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

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...

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Autores principales: Lu, Ting-Xun, Miao, Yi, Wu, Jia-Zhu, Gong, Qi-Xing, Liang, Jin-Hua, Wang, Zhen, Wang, Li, Fan, Lei, Hua, Dong, Chen, Yao-Yu, Xu, Wei, Zhang, Zhi-Hong, Li, Jian-Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4746587/
https://www.ncbi.nlm.nih.gov/pubmed/26857366
http://dx.doi.org/10.1038/srep20465
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author Lu, Ting-Xun
Miao, Yi
Wu, Jia-Zhu
Gong, Qi-Xing
Liang, Jin-Hua
Wang, Zhen
Wang, Li
Fan, Lei
Hua, Dong
Chen, Yao-Yu
Xu, Wei
Zhang, Zhi-Hong
Li, Jian-Yong
author_facet Lu, Ting-Xun
Miao, Yi
Wu, Jia-Zhu
Gong, Qi-Xing
Liang, Jin-Hua
Wang, Zhen
Wang, Li
Fan, Lei
Hua, Dong
Chen, Yao-Yu
Xu, Wei
Zhang, Zhi-Hong
Li, Jian-Yong
author_sort Lu, Ting-Xun
collection PubMed
description 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 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.
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spelling pubmed-47465872016-02-17 The distinct clinical features and prognosis of the CD10(+)MUM1(+) and CD10(−)Bcl6(−)MUM1(−) diffuse large B-cell lymphoma Lu, Ting-Xun Miao, Yi Wu, Jia-Zhu Gong, Qi-Xing Liang, Jin-Hua Wang, Zhen Wang, Li Fan, Lei Hua, Dong Chen, Yao-Yu Xu, Wei Zhang, Zhi-Hong Li, Jian-Yong Sci Rep Article 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 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. Nature Publishing Group 2016-02-09 /pmc/articles/PMC4746587/ /pubmed/26857366 http://dx.doi.org/10.1038/srep20465 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Lu, Ting-Xun
Miao, Yi
Wu, Jia-Zhu
Gong, Qi-Xing
Liang, Jin-Hua
Wang, Zhen
Wang, Li
Fan, Lei
Hua, Dong
Chen, Yao-Yu
Xu, Wei
Zhang, Zhi-Hong
Li, Jian-Yong
The distinct clinical features and prognosis of the CD10(+)MUM1(+) and CD10(−)Bcl6(−)MUM1(−) diffuse large B-cell lymphoma
title The distinct clinical features and prognosis of the CD10(+)MUM1(+) and CD10(−)Bcl6(−)MUM1(−) diffuse large B-cell lymphoma
title_full The distinct clinical features and prognosis of the CD10(+)MUM1(+) and CD10(−)Bcl6(−)MUM1(−) diffuse large B-cell lymphoma
title_fullStr The distinct clinical features and prognosis of the CD10(+)MUM1(+) and CD10(−)Bcl6(−)MUM1(−) diffuse large B-cell lymphoma
title_full_unstemmed The distinct clinical features and prognosis of the CD10(+)MUM1(+) and CD10(−)Bcl6(−)MUM1(−) diffuse large B-cell lymphoma
title_short The distinct clinical features and prognosis of the CD10(+)MUM1(+) and CD10(−)Bcl6(−)MUM1(−) diffuse large B-cell lymphoma
title_sort distinct clinical features and prognosis of the cd10(+)mum1(+) and cd10(−)bcl6(−)mum1(−) diffuse large b-cell lymphoma
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4746587/
https://www.ncbi.nlm.nih.gov/pubmed/26857366
http://dx.doi.org/10.1038/srep20465
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