A third of patients with diffuse large B-cell lymphoma (DLBCL) present with extranodal dissemination, which is associated with inferior clinical outcomes. MYD88L265P is a hallmark extranodal DLBCL mutation that supports lymphoma proliferation. Yet extranodal lymphomagenesis and the role of MYD88L265P in transformation remain mostly unknown. Here, we show that B cells expressing Myd88L252P (MYD88L265P murine equivalent) activate, proliferate, and differentiate with minimal T-cell costimulation. Additionally, Myd88L252P skewed B cells toward memory fate. Unexpectedly, the transcriptional and phenotypic profiles of B cells expressing Myd88L252P, or other extranodal lymphoma founder mutations, resembled those of CD11c+T-BET+ aged/autoimmune memory B cells (AiBC). AiBC-like cells progressively accumulated in animals prone to develop lymphomas, and ablation of T-BET, the AiBC master regulator, stripped mouse and human mutant B cells of their competitive fitness. By identifying a phenotypically defined prospective lymphoma precursor population and its dependencies, our findings pave the way for the early detection of premalignant states and targeted prophylactic interventions in high-risk patients.

Significance:

Extranodal lymphomas feature a very poor prognosis. The identification of phenotypically distinguishable prospective precursor cells represents a milestone in the pursuit of earlier diagnosis, patient stratification, and prophylactic interventions. Conceptually, we found that extranodal lymphomas and autoimmune disorders harness overlapping pathogenic trajectories, suggesting these B-cell disorders develop and evolve within a spectrum.

See related commentary by Leveille et al. (Blood Cancer Discov 2023;4:8–11).

This article is highlighted in the In This Issue feature, p. 1

Diffuse large B-cell lymphomas (DLBCL) are biological and clinically heterogeneous diseases that develop from mature activated B cells (1). Under normal circumstances, B-cell activation requires stimulation of the B-cell receptor (BCR) by a cognate antigen and costimulation from specialized T cells (2). Fully activated B cells can form transient structures called germinal centers (GC), in which they undergo somatic hypermutation (SHM) and compete for T-cell help to promptly expand and improve the affinity of their BCR against foreign antigens, before differentiating into effector cells, namely, plasma cells (PC; antibody-secreting cells) or memory B cells (MBC; long-lived cells that activate upon antigen reencounter, enabling faster and enhanced responses; ref. 3). These fine-tuned processes require B cells to be transiently endowed with tumorigenic-like features (heightened proliferation, genomic instability, tolerance to DNA damage, dysregulated metabolism, cell death escape, etc.), which are hijacked and perpetuated by mutations in lymphomas (4). These mutations are believed to largely arise as aberrant by-products of SHM, a process catalyzed by the enzyme activation-induced cytidine deaminase (AID/AICDA; ref. 3).

Although DLBCLs frequently initiate from, and localize to, the lymph nodes, one third of patients present with extranodal tumors in nonlymphoid organs, including immune-privileged sites, with an often fatal outcome (5–7). Extranodal DLBCLs manifest in advanced stages of the nodal disease or occur as primary events. The localization of these aggressive tumors and their elevated relapse rates (5) create significant clinical challenges. Standard DLBCL treatments (ref. 1; chemotherapy, anti–B-cell antibodies, and radiotherapy) are insufficient to cure most patients and carry significant toxicity. Moreover, there is no way to identify their onset at early stages, when they may be more susceptible to targeted therapies.

Recent large-scale profiling efforts have yielded a genetically defined classification for DLBCLs, including the identification of a highly aggressive subtype called “C5”/“MCD” (hereafter MCD) with the highest frequency of extranodal dissemination (8, 9). MCD and primary extranodal tumors in immune-privileged sites share founder mutations targeting MYD88 [core Toll-like-receptor (TLR) signaling mediator], CD79B (BCR complex component), TBL1XR1 (transcriptional repression complexes component), and others (8, 9). Approximately 70% of these carry an MYD88L265P gain-of-function missense mutation (9) that facilitates proliferation and survival through constitutive NF-κB signaling (10). This same mutation occurs in other B-cell malignancies, including Waldenstrom macroglobulinemia (WM) and chronic lymphocytic leukemia (11, 12), highlighting its widespread biological relevance. Mice expressing Myd88L252P (murine equivalent to MYD88L265P) in all B cells develop lymphadenopathy and occasional lymphomas with old age (13). A combination of Myd88L252P with BCL2 overexpression, a common feature in MCD-DLBCLs (8, 9), results in a higher incidence of lymphomas that closely resemble their human counterparts (14). However, the mechanisms through which these tumors arise from the immune system and progress to an overt and advanced disease remain unknown.

MCD tumors show the highest AID activity footprint, suggesting that these have transited through the GC during transformation (8). Still, AICDA is expressed in activated B cells before entering the GC (15), and even in proliferating B cells outside of lymphoid follicles (16), suggesting that MCD precursors could resort to alternative activated states to accumulate mutations (17). Because the immune system keeps a tight control on B-cell activation through selective costimulation, we hypothesized that MCD founder mutations altered these requirements, enabling the progressive transformation and expansion of lymphoma precursors. Here, we explore the evolutionary advantage conferred to mature B cells by the hallmark mutation MYD88L265P, as well as the pathogenic trajectories delineated by this mutation, to provide critical insight into extranodal lymphoma transformation and the precursor populations involved.

Myd88 Mutations Confer a Competitive Advantage to GC B Cells

To dissect how MCD founder mutations shape pathogenic trajectories, we first explored the impact of the class-defining lesion MYD88L265P on the GC. We crossed an existing Cre-inducible Myd88L252P mouse model (13) to the Cγ1Cre strain (18), restricting MYD88-mutant expression to (pre-) GC B cells (GCB) and GC-derived cells. We immunized young Cγ1Cre;Myd88L252P/WT or Cγ1Cre;Myd88WT/WT [wild-type (WT)] mice with the T cell–dependent antigen sheep red blood cells (SRBC) and profiled spleens at the peak of the GC. Although B-cell levels were unaltered (Fig. 1A; Supplementary Fig. S1A), Myd88L252P/WT mice showed a significant increase in the fraction (Fig. 1B) and absolute number (Supplementary Fig. S1B) of FAS+GL7+ GCBs. This expansion extended to GCBs with a mature phenotype (FAS+CD38; Supplementary Fig. S1C). An alternative T cell–dependent antigen yielded similar results (Supplementary Fig. S1D). In line with these findings, IHC staining for B cells (B220) and GCBs [peanut agglutinin (PNA)] revealed intact follicles harboring an increase in GC number and size in Myd88L252P/WT mice (Fig. 1CE).

To test whether Myd88L252P enhanced the competitive fitness of GCB, we conducted mixed chimera experiments in which equal numbers of Cd45.2;Myd88L252P/WT or Cd45.1/2;Myd88WT/WT bone marrow (BM) cells were transplanted into irradiated WT recipients. Following immunization, Myd88L252P GCBs manifested a significant competitive advantage, whereas the proportions of CD45.2+ and CD45.1/2+ total B cells were comparable (Fig. 1F). To dissect the kinetics of this advantage, we investigated additional time points following immunization. Although the GC response in chimeric mice showed the expected profile and duration (Fig. 1G, left), Myd88L252P GCBs were consistently expanded and developed cumulative dominance over time (Fig. 1G, center and right). These results indicate that GCBs harboring MYD88 mutations are endowed with a significant competitive advantage.

Myd88-Mutant GCB Exhibit Increased Proliferative Capacity

The size of the GC is determined through a fine-tuned balance between proliferation and cell death (3). Notably, the fraction of apoptotic GCBs was comparable in WT and Myd88L252P/WT mice, as assessed by cleaved caspase (Supplementary Fig. S2A) or Annexin V/DAPI (Supplementary Fig. S2B) staining, suggesting aberrant survival does not explain Myd88L252P GCB fitness. On the other hand, Myd88L252P GCB showed increased levels of the proliferation marker Ki-67 as compared with WT (Fig. 2A). Similarly, mutant GCBs exhibited higher incorporation of 5-ethynyl-2-deoxyuridine (EdU; Fig. 2B), indicative of increased DNA synthesis and proliferation. Notably, although the fraction of proliferating WT GCBs progressively decreased over the GC as expected (19), the proportion of Ki-67+Myd88L252P GCBs remained elevated and fairly constant (Fig. 2C). These differences align with the observed cumulative expansion of Myd88L252P/WT GCBs (Fig. 1G).

To gain insight into the proliferative capacity of Myd88L252P/WT B cells, we used an established culture system in which naïve B cells (NB) exposed to high levels of costimulatory signals develop a GC-like phenotype (iGCB; refs. 20, 21). To avoid artifactual effects related to the extent and timing of Cγ1Cre-induced recombination ex vivo, we isolated NB from CD19Cre;Myd88L252P/WT or CD19Cre;Myd88WT/WT mice. Although both WT and mutant B cells acquired an iGCB profile to a similar extent (see below), Myd88L252P/WT iGCB divided faster, as revealed by accelerated proliferation dye dilution (Supplementary Fig. S2C). These results suggest that the proliferative advantage of Myd88L252P/WT GCB is supported, at least in part, through a cell-intrinsic effect.

Myd88 Mutations Blur the Separation between GC Cell Compartments

The GC reaction is made up of anatomically and functionally specialized compartments; the dark zone (DZ; CXCR4+CD86) and light zone (LZ; CXCR4CD86+). Positively selected GCBs undergo repeated rounds of division in the DZ (3). In line with the increase in proliferating GCBs, Myd88L252P mice showed relative expansion of DZ GCBs (Supplementary Fig. S2D), and Myd88L252P GCBs preferentially acquired a DZ profile in chimeric mice (Fig. 2D). This became more pronounced at later stages in the GC reaction (Supplementary Fig. S2E). However, the fraction of proliferating cells (Fig. 2E) and the relative expression of Ki-67 among them (Fig. 2F) were higher in both compartments for Myd88L252P GCB than for WT. Thus, the increase in proliferating mutant GCBs does not simply reflect an abnormal distribution across zones but rather appears as a core feature conferred by Myd88L252P to all GCB, which obscures canonical compartmentalization.

To explore this, we sorted Myd88L252P/WT or WT GCBs from each compartment and conducted RNA sequencing (RNA-seq). Hierarchical clustering and principal component analysis revealed segregation by both Myd88 status and cell type (Fig. 2G; Supplementary Fig. S2F). Interestingly, despite the phenotypic DZ/LZ asymmetry observed by flow cytometry (FC), Myd88L252P/WT DZ and LZ GCBs were transcriptionally closer to prototypical LZ GCBs (Fig. 2H; Supplementary Fig. S2G) and further away from prototypical DZ GCBs (Fig. 2I; Supplementary Fig. S2G) than their WT counterparts. Hence, although Myd88L252P DZ GCBs portray canonical features, such as their proliferative status, their transcriptional identity appears more ambiguous.

Myd88 Mutations Reduce the Threshold for T cell–Derived Costimulatory Signals

B cells require costimulation to fully activate, escape cell death, and differentiate (2). In the GC, specialized follicular helper T cells (TFH) provide membrane-bound (e.g., CD40L) and soluble (e.g., IL4) signals to B cells (3). Interestingly, the transcriptional profile of MCD tumors is depleted of GC TFH signatures (9), which may reflect their immune evasive nature but could also suggest lower reliance on T-cell help. Myd88L252P and WT mice showed comparable levels of CD4+ cells (Fig. 3A). Myd88L252P mice presented an expansion of GC TFH (Fig. 3B), proportional to that of GCB (Fig. 3C), suggesting that TFH dosage in Myd88L252P GCs is adequate.

On the other hand, NF-κB priming by MYD88L265P (13) could lower signaling thresholds in B cells, enabling heightened responses with minimal T-cell help. To test whether GCB–TFH cross-talk was essential for MYD88-mutant B cells, as is for WT, we administered CD40L-blocking or control antibodies to SRBC-immunized chimeric mice (Fig. 3D). In IgG control–treated mice, Myd88L252P GCB showed the expected advantage (Fig. 3E, top row). Strikingly, whereas anti-CD40L treatment almost completely abrogated WT GCBs, there was significantly less reduction of Myd88L252P GCBs (Fig. 3E, bottom row). Myd88L252P GCBs resisting CD40L blockage still grouped in clusters within follicles (Supplementary Fig. S3A). Similar results were obtained using a strictly T cell–dependent antigen (Supplementary Fig. S3B). These results suggest that, although Myd88L252P B cells benefit from T-cell help, their lower signaling threshold allows them to fully activate, become GCBs, and expand with minimal costimulation. In fact, the relative Myd88L252P GCB expansion was more pronounced after blocking CD40L (Fig. 3F; Supplementary Fig. S3C), suggesting that normal T-cell help partially masks the advantage conferred by Myd88L252P. Differences in proliferation were also magnified after blocking CD40L, with a large proportion of Myd88L252P GCBs retaining their Ki-67+ status (Fig. 3G; Supplementary Fig. S3D).

To validate our findings, we assessed the impact of limited stimulation on iGCB formation. When exposed to high concentrations of a CD40-activating antibody, WT and Myd88L252P/WT activated and differentiated into mature iGCB at similar rates (Fig. 3H, left column). However, when the dosage was reduced by 10- or 20-fold, a larger fraction of Myd88L252P/WT B cells acquired an iGCB phenotype compared with WT (Fig. 3H, center and right columns), supporting that the activation threshold for mutant cells is significantly lower. Accordingly, Myd88L252P/WT B cells showed higher relative IκBα phosphorylation levels, and reduced total IκBα levels, compared with WT, upon acute CD40 stimulation (Supplementary Fig. S3E–S3G).

Activated B-cell DLBCL (ABC-DLBCL) tumors carrying MYD88L265P harbor increased p-STAT3 levels, and MYD88 silencing in MCD cell lines impairs STAT3 phosphorylation (10). Such an increase in p-STAT could enhance the response to IL4. Thus, we conducted additional ex vivo stimulation assays limiting IL4 concentration. Again, Myd88L252P/WT B cells managed to proliferate and acquire a fully mature iGCB phenotype even with highly restrictive IL4 concentrations that were detrimental to WT B-cell expansion/activation (Fig. 3I). In all, our data show that MYD88-mutant B cells can thrive with minimal T cell–derived costimulation.

Myd88 Mutations Favor Spontaneous GC Reactions

The lower reliance of Myd88L252P B cells on T-cell help could facilitate their recurring or persistent activation, a requirement for MCD pathogenesis (22) and tumor cell survival (23). To explore this, we profiled Myd88L252P/WT and WT mice two months after SRBC immunization, a time point at which GCs should be fully resolved. Akin to the GC peak, Myd88L252P mice exhibited significantly more GCB than WT, which only presented a residual population (Fig. 3J). Detected Myd88L252P GCBs could represent aberrantly long-lasting cells derived from the immunization, and/or originate from spontaneous GCs (24). To explore whether Myd88L252P exacerbated spontaneous GC formation/expansion, we profiled adult naïve mice housed in our specific pathogen–free facility. Indeed, Myd88L252P animals presented significantly more spontaneous splenic GCBs by FC (Fig. 3K; Supplementary Fig. S3H) or IHC (Fig. 3LN). A similar phenotype was observed in inguinal lymph nodes (Supplementary Fig. S3I). To exclude potential artifactual environmental variables—despite animals with different genotypes being housed as cagemates—we profiled naïve chimeric mice and observed comparable phenotypes (Fig. 3O; Supplementary Fig. S3J). This lower threshold to form GCBs shown by MYD88-mutant B cells could facilitate the aberrant reactivation of MCD precursor populations.

Myd88 Mutations Enable an Aberrantly Increased and Pervasive GC Output

TBL1XR1 mutations in GCBs bias them toward MBCs and away from PCs (22), which prompted us to explore whether this was a common theme among MCD founder mutations. First, we conducted a supervised analysis of the Myd88L252P/WT LZ GCB transcriptome (Fig. 2G) and, indeed, found strong enrichment for GCB-to-MBC transition signatures (Fig. 4A; ref. 25), and a depletion for genes associated with the PC fate (Fig. 4B). Differentially upregulated genes in mutant LZ GCBs included MBC-associated markers (26, 27), including Bcl2, Il9r, and Ccr6 (Supplementary Table S1). We then aimed to validate whether the transcriptional deviation from the PC fate resulted in constrained plasmacytic differentiation, using our ex vivo system (Supplementary Fig. S2C). The frequency (Fig. 4C) and absolute number (Fig. 4D) of CD138+ cells produced by Myd88L252P/WT B cells were moderately but significantly lower than for WT. Interestingly, although Myd88L252P/WT B cells lost IgD surface expression (reflective of activation) before WT did (Supplementary Fig. S4A), and underwent more division rounds per unit of time (Supplementary Fig. S4B), the relative CD138+ cell output was consistently inferior after each cell cycle (Fig. 4E).

Currently, there are no equivalent systems to induce and compare MBC formation. Thus, to assess whether the transcriptional bias translated into MBC expansion, we used a Cre-inducible fluorescent reporter (Rosa26YFP; ref. 28) to track (pre)GC-derived MBCs in vivo (Supplementary Fig. S4C). Following immunization, Rosa26YFP;Cγ1Cre;Myd88L252P/WT mice exhibited a significant increase in GC-derived (YFP+) MBC, compared with controls (Fig. 4F; Supplementary Fig. S4D). This expansion was disproportionately higher than that of GCBs (Fig. 4G), suggesting that MYD88L265P/WT GCs generate a significantly greater abundance of MBC. This exacerbated output could produce an abnormal “drainage” of LZ GCBs, and relative DZ GCB overrepresentation (Fig. 2D). Next, to determine whether the MBC expansion depended on T-cell costimulation, we generated Rosa26YFP-harboring chimeric animals and administered CD40L-blocking antibodies following immunization (Fig. 4H). Similar to GCBs (Fig. 3E), mutant YFP+ MBCs were significantly expanded in control conditions and upon impairment of GCB–TFH cross-talk (Fig. 4H). Thus, the aberrant phenotypes caused by MYD88 mutation appear hardwired into B cells and show little dependence on costimulation.

TFH fulfill a gatekeeper function ensuring that GCBs that develop a high affinity for the antigen are preferentially selected to survive, expand, and exit as long-lived effectors (2, 29). Given the observations above, we assessed antigen specificity in our Rosa26YFP-harboring models. NP-OVA–immunized chimeric mice showed the expected overrepresentation of total mutant GCBs (Fig. 4I, left). However, the relative frequency of cells with high affinity for the antigen (NP+) was significantly lower among mutant GCB than for WT (Fig. 4I, right). More importantly, among the expanded GC-derived mutant MBC pool, there was a dramatically lower fraction of cells with detectable NP affinity (Fig. 4J). These data suggest that MYD88 mutations enable highly permissive GC transit and exit, which could facilitate the spurious expansion and persistence of B-cell clones.

Myd88 Mutations Trigger an Aged/Autoimmune-like Program in GCBs

To gain mechanistic insight into the observed phenotypes, we conducted further analysis of RNA-seq profiles (Fig. 2G). Differential expression analysis identified Myd88L252P-driven signatures in DZ and LZ GCBs (|FC|>1.5; FDR<0.05), which were skewed toward gene activation (Fig. 5A; Supplementary Fig. S5A; Supplementary Table S1). Pathway analysis revealed enrichment for ABC-DLBCL, advanced-stage DLBCL, and WM signatures, supporting that our models recapitulate MYD88L265P effects in human lymphomas (Fig. 5B; Supplementary Fig. S5B; Supplementary Table S1). Accordingly, we saw enrichment for NF-kB–regulated genes, the central cascade activated by MYD88L265P (Fig. 5B; Supplementary Fig. S5B; ref. 30). We further saw depletion of TFH signatures (Fig. 5B; Supplementary Fig. S5B), partly driven by downregulation of the transcription factors Jun and Fos. We also observed enrichment for cell migration and chemotaxis signatures (Fig. 5B; Supplementary Fig. S5B), which could relate to the MBC-like program in GCBs (Fig. 4A), but also to the highly prevalent extranodal presentation of MYD88L265P tumors. Related to cell motility, Myd88L252P LZ GCB downregulated Rgs13 (Fig. 5A), a negative modulator of CXCR4 function (31), which could contribute to the observed DZ skew (Fig. 2D). Myd88L252P LZ GCBs also upregulated Il13ra1 (Supplementary Table S1), which pairs with the IL4 receptor and signals through overlapping effectors (32), providing a plausible mechanistic explanation to the enhanced response to IL4 by Myd88L252P B cells (Fig. 3I).

Beyond the aforementioned profiles, the most prominent signal in Myd88L252P GCBs related to IFN signaling and IFNγ in particular (Fig. 5B; Supplementary Fig. S5B). IFNγ not only instructs B-cell function against infections but also drives autoimmune phenotypes (33, 34). Indeed, our analysis showed enrichment for signatures related to immune responses and the autoimmune disorder systemic lupus erythematosus (Fig. 5B). IFNγ induces the expression of the transcription factor T-BET in B cells and drives the formation of “aged/autoimmune” B cells (AiBC; refs. 35–37). AiBCs are an MBC subpopulation, phenotypically distinguishable as T-BET+ and/or CD11c+ (38), that expand and differentiate into PCs responsible for pathogenic autoantibody production (36). B cells with similar phenotypes accumulate during viral/parasitic infections and in aged healthy females (38). Interestingly, Myd88L252P GCBs showed Tbx21 (T-BET) and Itgax (CD11c) upregulation (Fig. 5A; Supplementary Fig. S5A) by RNA-seq, a finding confirmed by RT-qPCR in independent mice (Supplementary Fig. S5C). Enhanced CD11c (Fig. 5C) and T-BET (Fig. 5D) protein expression was further observed in Myd88L252P GCBs driven by SRBC or alternative antigens (Supplementary Fig. S5D). In line with T-BET induction, genes with T-BET binding motifs in their promoter were overrepresented among upregulated genes in Myd88L252P LZ GCBs (Fig. 5E). Similarly, these genes matched those downregulated in T-BET knockout MBCs (Fig. 5F; ref. 39). These findings suggest that aberrant T-BET expression induces transcriptional rewiring of Myd88L252P GCB. Myd88L252P GCBs showed upregulation of other AiBC-related genes, including Itgam (CD11b), Fcrl5, Tlr7, and Cxcr3 (Fig. 5A; Supplementary Fig. S5E; refs. 38–40). Beyond individual markers, Myd88L252P GCBs showed significant enrichment for canonical AiBC signatures (Fig. 5G; Supplementary Fig. S5F; ref. 41). In all, Myd88L252P induced a program in GCBs that closely resembles that of pathogenic B cells driving autoimmune disorders.

Induction of an AiBC Program Is a Common Feature among MCD Founder Mutations

In addition to IFNγ, TLR activation is typically required to generate AiBCs (40). Because MYD88 is a critical signaling hub for most TLRs, the AiBC-related phenotype could pertain to MYD88L265P but not to MCDs as a class. Hence, we explored whether TBL1XR1 mutations would have similar effects. TBL1XR1 is a structural component of the SMRT/HDAC3 corepressor complex (22) with no evident functional link to MYD88. However, the transcriptome of Myd88L252P GCB showed significant enrichment for that of Tbl1xr1MUT GCB (Fig. 5H; Supplementary Fig. S5G). Further analysis of RNA-seq data from Tbl1xr1MUT GCB (22) revealed differential upregulation of AiBC markers, including Tbx21, Itgax, and Itgam (Fig. 5I), a finding confirmed by RT-qPCR in independent mice (Fig. 5J). Accordingly, Tbl1xr1MUT GCBs showed protein-level upregulation of T-BET (Fig. 5K), CD11c (Fig. 5L), and TLR7 (Supplementary Fig. S5H). Furthermore, as observed for Myd88L252P, Tbl1xr1MUT GCBs exhibited transcriptional enrichment for genes downregulated upon T-BET knockout (Fig. 5M) and for canonical AiBC signatures (Fig. 5N). These data suggest that the acquisition of an AiBC-like program is a common prevalent feature in MCD transformation, which is triggered by mechanistically distinct founder mutations.

MCD Mutations Cause a Cumulative Expansion of AiBC-like MBC

Given the transcriptional imprint exerted by T-BET in GCBs harboring MCD founder mutations, we explored whether this resulted in the generation of AiBC-like MBCs, something of particular relevance considering that these mutations aberrantly increase MBC output (ref. 22 and results herein). Notably, a significantly higher fraction of GC-derived MBCs coexpressed the canonical AiBC markers CD11b/CD11c in Myd88L252P mice (Fig. 6A). Accordingly, a higher proportion of Myd88L252P MBCs expressed T-BET (Fig. 6B). Studies in Rosa26YFP;Cγ1Cre;Tbl1xr1MUT animals revealed a similar expansion of CD11b+CD11c+ (Fig. 6C) and T-BET+ (Fig. 6D) MBCs.

Although AiBC generation was first described as absolutely dependent on CD40 signaling (42), recent studies suggest this could be context-dependent (43). Given the observed lower dependency on CD40 stimulation among Myd88L252P B cells, we asked whether the AiBC-like MBC expansion would occur under poor costimulation. CD40L-blocking antibodies reduced WT CD11c+ MBCs by ∼50%, whereas mutant CD11c+ MBC abundance remained elevated and comparable to that in IgG control–treated mice (Fig. 6E; Supplementary Fig. S6A), suggesting little-to-no costimulation is needed for mutant B cells to follow this cell fate.

CD19Cre;Myd88L252P mice, which express the mutation in all B cells, develop lymphadenopathy and occasional lymphomas with old age (median survival ∼70 weeks; ref. 13). We explored whether AiBC-like MBCs would also expand in this model. At 25 weeks of age, a time point at which CD19Cre;Myd88L252P mice do not show evidence of lymphoproliferative disease (13), total MBCs were expanded, and, within this population, there was a significant overrepresentation of AiBC-like (T-BET+CD11c+) phenotypes (Fig. 6F; Supplementary Fig. S6B). NBs did not express these markers, suggesting the phenotype was acquired only after activation (Supplementary Fig. S6C). Notably, mutant AiBC-like MBCs manifested a more active proliferative phenotype than WT counterparts, as per Ki-67 staining (Fig. 6G). Such differences were absent in non–AiBC-like MBCs (Supplementary Fig. S6D). This prompted us to explore whether AiBC-like MBCs progressively accumulated during malignant transformation. Hence, we conducted longitudinal tracking of B cells in Myd88L252P aging mice (20–90 weeks). Strikingly, mutant mice showed increasing accumulation of T-BET+CD11c+ MBCs (Fig. 6H), whereas there was little change in sex- and age-matched WT animals. Similar results were obtained when defining AiBC-like MBCs as CD11b+CD11c+ or CD11b+T-BET+ (Supplementary Fig. S6E and S6F). Conversely, we found little splenic plasmacytic differentiation (CD138+ cells), even at old age (Fig. 6I), suggesting these cells do not play a leading role in the longitudinal transformation.

To gain insights into the origin and trajectory of AiBC-like MBCs, we isolated this and other B-cell subsets from CD19Cre;Myd88L252P/WT mice at 40 weeks of age (Supplementary Fig. S6G) and performed targeted BCR sequencing. Despite reports that Aicda can activate in developing B cells under BCR/TLR costimulation (44), NBs from mutant mice showed largely undetectable SHM levels (Fig. 6J). On the other hand, AiBCs exhibited elevated SHM levels (Fig. 6J), suggesting these transited through the GC or acquired a GCB-like phenotype during their formation/expansion. SHM in AiBCs was significantly higher than that in other MBCs, but still lower than in (spontaneous) GCBs in the same animals (Fig. 6K). Notably, AiBCs showed the highest clonality across all studied populations, as would be expected from prospective lymphoma precursors. Two animals in our longitudinal study presented overt B-cell lymphomas at the time of necropsy, one of which had extranodal peritoneal localization (Supplementary Fig. S6H). Although a fraction of all splenic activated (IgD) B cells expressed CD11b and/or T-BET in this animal, more than 90% of tumor cells expressed one or both of these (Fig. 6L). In all, these observations support a role for AiBC-like MBCs as prospective precursor populations for MCD lymphomas.

T-BET Supports the Fitness of MYD88-Mutant B Cells

As the master regulator of canonical AiBC, T-BET ablation results in the loss of this population and amelioration of autoimmune disease severity in animal models (36). The observed T-BET–driven GCB transcriptional program and AiBC-like MBC expansion in our models suggest a similar dependency may exist in MCD precursors. To test this, we ablated T-BET in nontransformed primary Myd88L252P B cells using CRISPR/CAS9 and assessed their fitness to form GCBs after transplantation into immunocompetent recipients. Only a minimal fraction of NBs from donor mice would be expected to recognize a given antigen, greatly limiting our capacity to study transferred cells. To overcome this, we crossed our models to incorporate an engineered BCR with defined specificity for NP (B1-8hi strain; ref. 45). Briefly, NP-specific NBs from B1-8hi;Cd45.1;Myd88L252P or B1-8hi;Cd45.1;Myd88WT mice were first primed to enable editing (46), nucleofected with CAS9 complexes carrying control or Tbx21 guide RNAs (gRNA), and adoptively transferred into WT recipients (Fig. 7A). A fluorescently labeled transactivating RNA was used to track effective nucleofection with CAS9 complexes (Supplementary Fig. S7A). Targeted sequencing 24 hours after nucleofection confirmed the presence of disruptive lesions at the intended loci (Supplementary Fig. S7B). Recipient animals were immunized with an NP–protein conjugate the day after cell transfer and profiled at the peak of the NP-induced GC. Approximately 10% of GCBs in recipients derived from gCtrl-treated B1-8hi;Cd45.1;Myd88L252P transferred B cells (Fig. 7B; Supplementary Fig. S7C). Strikingly, gTbx21-treated mutant donors manifested significantly impaired expansion, similar to that of B1-8hi;Cd45.1;Myd88WT donor B cells (Fig. 7B). As expected, Myd88L252P GCBs featured higher T-BET expression compared with WT (Fig. 7C). However, GCBs derived from gTbx21-treated B1-8hi;Cd45.1;Myd88L252P cells showed minimal T-BET expression, confirming efficient editing (Fig. 7C). In line with the observed loss of competitive fitness, gTbx21-treated cells showed a significant reduction in Ki-67 expression, reflecting their impaired proliferative status (Fig. 7D). T-BET ablation also significantly impaired the expansion of AiBC-like (CD11c+) MBCs derived from transferred cells (Fig. 7E). Conversely, WT B-cell fitness was unaltered by Tbx21 knockout (Supplementary Fig. S7D–S7G). In all, these results show that T-BET supports the competitive fitness of B cells harboring founder MCD mutations.

Human ABC-DLBCL Tumors Exhibit AiBC-like Features

In the context of autoimmune disorders, some AiBCs retain their transcriptional and phenotypic profiles despite T-BET downregulation following disease onset (41). To assess whether T-BET expression could be detected in human DLBCL, we first analyzed transcriptional profiles of primary tumors from the NCI (47) and British Columbia Cancer Agency (BCCA; refs. 48, 49) cohorts and found that ABC-DLBCLs showed significantly higher TBX21 expression than GCB-DLBCLs (Fig. 7F). When narrowing down to MCD-DLBCL, the significant difference was upheld (Supplementary Fig. S7H) despite the limited number of MCD cases. MCD showed the highest levels of TBX21 among ABC-DLBCL only after N1 tumors (another subtype thought to originate from MBC; ref. 9). RT-qPCR and Western blot (WB) profiling of TBX21/T-BET in human cell lines supported these findings (Supplementary Fig. S7I–S7K). These observations in clinical specimens are consistent with the accumulation of T-BET+ B cells in our preclinical models (Fig. 6H).

To provide greater evidence that AiBC-like phenotypes exist in human ABC-DLBCL, beyond TBX21, we analyzed published single-cell RNA-seq profiles from primary tumors (50). Most cases in that study (n = 10/17) were Epstein–Barr virus/hepatitis B virus–positive, which could drive the expansion of AiBC (38). After excluding these to avoid confounding effects (Fig. 7G), most ABC-DLBCLs (n = 5/7) showed a high proportion of cells with elevated expression of ITGAX and other canonical AiBC markers (e.g., CD22, FCRL5; ref. 51), whereas only a minor fraction of cells expressed these in GCB-DLBCLs (n = 2; Fig. 7H; Supplementary Fig. S7L and S7M).

Our models strongly suggest that the AiBC phenotype is linked to dissemination-prone DLBCLs. Disseminated ABC-DLBCL (stages III–IV; n = 60) showed a trend toward higher TBX21 expression than localized tumors did (stages I–II; n = 30; Fig. 7I). Given the small number of cases in the latter category, this analysis was likely underpowered to reach statistical significance. Still, disseminated ABC-DLBCL (but not localized cases) showed significantly higher TBX21 levels than localized (n = 100) or disseminated (n = 80) GCB-DLBCL (Fig. 7I). To complement this, we conducted T-BET IHC staining of ABC-DLBCL tissue microarrays (52). T-BET expression in tumor cells was variable and generally lower than in T cells in the same sections (Supplementary Fig. S7N). Still, in line with the mRNA data, we found that a fraction of disseminated ABC-DLBCL harbored T-BET+ tumor cells, whereas these were not detected in limited-stage cases (Fig. 7J).

T-BET Supports the Self-Renewal Capacity of MCD Tumor Cells

To test whether T-BET influences the fitness of fully transformed MCD-DLBCL, we ablated T-BET in cell lines using CRISPR/CAS9 and assessed their ability to outgrow from single cells as a measure of self-renewal capacity (Fig. 7K). Bulk sequencing 48 hours after the delivery of TBX21-directed CAS9 complexes revealed extremely high penetrance of targeted disruptive mutations (Fig. 7L, left column). Only a minor fraction of plated cells (7/200 and 11/200, for two independent gRNAs) underwent clonal expansion as compared with gCTRL-treated cells (78/200 outgrows; Fig. 7L, center column). Importantly, the few gTBX21-treated clones that did expand showed T-BET levels comparable to parental, suggesting these derived from cells that escaped TBX21 editing (Fig. 7L, right column). Conversely, TBX21 ablation in a GCB-DLBCL model only had a mild nonsignificant effect on clonal fitness (Supplementary Fig. S7O–S7R). These findings suggest that T-BET retains an important role beyond lymphomagenesis by supporting the clonogenic potential of fully transformed MCD tumor cells.

During an adaptive immune response, lack of costimulation results in B-cell death, preventing the misfiring and inappropriate engagement of B cells in inflammatory responses (2, 29). Here, we found that MYD88L256P alleviates this requirement, enabling B cells to activate, proliferate, and differentiate into long-lived MBCs even under poor costimulation. TBL1XR1 mutations also imprint pathogenic trajectories on B cells despite limited costimulation (22), highlighting a common theme in MCD lymphomagenesis. Such autonomous programs illustrate how B cells normally attuned to their niche and under strict surveillance may initiate and sustain transformation. Moreover, although T-cell help may be readily available to B cells undergoing transformation in lymphoid tissues, this may not be the case at extranodal sites. Immune-privileged sites, which are targeted by MYD88L256P lymphomas (53), represent an extreme scenario, in that they offer a significantly different stromal landscape and greatly restrict lymphocytic infiltration, so they are likely ill-equipped to support transformation programs reliant on extensive B/T-cell cross-talk. Our results suggest that MYD88 mutations would still enable lymphomagenesis in such contexts. This is different from lymphomas such as classic Hodgkin, in which transformation and tumor maintenance rely on strong costimulation (54).

Our results show that MYD88 mutations endow B cells with a lower threshold and even semiautonomous capacity to engage in proliferative responses to external signals, consistent with studies showing increased proliferation of MYD88MUT B cells (55, 56). We find that this property leads to increased competitive fitness against WT B cells. Along these lines, we observed that mutant GCB formation and expansion occurred even in the absence of immunization. Age-associated spontaneous GC formation can be supported by TLR signaling (24). Beyond the direct effects of the MYD88 mutation downstream of TLRs, Myd88L252P GCB exhibited upregulation of Tlr3 and Tlr7, which could further contribute to these phenomena. TLRs not only activate by sensing conserved molecular patterns in pathogens but can also become aberrantly stimulated by self-antigens (57). Notably, MCD and primary extranodal DLBCLs distinctively harbor BCRs that solely or promiscuously recognize self-antigens (9, 58). Accordingly, MCD cell lines depend on autoreactive BCR signaling for their survival in vitro (23). Self-reactivity could also serve as a source of continuous or repeated activation for lymphoma precursors. Self-reactive antibodies have been detected in aged mice expressing Myd88L252P in all B cells (14). Although the early introduction of the mutation could artifactually alter central tolerance mechanisms in the BM, recent findings showed that spontaneous GCBs from animals where Myd88L252P was expressed in mature B cells harbored BCRs with similar properties to the self-reactive receptors in MCD cell lines (59). Here, we largely limited Myd88L252P expression to activated mature B cells, in line with the current understanding that founder mutations most likely arise as aberrant SHM by-products (8). Normally, lack of costimulation further prevents the expansion of self-reactive B cells that escaped central tolerance checkpoints (2), and even anergic self-reactive B cells awakened by antigen mimicry need to mutate their BCRs away from self to “redeem” themselves and be positively selected (29). Here, we show that MYD88-mutant GCs are significantly more permissive in terms of antigen specificity, which could set the stage for the aberrant activation and selection of clonal precursors driven by self-reactivity.

Previous studies on the effects of MYD88 mutations focused exclusively on plasmacytic fates, reporting abnormally elevated IgM antibodies and increased plasmablast proliferation in aged animal models (55, 60). Although informative, these did not delineate transformation trajectories or elucidate the selective advantage conferred by MYD88L265P as a founder mutation. We and others recently showed that MBCs are the most likely MCD precursor (22, 61), challenging the long-held belief that these arise from plasmablasts (17). Similarly, WM, a disease in which >90% of tumors carry MYD88L265P and tumor cells exhibit plasmacytic features, is thought to derive from MBC (62). In line with this revised framework, we now show that MYD88 mutation not only provides a competitive advantage to B cells but also shepherds them toward the MBC fate. The fact that early mutations in two functionally unrelated genes, namely, TBL1XR1 and MYD88, harness overlapping pathogenic trajectories, is a bona fide example of convergent evolution during lymphomagenesis.

MBCs represent a heterogeneous and largely uncharted population. Here, we found that MCD founder mutations introduce a T-BET–driven transcriptional program in GCBs and cause the cumulative expansion of AiBC-like MBCs. Unlike other MBCs, AiBC reactivation can be supported not only through BCR engagement and canonical costimulation (63) but also through TLR activation (35). TLR stimulation ex vivo is enough to induce T-BET expression in B cells, and increased TLR7 dosage promotes AiBC expansion (41). In turn, T-BET induces AICDA expression in MBC (39), which may favor the accumulation of mutations outside of a canonical GC context. Such plasticity and increased autonomy make AiBCs ideal vectors for driving pathogenic processes, as first described for autoimmune disorders (35–37). Notably, mutations similar to those in ABC-DLBCLs were identified in self-reactive pathogenic MBC in patients with Sjogren syndrome (SS; ref. 64), a rheumatic disease. Ours is the first demonstration that lymphoma mutations directly promote the generation of AiBC-like MBC in response to foreign antigens or even in the absence of immunization. A relationship between autoimmune disorders and lymphomas has been extensively reported (65), whereby patients with lupus, SS, or other autoimmune disorders show increased risk of developing aggressive lymphomas. One study on patients with lupus who developed DLBCL found most tumors corresponded to the non-GCB subtype (66). Also, a third of patients had only extranodal involvement at DLBCL diagnosis, and their onset was significantly shorter than for nodal disease alone. Given that MCDs fall into the non-GCB subclass (9), show significant association with extranodal disease (8, 47), and share a mutational landscape with primary extranodal tumors (9, 53), it is tempting to speculate that MCD-DLBCL may be disproportionately prevalent among patients with autoimmune disorders. Our finding that lymphomas and autoimmune disorders harness similar pathogenic populations provides a rationale for these clinical observations and prompts us to think of them as a spectrum rather than separate entities. Although our findings more directly support such conceptual framework for MCD and primary extranodal DLBCLs, BN2- and A53-DLBCLs also harbor self-reactive-prone BCRs (9), suggesting this may be a common theme among ABC-DLBCLs. Alternative stimuli, such as chronic infections, could similarly drive the production and restimulation of AiBC-like MBCs involved in lymphomagenesis. A clinical association between chronic viral infections and DLBCL has been made (67–69), although this appears specific to BN2-DLBCLs (70).

DLBCLs are most frequently diagnosed among people in their seventh decade, and the incidence of ABC-type tumors increases with age (71). It has been hypothesized that this skew reflects a change in normal B-cell populations during aging (71). Clonal expansion of B cells, overall reduction in B-cell diversity (72), and increased usage of the self-reactive-prone VH4-34 BCR (73) have been observed in aged individuals with no evident hematologic malignancies. This further supports a model in which a clonal and potentially autoreactive B-cell population, such as AiBC, is directly involved in lymphomagenesis. Our findings indicate that MCD founder mutations instruct these phenotypes. The incidence of MYD88L265P was also significantly higher in tumors from older individuals (74). Mutations targeting MYD88 have also been recently reported in lymphoid clonal hematopoiesis of indeterminate potential (L-CHIP; ref. 75), and normal precursors and mature B cells from patients with lymphoma (76), supporting the idea that MCD transformation involves a longitudinal process (Fig. 7M). Although these observations also indicate that MCD founder mutations can be acquired early in the B-cell lineage, our findings suggest that AiBC phenotypes manifest at the mature B-cell stage and support the idea that these cells acquire a GC-like state at some point during transformation.

The identification of precursor populations for aggressive and potentially incurable lymphomas remains a long sought-after but elusive goal. Here, we show that founder mutations associated with extranodal DLBCL give rise to a phenotypically distinguishable MBC subpopulation that differentially accumulates in time. In line with their prospective role as precursor cells, canonical AiBCs disseminate and can be found in circulation and distributed to many tissues (77). These observations raise the provocative idea that an accumulation of AiBC-like MBCs may be detectable in patients with lymphoma preceding primary tumor onset and/or ensuing relapses, paving the way for risk-based stratification and prophylactic interventions. This could further apply to premalignant conditions known to harbor MYD88L265P, such as monoclonal gammopathy of undetermined significance (78) or L-CHIP (75). Given their dismal outcome, patients at risk of developing central nervous system relapses routinely receive prophylactic treatment with methotrexate, a broad immunosuppressant, but recent studies have shown this to be largely ineffective (79). In this regard, we have unveiled a new axis involved in extranodal DLBCL pathogenesis amenable to therapeutic targeting. Despite advances in direct pharmacologic inhibition (80, 81) or proteolysis-targeting chimeras (82, 83) against transcription factors, blocking of signaling cascades upstream of T-BET, including the use of TLR7/9 inhibitors (84), appears as an alternative that could be more readily implemented. In addition to exploring these aspects, future studies should determine the exact mechanisms of actions of T-BET and other AiBC features in the context of extranodal lymphomagenesis and explore their potential value as predictive biomarkers for dissemination.

Mouse Models

Animal care was in strict compliance with institutional guidelines established by Weill Cornell Medicine (WCM), the Guide for the Care and Use of Laboratory Animals (National Academy of Sciences, 1996), and the Association for Assessment and Accreditation of Laboratory Animal Care International. The Research Animal Resource Center of WCM (protocol #2011-0031) and the Landesamt für Natur, Umwelt und Verbraucherschutz NRW (LANUV; (AZ: 84-02.04.2014.A146, 84-02.04.2017.A131, 81-02.04.2019.A009) approved all mouse procedures. The following strains were obtained from The Jackson Laboratory: C57Bl/6J (CD45.2, stock 000664; RRID:IMSR_JAX:000664), C57BL/6-Myd88tm1.1Rein/J (Myd88-L252P, stock 029349; RRID:IMSR_JAX:029349), Cγ1-Cre (stock 010611; RRID:MMRRC_010611-UCD), CD19-Cre (stock 006785; RRID:IMSR_JAX:006785), B6.SJL-PtprcaPepcb/Boy (CD45.1, stock 002014; RRID:IMSR_JAX:002014), Rosa26-lox-stop-lox-YFP (Rosa26YFP; stock 006148; RRID:MMRRC_006148-UCD), and B1-8hi (stock 007594; RRID:IMSR_JAX:007594). The generation of the conditional Tbl1xr1-D370Y mouse model has been described (22). Animals were housed in specific pathogen–free facilities. Experiments were conducted using aged and sex-matched littermates wherever possible. Experiments were designed to include male and female specimens in all groups, and no sex-based influence/bias was detected in the observations made in this work. Unless stated otherwise in the text, animals were 8 to 12 weeks of age at the time of experimentation. BM transplantations to generate chimeric animals, immunization strategies, and use of CD40L-blocking antibodies were all conducted as described (22).

Cell Lines

The DLBCL cell lines OCI-Ly1 (CVCL_1879; male origin; RRID:CVCL_1879), OCI-Ly3 (CVCL_8800; male origin; RRID:CVCL_8800), OCI-Ly8 (CVCL_8803; male origin; CVCL_8803), and OCI-Ly10 (CVCL_8795; female origin; RRID:CVCL_8795) were grown in Iscove's Modified Dulbecco's Media (12440061; ThermoFisher Scientific) supplemented with 10% FBS and penicillin G/streptomycin; U2932 (CVCL_1896; female origin; CVCL_1896), HBL1 (CVCL_4213; male origin; RRID:CVCL_4213), TMD8 (CVCL_A442, male origin), MD901 (CVCL_D709; male origin; RRID:CVCL_A442), RIVA (CVCL_1885; female origin; RRID:CVCL_1885), RC-K8 (CVCL_1883; male origin; RRID:CVCL_1883), and HLY-1 (CVCL_H207; RRID:CVCL_H207) were grown in RPMI medium (10-040-CV; Corning) supplemented with 10% FBS, penicillin G/streptomycin, L-glutamine, and HEPES. All cells were grown in incubators at 37°C in a 5% CO2 atmosphere. Cells were maintained in culture for up to 4 to 6 weeks between the time of thawing and experimentation. HBL-1, HLY-1, and U2932 were obtained from Jose Martinez-Climent (Universidad de Navarra, Pamplona, Spain); OCI-Ly3 were obtained from Anas Younes (Memorial Sloan Kettering Cancer Center, New York, NY; OCI-Ly1, OCI-Ly7, OCI-Ly8, and OCI-Ly10 were obtained from the Ontario Cancer Institute; TMD8 was obtained from Louis M. Staudt (NCI); and RC-K8 and RIVA were obtained from the German Collection of Microorganisms and Cell Cultures GmbH (DSMZ). Cell line authentication was performed at IDEXX BioResearch, using methods recommended by the American National Standards Institute (ASN-0002-2011). Cell lines were confirmed to be of human origin and tested for evidence of cross-species contamination (mouse, rat, Chinese hamster, and African green monkey). All cell lines were routinely tested for Mycoplasma contamination using a MycoAlert PLUS Detection Kit (LT07-705).

FC Analysis and Cell Sorting

Single-cell suspensions from mouse spleens, lymph nodes, BM, or tumors were stained using the following fluorescent-labeled anti-mouse antibodies: from eBioscience ThermoFisher Scientific: PE-Cy5.5 anti-CD11c (35-0114-80, dilution 1:200; RRID:AB_11219866), PE-Cy7 anti-CD11b (25-0112-82, dilution 1:400; RRID:AB_469588), APC anti-CD38 (17-0381, dilution 1:500; RRID:AB_469381), PE anti-CXCR4 (12-9991, dilution 1:400; RRID:AB_891391), PerCP-Cy5.5 anti-CD45.1 (45-0453, dilution 1:500; RRID:AB_1107003), FITC anti–PD-1 (11–9985, dilution 1:150; RRID:AB_465472); from BD Biosciences: AF647 anti–active caspase-3 (560626, dilution 1:100; RRID:AB_1727414), BUV615 anti-CD45 (752418, dilution 1:500; RRID:AB_2917432), BV421 and BV711 anti–Ki-67 (562899 and 563755, dilution 1:500; RRID:AB_2686897 and RRID:AB_2738406), FITC, PE-Cy7, and BV786 anti-B220 (553087, 552772 and 563894, dilution 1:500; RRID:AB_394617, RRID:AB_394458, and RRID:AB_2738472), BV421, BUV805, and PE-Cy7 anti-FAS (562633, 741968, and 557653, dilution 1:500; RRID:AB_2737690, RRID:AB_2871273, and RRID:AB_396768), BUV563 and BUV395 anti-CD38 (741271 and 740245, dilution 1:500; RRID:AB_2870812 and RRID:AB_2739992), PE-Cy7 anti-CXCR5 (560617, dilution 1:100; RRID:AB_1727521), PE-Cy7 anti-CD86 (560582 and 564198, dilution 1:300; RRID:AB_1727518 and RRID:AB_2738663), BV510 anti-IgD (563110, dilution 1:500; RRID:AB_2737003), APC and BUV737A anti-CD138 (558626 and 564430, dilution 1:500; RRID:AB_1645216 and RRID:AB_2738805), FITC anti-CD19 (553785, dilution 1:500; RRID:AB_395049), FITC and AF647 anti-GL7 (553666 and 561529, dilution 1:500; RRID:AB_394981 and RRID:AB_10716056); from BioLegend: APC anti-CD11b (101212, dilution 1:400; RRID:AB_312795), BV785 and APC-Cy7 anti-CD11c (117336 and 117324, dilution 1:200; RRID:AB_2565268 and RRID:AB_830649) BV711 and APC anti–T-BET (644820 and 644814, dilution 1:100; RRID:AB_2715766 and RRID:AB_10901173), PercP-Cy5.5 anti-CD138 (142510, dilution 1:500; RRID:AB_2561601) Spark NIR 685 anti-CD19 (115567, dilution 1:500; RRID:AB_2819828), AF488 anti-IgD (405717, dilution 1:500; RRID:AB_10730618), APC-Cy7 anti-CD4 (100414, dilution 1:500; RRID:AB_312699), APC-Cy7 anti-CD45.1 (110716, dilution 1:500; RRID:AB_313505), PerCP-Cy5.5 anti-CD45.2 (109828, dilution 1:500; RRID:AB_893350), APC anti-CD3 (100235, dilution 1:500; RRID:AB_2561455), APC-Cy7 and PE anti-B220 (103224 and 103208, dilution 1:500; RRID:AB_313007 and RRID:AB_312993), PerCP-Cy5.5 anti-GL7 (144610, dilution 1:500; RRID:AB_2562979), PerCP-Cy5.5 anti-FAS (152610, dilution 1:500; RRID:AB_2632905), BV605 anti-CD86 (105037, dilution 1:300; RRID:AB_11204429), PE anti-TLR7 (160004, dilution 1:100; RRID:AB_2876562); and from Biosearch Technologies: PE NP (N-5070-1, dilution 1:100). NIP-haptenated FITC was obtained from M.J. Shlomchik (University of Pittsburgh, Pittsburgh, PA). A Zombie NIR Fixable Viability Kit (423105, BioLegend), a LIVE/DEAD Fixable Violet Dead Cell Stain Kit (L34963; ThermoFisher Scientific), or DAPI (D1306; Thermo­Fisher Scientific) was used for exclusion of dead cells. Intracellular stains, AnnexinV/DAPI stains, and detection of EdU incorporation were performed as described (22). Proliferation was assessed using a CellTrace CFSE Cell Proliferation Kit (C34554; ThermoFisher Scientific) according to the vendor's protocol. Data were acquired on a BD Fortessa or BD Symphony instrument (BD Biosciences) or a Cytek Aurora spectral FC analyzer (Cytek) and analyzed using a FlowJo software package (BD Biosciences; RRID:SCR_008520).

When B-cell populations were sorted, single-cell suspensions were preenriched in B cells using positive selection with anti-B220 magnetic microbeads (130-049-501; Miltenyi Biotec) or negative selection with the EasySep Mouse B-Cell Isolation Kit (19854; STEMCELL Technologies). The stated populations were then isolated using a BD FACSAria II or a BD Influx cell sorter (BD Biosciences).

Primary B-cell Cultures

Total splenocytes were harvested from 8- to 16-week-old naïve mice, and NBs were isolated using negative selection with CD43 magnetic beads (130-049-801; Miltenyi Biotec) in accordance with the manufacturer's protocol. In some experiments, cells were stained with a CellTrace proliferation dye as noted above. Cells were seeded at 1 × 106 cells/mL in RPMI media with 10% FBS, penicillin G/streptomycin, MEM nonessential AA (11140050, Thermo Fisher Scientific), 50 μmol/L 2-Mercaptoethanol (21985023, Thermo Fisher Scientific), containing the indicated concentrations of murine recombinant IL4 (0–25 ng/mL; 404-ML; R&D Systems) and a functional grade anti-CD40 monoclonal antibody (0–1 μg/mL; 16-0402-82, Thermo Fisher Scientific; RRID:AB_468945). Cells were incubated at 37°C with 5% CO2, and the culture medium was renewed every 2 to 3 days.

CRISPR Editing of DLBCL Cell Lines and Primary B Cells

Human cell lines were electroporated using an Amaxa Nucleofector and the SF Cell Line 4D-Nucleofector X Kit (PBC2-22500; Lonza) to incorporate a recombinant Cas9 nuclease (Alt-R S.p. Cas9 Nuclease V3, #1081058), control (#1072544 or #1072545), or TBX21-targeting gRNAs (Hs.Cas9.TBX21.1.AB “#1”: 5′-GCGGUACCAGAGCGGCAAGU-3′; Hs.Cas9.TBX21.1.AC “#2”: 5′-GAUUAAACUUGGACCACAAC-3′), electroporation enhancer (#1075915), and a tracrRNA-ATTO550 (#1075927; all from Integrated DNA Technologies) following the vendor's recommendations. For primary murine B cells, the P4 Primary Cell 4D-Nucleofector X Kit L (V4XP4012; Lonza) was used, along with control or Tbx21-targeting (Mm.Cas9.TBX21.1.AA: 5′-UCCAAGGAAGCGACCCGGCG-3′; Mm.Cas9.TBX21.1.AC: 5′-GGUUGAACUUGGACCACAAC-3′; Integrated DNA Technologies) gRNAs.

B-cell Adoptive Transfer

For B-cell adoptive transfers, total splenocytes were harvested from 8- to 12-week-old donor mice (Cd45.1/1 or Cd45.1/2), and B cells were isolated using negative selection as described above. To increase the number of productive (NP-binding) B cells in the mix, cells were further subjected to Igκ light chain–based depletion. To this end, an anti-Igκ antibody (409502, BioLegend; RRID:AB_2563297) biotinylated in-house (ab201796; Abcam) was added during magnetic B-cell isolation. Cells were grown overnight in complete media containing 25 ng/mL murine recombinant IL4 and 1 μg/mL of an anti-CD40 antibody. Cells were nucleofected with ATTO-labeled CAS9 ribonucleoprotein complexes as stated above and were allowed to recover overnight in complete media supplemented with IL4 and the CD40 agonist. The percentage of ATTO+ and NP-binding cells in each population was determined by FC to allow for normalization across conditions. Cells were allowed to rest in complete media without IL4/anti-CD40 for >2 hours prior to transfer. A number of mature B cells corresponding to 1 × 105 ATTO+NP+ B cells were injected i.v. into C57Bl/6J recipient mice (Cd45.2/2). Recipient animals were immunized with an NP conjugate 16 hours after cell transfer and euthanized for analysis at the stated time points.

Quantitative Real-Time PCR

Total RNA extracts and cDNA synthesis were conducted as described (22). Expression of genes of interest was detected using a Fast SYBR Green Master Mix (4385614; Thermo Fisher Scientific) on a QuantStudio6 Flex Real-Time PCR System (Thermo Fisher Scientific). Gene expression was normalized to Actin or GAPDH levels using the ΔΔC(t) method. Primer sequences were as follows (5′→3′): hTBX21.F: GGTTGCGGAGACATGCTGA; hTBX21.R: GTAGGCGTAGGCTCCAAGG; mTbx21.F: AGCAAGGACGGCGAATGTT; mTbx21.R: GGGTGGACATATAAGCGGTTC; mItgax.F: CTGGATAGCCTTTCTTCTGCTG; mItgax.R: GCACACTGTGTCCGAACTCA; and mItgam.F: ATGGACGCTGATGGCAATACC; mItgam.R: TCCCCATTCACGTCTCCCA.

Targeted Genomic Sequencing

Genomic DNA from primary B cells or human DLBCL cell lines was extracted as described (22). DNA concentration was determined using Qubit Fluorometric Quantification, and the amount of template DNA across samples was normalized for amplification. The CRISPR-targeted Tbx21 or TBX21 loci were PCR-amplified using the following primers (5′→3′): hTBX21.AB.F: AGGATGTTTGTGGACGTGGT; hTBX21.AB.R: CAGGAAGCCAGAAACAGGAG; hTBX21.AC.F: AGGTGTCGGGGAAACTGAG; hTBX21.AC.R: CCTGTCTCCCTACGCTGAAG; and mTbx21AA.F: CTC AGCTTCCCAGACACCTC; mTbx21AA.R: GACCAACAGCATCGTTTCTTC. PCR products were resolved by agarose gel electrophoresis, bands of interest were excised, and DNA was retrieved using the QIAquick Gel Extraction Kit (28706 × 4; Qiagen). Library preparation, amplicon sequencing, and variant calling were performed by GENEWIZ or the Massachusetts General Hospital Center for Computational and Integrative Biology DNA Core.

BCR sequencing from primary murine cells was conducted by Adaptive Biotechnologies using an ImmunoSEQ Assay (85) as described (86). BCR repertoire analysis, including clonality and mutation burden calculations, was performed using the immunoSEQ Analyzer 3.0 (Adaptive Biotechnologies).

RNA-seq

Library preparation, sequencing, and post-processing of the raw data were performed at the Genomics Core at WCM, as described (22). Paired-end sequencing (PE75 × 2) was performed on an Illumina NextSeq 500 instrument (Illumina). Hierarchical clustering was performed using Euclidean distance of log transcripts per million (TPM) + 0.1 values of genes within the top 5th percentile of SD across replicates and Ward's minimum variance. Gene set enrichment analysis (GSEA) was performed using the GSEA algorithm as described in (87). Pathway analysis was performed using the PAGE algorithm (88).

Histology and IHC

Murine tissue preparation and staining were conducted by the Laboratory of Comparative Pathology at Memorial Sloan Kettering Cancer Center as described (22, 89). The following primary antibodies were used for IHC: biotin-conjugated anti-B220 (550286; BD Biosciences; RRID:AB_393581) and anti-PNA (B1075; Vector Laboratories; RRID:AB_2313597). IHC on human specimens was performed at the BCCA as described previously (49, 52), using an anti–T-BET (4B10) antibody (561262; BD Biosciences; dilution 1:50; RRID:AB_10565981). T-BET staining was semiquantitatively assessed on tumor cells using HistoScore (HS = I × P): intensity (I = [1–3]) and percentage of positive cells (P = [0–100]). Specimens with HS > 10 were defined as T-BET–positive.

Cell Lysis and Immunoblotting

Whole-cell protein lysate preparation and SDS-PAGE analysis were performed as described (22), using the following primary antibodies: β-ACTIN (C-4; sc-47778; Santa Cruz Biotechnology; RRID:AB_626632), T-BET (D6N8B; #13232; RRID:AB_2616022), IκBα (44D4; #4812; RRID:AB_10694416), and Phospho-IκBα (Ser32; 14D4; #2859S; RRID:AB_561111; Cell Signaling Technology).

Data Availability

RNA-seq data from this article have been deposited in the Gene Expression Omnibus database (RRID:SCR_005012) under accession number GSE201058. Gene expression data from individuals with de novo DLBCL from the NCI (47), BCCA (49), and Sun Yat-sen University Cancer Center (50) cohorts had been previously published. The code used for analysis is available upon request.

Statistical Analysis

Statistical parameters, including the exact value and definition of n, precision measures (mean ± SEM or SD), and statistical significance are reported in figures and figure legends. No statistical methods were used to predetermine animal sample sizes, but these were decided based on reports using similar models and approaches (13, 14, 22, 89). Statistical analysis was conducted using GraphPad Prism 8 (GraphPad Software; RRID:SCR_002798) or the R statistical language scripts and packages specified. Data were judged to be statistically significant when P < 0.05. Asterisks in figures denote statistical significance (*, P < 0.05; **, P < 0.01; ***, P < 0.001).

M.A. Rivas reports grants from the American Society of Hematology during the conduct of the study. M. Xia reports grants from Janssen outside the submitted work. C. Meydan reports personal fees from Thorne HealthTech outside the submitted work. C.E. Mason reports personal fees from Tempus Labs and is cofounder of Onegevity and Biotia outside the submitted work. C. Steidl reports personal fees from Bayer, and grants from Epizyme and Trillium Therapeutics outside the submitted work. D.W. Scott reports personal fees from AbbVie, AstraZeneca, and Incyte, grants and personal fees from Janssen, and grants from Roche outside the submitted work, as well as a patent describing the use of gene expression to subtype aggressive B-cell lymphomas pending, issued, and licensed to NanoString Technologies. H.C. Reinhardt reports grants from Deutsche Forschungsgemeinschaft, Deutsche Jose Carreras Leukåmie Stiftung, Else Kröner-Fresenius Stiftung, and Deutsche Krebshilfe during the conduct of the study; grants, personal fees, and other support from AstraZeneca and Gilead, personal fees and other support from AbbVie, Bristol Myers Squibb, Novartis, and Roche, personal fees from Merck and Vertex, and nonfinancial support and other support from SinABiomedics outside the submitted work; and is a cofounder of CDL Therapeutics GmbH. A.B. Pernis reports personal fees from Ono Pharmaceutical outside the submitted work, as well as a patent for US 11,147,829 B2 issued. A.M. Melnick reports grants from Janssen, grants and personal fees from Epizyme and Daiichi Sankyo, and personal fees from Treeline outside the submitted work. No disclosures were reported by the other authors.

L. Venturutti: Conceptualization, resources, data curation, formal analysis, supervision, funding acquisition, investigation, visualization, methodology, writing–original draft, project administration, writing–review and editing. M.A. Rivas: Formal analysis, validation, investigation, project administration. B.W. Pelzer: Formal analysis, investigation, methodology, project administration. R. Flümann: Resources, investigation. J. Hansen: Resources, investigation. I. Karagiannidis: Investigation. M. Xia: Investigation, visualization, methodology. D.R. McNally: Data curation, formal analysis, investigation, visualization, methodology. Y. Isshiki: Investigation, methodology. A. Lytle: Formal analysis, investigation, methodology. M. Teater: Data curation, formal analysis, investigation, visualization, methodology. C.R. Chin: Data curation, formal analysis. C. Meydan: Data curation, formal analysis. G. Knittel: Resources, investigation, methodology. E. Ricker: Resources, methodology. C.E. Mason: Data curation, formal analysis. X. Ye: Resources. Q. Pan-Hammarström: Resources. C. Steidl: Resources. D.W. Scott: Resources. H.C. Reinhardt: Resources, formal analysis, supervision, funding acquisition, writing–review and editing. A.B. Pernis: Resources, formal analysis, methodology, writing–review and editing. W. Béguelin: Supervision, investigation, methodology, project administration, writing–review and editing. A.M. Melnick: Conceptualization, resources, formal analysis, supervision, funding acquisition, methodology, writing–original draft, project administration, writing–review and editing.

We thank all members of the Melnick lab for thoughtful discussions and suggestions, Mohamed Moustafa for his help with FC optimization, Hao Shen for his outstanding support with mouse colonies, the Genomics Core and Flow Cytometry Core (WCM), Molecular Cytology Core Facility (MSKCC), and Center of Comparative Medicine and Pathology (WCM/MSKCC). L. Venturutti is a Michael Smith Health Research BC Scholar and is funded by the BC Cancer Foundation, the Canadian Institutes of Health Research (Project Grant #180613), and The Leukemia & Lymphoma Society (LLS)-TRP 6663-23. M.A. Rivas was funded by an ASH Junior Faculty Scholar Award. B.W. Pelzer was funded by Deutsche Krebshilfe (Mildred Scheel Nachwuchszentrum Grant #70113307). C.E. Mason was funded by Scientific Computing Unit, XSEDE Supercomputing Resources, the Starr Cancer Consortium (I7-A765, I9-A9-071, I13-0052), the Vallee Foundation, the WorldQuant Foundation, the Pershing Square Sohn Cancer Research Alliance, the NIH (R01MH117406, R01CA249054, R01AI151059, P01CA214274), and the LLS (9238-16, LLS-MCL-982). Q. Pan-Hammarström was funded by the Swedish Research Council, the Swedish Cancer Society, CIMED, Radiumhemmets research fund, and the Knut and Alice Wallenberg Foundation. A.B. Pernis was funded by the NIH (AR064883 and AR070146). E. Ricker was funded by a T32 Rheumatology Research Training Grant. H.C Reinhardt was funded by Deutsche Forschungsgemeinschaft (RE2246/13-1, SFB-1430-A09, SFB-1530-A01), Deutsche Jose Carreras Leukämie Stiftung (R12/08), Else Kröner-Fresenius Stiftung (EKFS-2014-A06, 2016_Kolleg.19), and Deutsche Krebshilfe (1117240 and 70113041). A.M. Melnick was funded by NCI-R35 CA220499 and LLS-SCOR 7012-16.

The publication costs of this article were defrayed in part by the payment of publication fees. Therefore, and solely to indicate this fact, this article is hereby marked “advertisement” in accordance with 18 USC section 1734.

Note: Supplementary data for this article are available at Cancer Discovery Online (http://cancerdiscovery.aacrjournals.org/).

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