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The distinct clinical features and prognosis of the CD10+MUM1+ and CD10-Bcl6-MUM1- diffuse large B-cell lymphoma
被引:23
|作者:
Lu, Ting-Xun
[1
,2
]
Miao, Yi
[1
]
Wu, Jia-Zhu
[1
]
Gong, Qi-Xing
[3
]
Liang, Jin-Hua
[1
]
Wang, Zhen
[3
]
Wang, Li
[1
]
Fan, Lei
[1
]
Hua, Dong
[2
]
Chen, Yao-Yu
[1
]
Xu, Wei
[1
]
Zhang, Zhi-Hong
[3
]
Li, Jian-Yong
[1
,4
]
机构:
[1] Nanjing Med Univ, Jiangsu Prov Hosp, Dept Hematol, Affiliated Hosp 1, Nanjing 210029, Jiangsu, Peoples R China
[2] Jiangnan Univ, Dept Oncol, Affiliated Hosp, Wuxi 214062, Jiangsu, Peoples R China
[3] Nanjing Med Univ, Jiangsu Prov Hosp, Dept Pathol, Affiliated Hosp 1, Nanjing 210029, Jiangsu, Peoples R China
[4] Nanjing Med Univ, Collaborat Innovat Ctr Canc Personalized Med, Nanjing 210029, Jiangsu, Peoples R China
来源:
基金:
中国国家自然科学基金;
关键词:
GENE-EXPRESSION;
GERMINAL CENTER;
IMMUNOHISTOCHEMICAL BIOMARKERS;
PREDICT SURVIVAL;
OF-ORIGIN;
RITUXIMAB;
IMPACT;
CHEMOTHERAPY;
ALGORITHMS;
SUBTYPES;
D O I:
10.1038/srep20465
中图分类号:
O [数理科学和化学];
P [天文学、地球科学];
Q [生物科学];
N [自然科学总论];
学科分类号:
07 ;
0710 ;
09 ;
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 (CD10(-)Bcl6(-)MUM(-), 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 nonGCB 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.
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页数:10
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