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A novel classification based on B-cell receptor signal gene expression correlates with prognosis in primary breast diffuse large B-cell lymphoma

Primary breast diffuse large B-cell lymphoma (PB-DLBCL), the most common histologic subtype of lymphoid malignancy in the breast, is a clinically and genetically heterogeneous disease that has insufficient systematic studies on the pathological and molecular features, optimal treatment scheme, as we...

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Autores principales: Su, Wenjia, Niu, Xingjian, Ji, Hongfei, Xu, Yang, Zhong, Lei, Wang, Shuye, Tang, Dabei, Zhou, Xiaoping, Zhang, Qingyuan, Zhou, Jin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ivyspring International Publisher 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7066002/
https://www.ncbi.nlm.nih.gov/pubmed/32201514
http://dx.doi.org/10.7150/jca.39083
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author Su, Wenjia
Niu, Xingjian
Ji, Hongfei
Xu, Yang
Zhong, Lei
Wang, Shuye
Tang, Dabei
Zhou, Xiaoping
Zhang, Qingyuan
Zhou, Jin
author_facet Su, Wenjia
Niu, Xingjian
Ji, Hongfei
Xu, Yang
Zhong, Lei
Wang, Shuye
Tang, Dabei
Zhou, Xiaoping
Zhang, Qingyuan
Zhou, Jin
author_sort Su, Wenjia
collection PubMed
description Primary breast diffuse large B-cell lymphoma (PB-DLBCL), the most common histologic subtype of lymphoid malignancy in the breast, is a clinically and genetically heterogeneous disease that has insufficient systematic studies on the pathological and molecular features, optimal treatment scheme, as well as the prognostic factors. The aim of our study was to identify biomarkers and distinct subtypes of PB-DLBCLs and then evaluate the prognosis of this rare malignant lymphoma. We carried out hierarchical clustering analysis to evaluate protein expressions of potential biomarkers detected by immunohistochemistry staining of samples from 68 PB-DLBCL patients. The gene expression data from TCGA database was obtained to validate the identified clusters. We identified three robust clusters based on the B-cell receptor (BCR) signaling pathway, including two recognized NF-κB-dependent and PI3K-dependent clusters, and a distinct subset of PB-DLBCL with NF-κB-independent anti-apoptotic overexpression plus PI3K signaling, which exhibited an evolving definition and distinctive characters of a cluster group. Furthermore, survival analysis results showed an inferior outcome in NF-κB-dependent cluster patients and favorable survival in the PI3K-dependent cluster patients, suggesting an important predictive value of the three clusters. Our study provided a new perspective for understanding clinical complexity of PB-DLBCLs, and gave evidence for finding targeted biomarkers and strategies.
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spelling pubmed-70660022020-03-20 A novel classification based on B-cell receptor signal gene expression correlates with prognosis in primary breast diffuse large B-cell lymphoma Su, Wenjia Niu, Xingjian Ji, Hongfei Xu, Yang Zhong, Lei Wang, Shuye Tang, Dabei Zhou, Xiaoping Zhang, Qingyuan Zhou, Jin J Cancer Research Paper Primary breast diffuse large B-cell lymphoma (PB-DLBCL), the most common histologic subtype of lymphoid malignancy in the breast, is a clinically and genetically heterogeneous disease that has insufficient systematic studies on the pathological and molecular features, optimal treatment scheme, as well as the prognostic factors. The aim of our study was to identify biomarkers and distinct subtypes of PB-DLBCLs and then evaluate the prognosis of this rare malignant lymphoma. We carried out hierarchical clustering analysis to evaluate protein expressions of potential biomarkers detected by immunohistochemistry staining of samples from 68 PB-DLBCL patients. The gene expression data from TCGA database was obtained to validate the identified clusters. We identified three robust clusters based on the B-cell receptor (BCR) signaling pathway, including two recognized NF-κB-dependent and PI3K-dependent clusters, and a distinct subset of PB-DLBCL with NF-κB-independent anti-apoptotic overexpression plus PI3K signaling, which exhibited an evolving definition and distinctive characters of a cluster group. Furthermore, survival analysis results showed an inferior outcome in NF-κB-dependent cluster patients and favorable survival in the PI3K-dependent cluster patients, suggesting an important predictive value of the three clusters. Our study provided a new perspective for understanding clinical complexity of PB-DLBCLs, and gave evidence for finding targeted biomarkers and strategies. Ivyspring International Publisher 2020-02-10 /pmc/articles/PMC7066002/ /pubmed/32201514 http://dx.doi.org/10.7150/jca.39083 Text en © The author(s) This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
spellingShingle Research Paper
Su, Wenjia
Niu, Xingjian
Ji, Hongfei
Xu, Yang
Zhong, Lei
Wang, Shuye
Tang, Dabei
Zhou, Xiaoping
Zhang, Qingyuan
Zhou, Jin
A novel classification based on B-cell receptor signal gene expression correlates with prognosis in primary breast diffuse large B-cell lymphoma
title A novel classification based on B-cell receptor signal gene expression correlates with prognosis in primary breast diffuse large B-cell lymphoma
title_full A novel classification based on B-cell receptor signal gene expression correlates with prognosis in primary breast diffuse large B-cell lymphoma
title_fullStr A novel classification based on B-cell receptor signal gene expression correlates with prognosis in primary breast diffuse large B-cell lymphoma
title_full_unstemmed A novel classification based on B-cell receptor signal gene expression correlates with prognosis in primary breast diffuse large B-cell lymphoma
title_short A novel classification based on B-cell receptor signal gene expression correlates with prognosis in primary breast diffuse large B-cell lymphoma
title_sort novel classification based on b-cell receptor signal gene expression correlates with prognosis in primary breast diffuse large b-cell lymphoma
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7066002/
https://www.ncbi.nlm.nih.gov/pubmed/32201514
http://dx.doi.org/10.7150/jca.39083
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