PhD Scientific Days 2024

Poster Session A - Molecular Medicine 1.

Molecular Heterogeneity of Diffuse Large B-cell Lymphoma: A Multi-Centre Real-World Study

Text of the abstract

Introduction: Two-thirds of diffuse large B-cell lymphoma (DLBCL) patients are cured with first-line treatment, however, one-third still develop relapsed/refractory DLBCL with inferior prognosis. This is partly due to the underlying molecular heterogeneity of the disease. In a multi-centre study, our research team is collecting tissue and follow-up liquid biopsy materials from a total of 124 newly diagnosed DLBCL patients from nine haematology centres in Hungary, starting from September 2022.

Aims: We aim to assess the utility of currently available molecular classification systems on a "real-world" cohort.

Method: We have created the proprietary 'SU-DLBCL Predictor' gene panel, which allows the analysis of 251 genes, 4 translocation breakpoints (BCL2, BCL6, MYC, PD-L1) and copy number variations genome-wide. Eighty-three tissue samples from patients with DLBCL at diagnosis were analysed using this panel. After library preparation with a custom SureSelect XTHS2 (Agilent, USA) panel, samples were sequenced on NextSeq2000 (Illumina, USA) platform and data were evaluated using our bioinformatics pipeline, the LymphGen classification algorithm and R statistical software.

Results: In the 83 samples analysed, the LymphGen algorithm identified 10 ST2 (12%), 8 EZB (9.5%), 8 BN2 (9.5%), 6 MCD (7%), 5 A53 (6%), 2 N1 (2%), 3 composite (4%) and 41 Other (50%) cases. Mutations were most frequently identified in the KMT2D (48%), PABPC1 (39%), HIST1H1E (28%), MYD88 (27%), and TP53 (27%) genes, with copy number gains most frequently involving the BCL2 (31%), BCL6 (27%), and SOCS1 (25%) genes. 17p deletions were detected in 7 samples (8%).

Results: We were the first in Hungary to successfully optimize a test algorithm for the classification of DLBCL. Our preliminary results for 83 samples show a large overlap with the literature both in terms of variation frequency and subgroup distribution.

Funding: The research was funded by the NRDIH KDP-1022882, EFOP-3.6. 3-VEKOP-16-2017-00009, ÚNKP-21-3-II-SE-24, ÚNKP-22-5-SE-7, ÚNKP-22-3-II-SE-72, H2020-739593, K21_137948, TKP2021-EGA-24, TKP2021-NVA-15, FK20_134253, the MTA Bolyai programme BO/125/22 and Elixir Hungary.