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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.
- Source :
- BMC Medical Genomics; 4/13/2024, Vol. 17 Issue 1, p1-14, 14p
- 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. 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. 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. 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. [ABSTRACT FROM AUTHOR]
- Subjects :
- NUCLEOTIDE sequencing
DIFFUSE large B-cell lymphomas
GENETIC mutation
Subjects
Details
- Language :
- English
- ISSN :
- 17558794
- Volume :
- 17
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- BMC Medical Genomics
- Publication Type :
- Academic Journal
- Accession number :
- 176583048
- Full Text :
- https://doi.org/10.1186/s12920-024-01866-y