Wenhua Jiang1, Hailong Wang2, Shiyong Zhou3, Guoqing Zhu4, Mingyou Gao5, Kuo Zhao5, Limeng Zhang5, Xiaojing Xie5, Ning Zhao5, Caijuan Tian6, Zhenzhen Zhang6, Fang Yan6, Yi Pan7, Pengfei Liu8. 1. Department of Radiotherapy, The Second Hospital of Tianjin Medical University, Tianjin, 300211, China. 2. Department of Oncology, Tianjin Academy of Traditional Chinese Medicine Affiliated Hospital, No.354 Beima Road, Hongqiao District, Tianjin, 300120, China. 3. Department of Lymphoma, Sino-US Center of Lymphoma and Leukemia, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China. 4. State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300020, China. 5. Department of Oncology, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Tianjin, 300060, China. 6. Tianjin Marvel Medical Laboratory, Tianjin Marvelbio Technology Co., Ltd, Tianjin, 300381, China. 7. Department of Pathology, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin Medical University Cancer Institute and Hospital, Huanhu West Road, Tiyuanbei, Hexi District, Tianjin, 300060, China. tjzlpy@163.com. 8. Department of Oncology, Tianjin Academy of Traditional Chinese Medicine Affiliated Hospital, No.354 Beima Road, Hongqiao District, Tianjin, 300120, China. tianjinmarvel@163.com.
Abstract
BACKGROUND: The purpose of this study was to construct a new typing model for diffuse large B-cell lymphoma (DLBCL) patients based on the B-cell receptor (BCR) and explore its potential molecular mechanism. METHODS: BCR repertoire sequencing and whole-exome sequencing were performed on formalin-fixed paraffin-embedded samples from 12 DLBCL patients. Subsequently, a typing model was built with cluster analysis, and prognostic indicators between the two groups were compared to verify the typing model. Then, mutation and bioinformatics analyses were conducted to investigate the potential biomarkers of prognostic differences between the two groups. RESULTS: Based on BCR sequencing data, we divided patients into two clusters (cluster 1 and cluster 2); this classification differed from the traditional typing method (GCB and non-GCB), in which cluster 1 included some non-GCB patients. The progression-free survival (PFS), overall survival (OS), metastasis and Shannon diversity index of IGH V-J and survival after chemotherapy were significantly different (P < 0.05) between the two clusters, but no statistical significance was found between the GCB and non-GCB groups. The mutation status of 248 genes was significantly different between cluster 1 and cluster 2. Among them, FTSJ3, MAGED2, and ODF3L2 were the specific mutated genes in all patients in cluster 2, and these genes could be considered critical to the different prognoses of the two clusters of DLBCL patients. CONCLUSION: We constructed a new typing model of DLBCL based on BCR repertoire sequencing that can better predict the survival time after chemotherapy. FTSJ3, MAGED2, and ODF3L2 may represent key genes for the difference in prognosis between the two clusters.
BACKGROUND: The purpose of this study was to construct a new typing model for diffuse large B-cell lymphoma (DLBCL) patients based on the B-cell receptor (BCR) and explore its potential molecular mechanism. METHODS: BCR repertoire sequencing and whole-exome sequencing were performed on formalin-fixed paraffin-embedded samples from 12 DLBCL patients. Subsequently, a typing model was built with cluster analysis, and prognostic indicators between the two groups were compared to verify the typing model. Then, mutation and bioinformatics analyses were conducted to investigate the potential biomarkers of prognostic differences between the two groups. RESULTS: Based on BCR sequencing data, we divided patients into two clusters (cluster 1 and cluster 2); this classification differed from the traditional typing method (GCB and non-GCB), in which cluster 1 included some non-GCBpatients. The progression-free survival (PFS), overall survival (OS), metastasis and Shannon diversity index of IGH V-J and survival after chemotherapy were significantly different (P < 0.05) between the two clusters, but no statistical significance was found between the GCB and non-GCB groups. The mutation status of 248 genes was significantly different between cluster 1 and cluster 2. Among them, FTSJ3, MAGED2, and ODF3L2 were the specific mutated genes in all patients in cluster 2, and these genes could be considered critical to the different prognoses of the two clusters of DLBCL patients. CONCLUSION: We constructed a new typing model of DLBCL based on BCR repertoire sequencing that can better predict the survival time after chemotherapy. FTSJ3, MAGED2, and ODF3L2 may represent key genes for the difference in prognosis between the two clusters.
Entities:
Keywords:
B-cell receptor repertoire; Diffuse large B-cell lymphoma; Prognosis; Typing
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