Background: Follicular lymphoma (FL), the most common indolent non-Hodgkin’s Lymphoma, is a heterogeneous disease and a paradigm of the contribution of immune tumor microenvironment to disease onset, progression, and therapy resistance. Patient-derived models are scarce and fail to reproduce immune phenotypes and therapeutic responses. Methods: To capture disease heterogeneity and microenvironment cues, we developed a patient-derived lymphoma spheroid (FL-PDLS) model culturing FL cells from lymph nodes (LN) with an optimized cytokine cocktail that mimics LN stimuli and maintains tumor cell viability. Results: FL-PDLS, mainly composed of tumor B cells (60% on average) and autologous T cells (13% CD4 and 3% CD8 on average, respectively), rapidly organizes into patient-specific three-dimensional (3D) structures of three different morphotypes according to 3D imaging analysis. RNAseq analysis indicates that FL-PDLS reproduces FL hallmarks with the overexpression of cell cycle, BCR, or mTOR signaling related gene sets. FL-PDLS also recapitulates the exhausted immune phenotype typical of FL-LN, including expression of BTLA, TIGIT, PD-1, TIM-3, CD39 and CD73 on CD3⁺ T cells. These features render FL-PDLS an amenable system for immunotherapy testing. With this aim, we demonstrate that the combination of obinutuzumab (anti-CD20) and nivolumab (anti-PD1) reduces tumor load in a significant proportion of FL-PDLS. Interestingly, B cell depletion inversely correlates with the percentage of CD8⁺ cells positive for PD-1 and TIM-3. Conclusions: In summary, FL-PDLS is a robust patient-derived 3D system that can be used as a tool to mimic FL pathology and to test novel immunotherapeutic approaches in a context of personalized medicine.

Follicular lymphoma (FL) is an indolent B cell lymphoproliferative disorder of transformed follicular center B cells, which accounts for 20–30 percent of all non-Hodgkin lymphoma (NHL) cases. Great advances have been made to identify the most relevant targets for precision therapy. However, no relevant models for in vitro studies have been developed or characterized in depth. To this purpose, we generated a 3D cell model from t(14;18)-positive B-NHL cell lines cultured in ultra-low attachment 96-well plates. Morphological features and cell growth behavior were evaluated by classical microscopy (2D imaging) and response to treatment with different drugs was evaluated by a high-content analysis system to determine the robustness of the model. We show that the ultra-low attachment (ULA) method allows the development of regular, spherical and viable ULA-multicellular aggregates of lymphoma cells (MALC). However, discrepancies in the results obtained after 2D imaging analyses on drug-treated ULA-MALC prompted us to develop 3D imaging and specific analyses. We show by using light sheet microscopy and specifically developed 3D imaging algorithms that 3D imaging and dedicated analyses are necessary to characterize morphological properties of 3D models and drug effects. This study proposes a new method, but also imaging tools and informatic solutions, developed for FL necessary for future preclinical studies.

Bispecific antibodies (bsAbs) such as glofitamab represent a promising therapeutic approach for relapsed/refractory B-cell non-Hodgkin lymphoma (R/R B-NHL), but resistance mechanisms remain poorly understood. This study aimed to identify predictive markers of bsAb resistance based on the response of 3-dimensional patient-derived lymphoma spheroids (PDLS) established from 39 R/R B-NHL samples. PDLS were treated with glofitamab for 3 days, and B-cell depletion was quantified to assess the ex vivo treatment response. Comprehensive immune profiling was performed on patient samples using multiparametric flow cytometry, single-cell RNA sequencing, codetection by indexing spatial proteomics, and functional assays. High responders to glofitamab possessed CD8+ T cells with consistently higher cytotoxic and activation signatures across effector differentiation states, whereas low responders showed enrichment of exhausted CD8+ T cells with enhanced expression of exhaustion markers (T-cell immunoglobulin and ITIM domain [TIGIT], LAG3, and PD1). Furthermore, low responders exhibited elevated functional CD4+ T follicular helper (Tfh) cells in close proximity to malignant B cells, thus promoting their survival through interleukin-21 and C-X-C motif chemokine ligand 13 signaling pathways. Analysis of pretreatment RNA-sequencing data from 48 patients with R/R B-NHL confirmed that high Tfh cell abundance is associated with poor glofitamab response. In PDLS, anti-TIGIT cotreatment enhanced glofitamab efficacy in low responders, and Tfh cell depletion experiments confirmed that reducing Tfh cell activity increased B-cell depletion. Together, these findings identify CD8+ T-cell exhaustion and functionally activated Tfh cells as key factors associated with glofitamab resistance in R/R B-NHL. This work supports their potential use as predictive biomarkers for selecting patients with higher probability of response and provides a foundation for future combination therapeutic strategies.

Characterization of the molecular mechanisms involved in tumor cell clustering could open the way to new therapeutic strategies. Towards this aim, we used an in vitro quantitative procedure to monitor the anchorage-independent cell aggregation kinetics in a panel of 25 cancer cell lines. The analysis of the relationship between selected aggregation dynamic parameters and the gene expression data for these cell lines from the CCLE database allowed identifying genes with expression significantly associated with aggregation parameter variations. Comparison of these transcripts with the perturbagen signatures from the Connectivity Map resource highlighted that they were strongly correlated with the transcriptional signature of most histone deacetylase (HDAC) inhibitors. Experimental evaluation of two HDAC inhibitors (SAHA and ISOX) showed that they inhibited the initial step of in vitro tumor cell aggregation. This validates our findings and reinforces the potential interest of HDCA inhibitors to prevent metastasis spreading.