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Keywords = V(D)J rearrangement patterns

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22 pages, 2639 KiB  
Article
Overlapping Gene Expression and Molecular Features in High-Grade B-Cell Lymphoma
by Katharina D. Faißt, Cora C. Husemann, Karsten Kleo, Monika Twardziok and Michael Hummel
J. Mol. Pathol. 2024, 5(4), 415-436; https://doi.org/10.3390/jmp5040028 - 30 Sep 2024
Viewed by 2369
Abstract
Aggressive B-cell lymphoma encompasses Burkitt lymphoma (BL), diffuse large B-cell lymphoma (DLBCL), and, as per the 2016 WHO classification, high-grade B-cell lymphoma (HGBL) not otherwise specified (NOS) and HGBL double/triple hit (DH/TH). However, the diagnostic distinction of HGBL from BL and DLBCL is [...] Read more.
Aggressive B-cell lymphoma encompasses Burkitt lymphoma (BL), diffuse large B-cell lymphoma (DLBCL), and, as per the 2016 WHO classification, high-grade B-cell lymphoma (HGBL) not otherwise specified (NOS) and HGBL double/triple hit (DH/TH). However, the diagnostic distinction of HGBL from BL and DLBCL is difficult by means of histology/immunostaining in a substantial number of patients. This study aimed to improve subtyping by the identification of molecular features of aggressive B-cell lymphomas, with a specific focus on HGBL. To this end, we performed a comprehensive gene expression and mutational pattern analysis as well as the detection of B-cell clonality of 34 cases diagnosed with BL (n = 4), DLBCL (n = 16), HGBL DH (n = 8), and HGBL NOS (n = 6). Three distinct molecular subgroups were identified based on gene expression, primarily influenced by MYC expression/translocation and cell proliferation. In HGBL, compared to BL, there was an upregulation of PRKAR2B and TERT. HGBL DH exhibited elevated expression of GAMT and SMIM14, while HGBL NOS showed increased expression of MIR155HG and LZTS1. Our gene mutation analysis revealed MYC, ARID1A, BCL2, KMT2D, and PIM1 as the most affected genes in B-cell lymphoma, with BCL2 and CREBBP predominant in HGBL DH, and MYC and PIM1 in HGBL NOS. Clonality analysis of immunoglobulin heavy and light chain rearrangements did not show distinguishable V- or J-usage between the diagnostic subgroups. Full article
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20 pages, 3032 KiB  
Article
A Comparative Analysis of the Immunoglobulin Repertoire in Leukemia Cells and B Cells in Chinese Acute Myeloid Leukemia by High-Throughput Sequencing
by Huige Yan, Lina Wu, Pingzhang Wang, Miaoran Xia, Zhan Shi, Xinmei Huang, Sha Yin, Qian Jiang, C. Cameron Yin, Xiangyu Zhao and Xiaoyan Qiu
Biology 2024, 13(8), 613; https://doi.org/10.3390/biology13080613 - 13 Aug 2024
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Abstract
It is common knowledge that immunoglobulin (Ig) is produced by B lymphocytes and mainly functions as an antibody. However, it has been shown recently that myeloblasts from acute myeloid leukemia (AML) could also express Ig and that AML-Ig played a role in leukemogenesis [...] Read more.
It is common knowledge that immunoglobulin (Ig) is produced by B lymphocytes and mainly functions as an antibody. However, it has been shown recently that myeloblasts from acute myeloid leukemia (AML) could also express Ig and that AML-Ig played a role in leukemogenesis and AML progression. The difference between Ig from myeloblasts and B cells has not been explored. Studying the characteristics of the Ig repertoire in myeloblasts and B cells will be helpful to understand the function and significance of AML-Ig. We performed 5′ RACE-related PCR coupled with PacBio sequencing to analyze the Ig repertoire in myeloblasts and B cells from Chinese AML patients. Myeloblasts expressed all five classes of IgH, especially Igγ, with a high expression frequency. Compared with B-Ig in the same patient, AML-Ig showed different biased V(D)J usages and mutation patterns. In addition, the CDR3 length distribution of AML-Ig was significantly different from those of B-Ig. More importantly, mutations of AML-IgH, especially Igμ, Igα, and Igδ, were different from that of B-IgH in each AML patient, and the mutations frequently occurred at the sites of post-translational modification. AML-Ig has distinct characteristics of variable regions and mutations, which may have implications for disease monitoring and personalized therapy. Full article
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