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Using an immunohistochemistry (IHC) based method, diffuse large B-cell lymphoma (DLBCL) can be classified into germinal center B-cell (GCB) and non-GCB subtypes. However, the prognostic value of Hans algorithm was contradictory in the literature. Using IHC and fluorescence in situ hybridization, we analyzed the antibodies applied in Hans algorithm and other genetic factors in 601 DLBCL patients and prognostic value of Hans algorithm in 306 cases who were treated with chemoimmunotherapy. The results showed that patients with GCB subtype have better overall survival (OS) and progression-free survival (PFS) than non-GCB cases. However, to some extent, double positive (CD10+MUM1+, DP) and triple negative (CD10Bcl6MUM, TN) showed different clinical characteristics and prognosis to others that were assigned to the same cell-of-origin group. The DP group showed similar OS (median OS: both not reached, P = 0.3650) and PFS (median PFS: 47.0 vs. 32.7 months, P = 0.0878) with the non-GCB group while the TN group showed similar OS (median OS: both not reached, P = 0.9278) and PFS (median PFS: both not reached, P = 0.9420) with the GCB group. In conclusion, Recognition of specific entities in Hans algorithm could help us to accurately predict outcome of the patients and choose the best clinical management for them.
机译:使用基于免疫组织化学(IHC)的方法,弥散性大B细胞淋巴瘤(DLBCL)可以分为生发中心B细胞(GCB)和非GCB亚型。然而,汉斯算法的预后价值在文献中是矛盾的。使用IHC和荧光原位杂交,我们分析了Hans算法中应用的抗体和其他遗传因素在601例DLBCL患者中的应用以及306例化学免疫疗法治疗汉斯算法的预后价值。结果显示,与非GCB病例相比,GCB亚型患者具有更好的总体生存(OS)和无进展生存(PFS)。但是,在某种程度上,双阳性(CD10 + MUM1 + ,DP)和三阴性(CD10 - Bcl6 - (sup> MUM -,TN)与分配给同一起源细胞组的其他患者表现出不同的临床特征和预后。 DP组与非GCB组的OS相似(中位OS:均未达到,P = 0.3650)和PFS(PFS中位:47.0 vs. 32.7个月,P = 0.0878),而TN组显示相似的OS(中位OS) :GCB组均未达到,P = 0.9278)和PFS(中位PFS:均未达到,P = 0.9420)。总之,在Hans算法中识别特定实体可以帮助我们准确地预测患者的预后并为其选择最佳的临床治疗方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号