An Overview on Diffuse Large B-Cell Lymphoma Models: Towards a Functional Genomics Approach

Abstract

Lymphoma research is a paradigm of the integration of basic and clinical research within the fields of diagnosis and therapy. Clinical, phenotypic, and genetic data are currently used to predict which patients could benefit from standard treatment. However, alternative therapies for patients at higher risk from refractoriness or relapse are usually empirically proposed, based on trial and error, without considering the genetic complexity of aggressive B-cell lymphomas. This is primarily due to the intricate mosaic of genetic and epigenetic alterations in lymphomas, which are an obstacle to the prediction of which drug will work for any given patient. Matching a patient's genes to drug sensitivity by directly testing live tissues comprises the "precision medicine" concept. However, in the case of lymphomas, this concept should be expanded beyond genomics, eventually providing better treatment options for patients in need of alternative therapeutic approaches. We provide an overview of the most recent findings in diffuse large B-cell lymphomas genomics, from the classic functional models used to study tumor biology and the response to experimental treatments using cell lines and mouse models, to the most recent approaches with spheroid/organoid models. We also discuss their potential relevance and applicability to daily clinical practice.

Keywords: B-cell lymphoma; cancer; cell lines; diffuse large B-cell lymphoma; functional model; gene editing; genomics; murine models; organoid/spheroid; therapy.

Figure 1

Diffuse large B-cell lymphoma complexity: untangling the networks underlying genetic subtypes. Schematic view of the most relevant genetic events in B-cell physiology pathways for each genetic subtype (GS) highlighted in purple (MCD), light blue (BN2), yellow (EZB), green (N1), or red (ST2), as described in the figure key. Mutations in CD79A and CD79B and SYK lead to chronic activation of the B-cell receptor (BCR; of special importance in the MCD GS), which triggers the activation of SYK, BTK, and PKC promoting the formation of the CARD11-BCL10-MALT1 complex. Mutations in genes that encode all the components in this complex can be identified in a subset of DLBCLs and are especially relevant for the BN2 GS. Mutations in genes that encode MYD88, IRAK1, and IRAK4 activate Toll-like receptor (TLR) signaling, which is further promoted by alterations in positive regulators downstream TLR, such as TRAF6. Alterations in Notch signaling, binding of CD27 to CD70, and BCR activation also lead to abnormal activation of PI3K-AKT-mTOR pathway, which also presents genetic alterations in this disorder. Most of these pathways converge in the activation of IKK and downstream NF-κB signaling, promoting lymphomagenesis. Tumor cell survival is boosted by alterations in the BLC2 and BCL6 axis, TP53, and imbalances in cytokine related pathways: interleukins (IL), interferon gamma (IFNγ), or tumor necrosis factor (TNF), which overall lead to increased survival and decreased apoptosis in these cells. Alterations at the nuclear level are also common in all genetic subtypes (except for the N1 subtype), and involve p53, DNA damage pathway, epigenetic regulators, and other components involved in proliferation and survival cell processes. Currently, there are targeted therapies against several components downstream these pathways (tagged with a pill icon). Activating genetic events are highlighted with a star, while those involving inactivation are flagged with a hexagon.

Figure 2

Preclinical models in lymphoma research and procedures. Research models in B-cell lymphomas include: (A) two-dimensional (2D) cell cultures comprising B-cells, patient lymphoma samples, DLBCL cell lines, gene edited cell lines, or mixed-cell cultures; (B) three-dimensional (3D) cell cultures, such as simple organoids involving a single cell type, complex organoids involving several cell types, and more complex systems, such as organ-on-chip models and microfluidics-based platforms; (C) mouse models, with CD57BL/6, immunodeficient, or genetically engineered mice (GEM). Their uses are summarized in the boxes below the mice. (D) All these elements can be combined and used to develop a variety of procedures involving cells from the same species (syngeneic allografts, left) or from different species (xenografts, right).

Figure 3

The near future for B-cell lymphoma patients: genetic signatures lead to personalized treatments. Recent studies have identified genetic signatures in diffuse large B-cell lymphoma (DLBCL) patients that can be used to predict outcome and therapy response. In the near future, a combination of newly adapted routines in daily clinical practice (left) and basic research (right) are very likely to lead to personalized treatments for B-cell lymphoma patients, based on the genetic profile of their biopsies. To this end, gene edition of DLBCL cell lines in the laboratory will enable the replication of the DLBCL genetic subtypes (GS) identified in patients (BN2, N1, EZB, MCD, and ST2). 3D organoid-based drug screenings will establish the sensitivities of the different genetic variants to single drugs or drug combinations, at the dose and posology levels, while maintaining the lymphoma microenvironment and intercellular interactions. Once a GS has been matched to a certain treatment regimen, drug sensitivity should be validated in organoids derived from fresh patient biopsies (patient derived organoids, PDOs). Inclusion of biopsy sequencing using targeted panels of selected genes as part of the daily clinical routine will eventually allow personalized treatments to be directly assigned based on the GS of patient biopsies, optimized treatment-response rates, and improved overall survival. FFPE: formalin-fixed, paraffin-embedded.