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Single-Cell Atlas of Diffuse Large B-Cell Lymphoma Reveals Integrated Malignant B Cell and Tumor Microenvironment Characteristics Associated with Clinical Response
Background: Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive B-cell lymphoma with high clinical and biological heterogeneity. Despite current effective immunochemotherapy, up to 40% of patients do not respond or develop refractory disease. DLBCL is characterized by two major cell-...
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Published in: | Blood 2024-11, Vol.144, p.1597-1597 |
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Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Online Access: | Get full text |
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Summary: | Background:
Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive B-cell lymphoma with high clinical and biological heterogeneity. Despite current effective immunochemotherapy, up to 40% of patients do not respond or develop refractory disease. DLBCL is characterized by two major cell-of-origin (COO) subtypes, germinal center B cell-like (GCB) and activated B cell-like (ABC), with recent research uncovering additional molecular subgroups based on genomic alterations or tumor microenvironment (TME) features. We recently reported (Baaklini et al. ASH 2023) a multimodal single-cell atlas of 62 DLBCL cases, integrating single-cell transcriptomes, immune repertoire and genetic features, that we have leveraged to decrypt recurrent B cell states and TME ecosystems while identifying clinically relevant prognostic biomarkers. Here we report further analyses of the single-cell atlas dataset focused on TME composition and differentiation trajectories, and the validation of our main findings through cell-state deconvolution of bulk RNA-seq datasets and single-cell spatial transcriptomics analyses.
Methods:
The DLBCL single-cell atlas was generated with 5'-end single-cell RNA, B-cell receptor (BCR) and T-cell receptor sequencing on 63 DLBCL lymph node biopsies obtained from the real-world, clinically-annotated, multicentric CeVi collection and included 43 patient samples at diagnosis (ABC = 17, GCB = 11, Unclassified = 6, Not Evaluated = 9; 21 of which did not achieve event-free survival at 24 months (EFS24) after R-chemotherapy regimens), 11 relapsed/refractory DLBCL and 8 DLBCL transformed from indolent lymphoma. Methods for overall cell annotation and malignant B cell states identification were reported previously (Baaklini et al. ASH 2023). For the analysis of the TME and the focus on T cells, we identified clonally expanded T-cell subsets based on their TCR sequences, and used trajectory inference algorithms to track CD8 T cell branched differentiation. Validation on public, clinically annotated data (Schmitz et al. NEJM 2018) was performed by gene signature scoring and reference-based deconvolution. Single-cell spatial transcriptomics was performed on a subseries of 20 DLBCL cases laid out as tissue microarrays, using two distinct technologies with off-the-shelf 1000-plex and 377-plex panels.
Results:
We previously reported the identification of 5 conserved malignant B cell transcriptional archetypes (Arch.1-5) that co-exist in DLBCL samples: Arch.1 |
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ISSN: | 0006-4971 |
DOI: | 10.1182/blood-2024-209815 |