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Mutation landscape in Chinese nodal diffuse large B-cell lymphoma by targeted next generation sequencing and their relationship with clinicopathological characteristics.

Authors :
Cao B
Sun C
Bi R
Liu Z
Jia Y
Cui W
Sun M
Yu B
Li X
Zhou X
Source :
BMC medical genomics [BMC Med Genomics] 2024 Apr 13; Vol. 17 (1), pp. 84. Date of Electronic Publication: 2024 Apr 13.
Publication Year :
2024

Abstract

Background: Diffuse large B-cell lymphoma (DLBCL), an aggressive and heterogenic malignant entity, is still a challenging clinical problem, since around one-third of patients are not cured with primary treatment. Next-generation sequencing (NGS) technologies have revealed common genetic mutations in DLBCL. We devised an NGS multi-gene panel to discover genetic features of Chinese nodal DLBCL patients and provide reference information for panel-based NGS detection in clinical laboratories.<br />Methods: A panel of 116 DLBCL genes was designed based on the literature and related databases. We analyzed 96 Chinese nodal DLBCL biopsy specimens through targeted sequencing.<br />Results: The most frequently mutated genes were KMT2D (30%), PIM1 (26%), SOCS1 (24%), MYD88 (21%), BTG1 (20%), HIST1H1E (18%), CD79B (18%), SPEN (17%), and KMT2C (16%). SPEN (17%) and DDX3X (6%) mutations were highly prevalent in our study than in Western studies. Thirty-three patients (34%) were assigned as genetic classification by the LymphGen algorithm, including 12 cases MCD, five BN2, seven EZB, seven ST2, and two EZB/ST2 complex. MYD88 L265P mutation, TP53 and BCL2 pathogenic mutations were unfavorable prognostic biomarkers in DLBCL.<br />Conclusions: This study presents the mutation landscape in Chinese nodal DLBCL, highlights the genetic heterogeneity of DLBCL and shows the role of panel-based NGS to prediction of prognosis and potential molecular targeted therapy in DLBCL. More precise genetic classification needs further investigations.<br /> (© 2024. The Author(s).)

Details

Language :
English
ISSN :
1755-8794
Volume :
17
Issue :
1
Database :
MEDLINE
Journal :
BMC medical genomics
Publication Type :
Academic Journal
Accession number :
38609996
Full Text :
https://doi.org/10.1186/s12920-024-01866-y