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Record W4405043929 · doi:10.1182/blood-2024-198542

Follicular Dendritic Cells Represent a Therapeutic Vulnerability in Early Follicular Lymphoma

2024· article· en· W4405043929 on OpenAlexaff
Caitlin Gribbin, Dylan McNally, Ioannis Karagiannidis, Henna S. Nam, Hiranmayi Ravichandran, Baptiste Brauge, Karin Tarte, Amy Chadburn, Madhu M. Ouseph, Sebastian E. Carrasco, Christian Steidl, David W. Scott, Ari Melnick, Wendy Béguelin

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsSpinal Cord Injury BC
Fundersnot available
KeywordsFollicular lymphomaFollicular phaseFollicular dendritic cellsMedicineLymphomaImmunologyCancer researchBiologyInternal medicineAntigen-presenting cellImmune systemT cell

Abstract

fetched live from OpenAlex

Follicular lymphomas (FLs) arise from germinal center (GC) B cells and contain a rich tumor microenvironment (TME) including CD4+ and CD8+ T cells, macrophages, and lymphoid stromal cells, among which follicular dendritic cells (FDCs) are particularly abundant. FDCs interact with GC B cells through antigen presentation, secretion of BAFF, which binds to BAFFR to induce trophic signals, and secretion of CXCL13, which draws B cells into GCs via CXCR5. While the role of FDCs in FL is not fully understood, BAFFR expression has been associated with worse outcomes in diffuse large B-cell lymphoma. We hypothesized that FDCs 1) play a critical role in FL, primarily through BAFF signaling, 2) represent a therapeutic target in FL, and 3) are most amenable to targeting as a form of early intervention therapy for FL. We profiled the FL TME of 151 patient biopsies at the spatial level using imaging mass cytometry (IMC) and found that FDCs were highly prevalent and in close proximity to FL B cells. We previously showed that FDCs are especially abundant in both human and murine EZH2Y641F gain-of-function mutant FLs. To determine the functional relevance of these FDCs and the potential relevance of BAFF, we administered anti-BAFF blocking antibody to immunized mice bearing 50% WT and 50% mutant EZH2 B cells. BAFF blockade caused significantly greater depletion of EZH2Y641F GC B cells relative to WT (p<0.05), documenting a critical role for FDCs and BAFF in EZH2 mutant GC B cells. We generated and credentialed a bona fide FL mouse model, driven by GC-specific expression of BCL2 and EZH2Y641F. These EZH2/BCL2 mice develop lymphoid hyperplasia at 5 months and FL at 8 months. To investigate the changing composition of the TME in FL, we immunized a cohort of 25 EZH2/BCL2 mice and sacrificed 5 mice at 5 time points between 6 and 11 months. We extracted RNA from spleen containing lymphoma cells and the entire TME and performed qPCR on 93 genes, including cytokines and chemokines involved in GC intercellular signaling. BAFF transcript abundance was increased in EZH2/BCL2 relative to WT mice at all timepoints (p<0.05), supporting BAFF as potentially biologically relevant in FL. Given the relevance of the BAFF-BAFFR axis and mutant EZH2 dependency on FDCs, we next investigated the effects of BAFF and EZH2 inhibition on FL incidence and TME composition. We treated 40 immunized EZH2/BCL2 mice biweekly with anti-BAFF or IgG control beginning at 6 months. Mice also received 3 weeks of tazemetostat (taz), an EZH2 inhibitor approved in FL, or vehicle (veh) before sacrifice at 7 months (recapitulating early FL) and 11 months (late FL) (n=20 per timepoint). We analyzed splenic tissues by histology, flow cytometry, and immunofluorescence (IF) imaging. Combined anti-BAFF + taz, and to a lesser extend anti-BAFF, delayed the onset and progression of FL. Anti-BAFF increased the recruitment of CD4+ and CD8+ T cells into follicular areas in both early (p<0.001) and late (p<0.05) timepoints. This was enhanced by taz at the late timepoint (1.5-fold, p<0.05). IF showed that BAFF blockade decreased FDC contacts with FL B cells (1.9-fold) and T cells (2.6-fold) at the early timepoint. In contrast, at the late timepoint, anti-BAFF increased FDC contacts with FL B cells (1.7-fold) but not T cells. Similarly, anti-BAFF decreased CXCL13+ FDCs at the early timepoint (1.7-fold) but increased CXCL13+ FDCs at the late timepoint (0.6-fold). These findings suggest that BAFF inhibition increases T cell involvement in FL and decreases FL incidence, though these effects are later reversed, potentially through compensatory resistance mechanisms or neutralizing antibodies against anti-BAFF. Notably, the presence of CXCL13+ FDCs was linked to inferior PFS in our cohort of FL patients profiled by IMC (p<0.001) and CXCL13 transcripts were progressively increased in our EZH2/BCL2 mice analyzed at various timepoints as compared to WT. CXCL13 expression may highlight active FDCs, which decrease at the early timepoint with BAFF inhibition and later recur as FL progresses. Overall, we identify FDCs as a therapeutic target in FL and highlight the additive effects of EZH2 inhibition. We further establish a critical treatment window early in FL at which point BAFF and EZH2 inhibition increase T cell involvement within the TME and prevent FL formation. These findings reveal a promising strategy for treating FL early in its disease course and potentially for enhancing T cell-based immunotherapies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.241
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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