Immune Crosstalk Profiling of Non-Hodgkin Lymphoma (NHL) Tumor Immune Microenvironment Identifies Two Clusters Based on T Cell Exhaustion, Correlating with Different Clinical Outcomes
Authors: Medina Daniel , Palomo Laura , Navarro Víctor , García Cristina , Nieto Juan Camilo , Carabia Júlia , Pagès Geli Carlota , Acha Pamela , Pujadas Gemma , Palacio Carlos , Gallur Laura , Castellvi Josep , Abrisqueta Pau , Bosch Francesc , Crespo Marta 
Published: December 2024

Introduction: Tumor cells use different mechanisms to evade immune surveillance, leading to the remodeling of the tumor immune microenvironment (TIM). TIM is considered to play an important role in the pathogenesis and response to treatment in non-Hodgkin lymphoma (NHL). Herein, we hypothesized that different NHL subtypes share common TIM patterns that can predict patient outcomes. Therefore, our objective was to characterize the crosstalk between cancer cells and T cells across different NHL subtypes and its clinical relevance.
Methods: Biopsies from 64 NHL patients and 16 reactive/non-malignant lymphoid tissues (rLT) were analyzed by flow cytometry. Immune profiling included major lymphocyte subpopulations, as well as the expression of inhibitory (PD-L1, CD112, CD155) and co-stimulatory ligands (CD58, 4-1BBL, ICOSL, OX40L) and HLA-I in B cells, the expression of inhibitory (PD-1, TIGIT, TIM3, LAG3, CD244, CD160) and co-stimulatory receptors (4-1BB, ICOS, OX40) on T cells, T cell differentiation status, Tregs and T-helper cells. Overall survival (OS) and progression-free survival (PFS) was available for 59 out of 64 patients.
Results: The characterized tumors included follicular lymphoma (FL) (n=35), diffuse large B cell lymphoma (DLBCL) (n=14), marginal zone lymphoma (MZL) (n=7), mantle cell lymphoma (MCL) (n=4), Burkitt's lymphoma (BL) (n=3) and high-grade B cell lymphoma (HGBCL) (n=1). The immune profiling showed a higher percentage of CD58+ and HLA-I negative NHL cells compared to healthy B cells in rLT. Moreover, we observed a significantly higher number of patients with NHL cells expressing PD-L1, CD112 and ICOSL compared to rLT. These results confirmed the loss of surface HLA-I and the expression of PD-1 and TIGIT ligands as common immune evasion mechanisms in NHL. CD4+ T cells were reduced in NHL compared to rLT, while CD8+ T cell levels were not distinct. Both CD4+ and CD8+ T cells exhibited depletion of the naïve pool and elevated expression of PD-1, TIGIT, LAG3 and TIM3. The percentage of CD4+ and CD8+ T cells co-expressing PD-1 and TIGIT was also significantly higher in NHL. An increased expression of the co-stimulatory receptor 4-1BB was observed in CD4+ and CD8+ T cells from NHL tumors. Additionally, Treg frequency was higher in NHL while there were no significant differences in T-helper subpopulations. Overall, our data showed a skewing of T cells towards an effector profile with increased expression of exhaustion markers in NHL.
Unsupervised clustering of the samples using the k-means method based on the 54 parameters assessed by immunophenotyping identified 3 different clusters: ‘reactive’ (n=28; 13 rLT, 8 FL, 2 DLBCL, 2 MZL, 2 MCL and 1 BL), ‘indolent’ (n=41; 25 FL, 5 MZL, 5 DLBCL, 3 rLT, 2 MCL, 1 BL) and ‘aggressive’ (n=11; 7 DLBCL, 2 FL, 1 HGBCL, 1 BL). The reactive cluster was distinguished from the indolent and aggressive clusters by lower PD-1 and TIGIT expression, as well as a higher percentage of naïve T cells, CD4+ TCM and total CD4+. The aggressive cluster was differentiated from the indolent cluster by higher expression of inhibitory ligands in malignant cells and elevated TIM3 and LAG3 expression in T cells.
To cluster based only on TIM elements, we repeated the clustering of the whole cohort but excluding B cell markers. Samples from the reactive cluster were still grouped together, whereas the indolent/aggressive clusters were united into a single one we named as effector/exhausted (E/E). Patients clustered into the reactive group had longer median PFS compared to those in the E/E (79 months vs. 42 months, HR=0.35; p=0.03). Considering only FL cases, the FL cases clustering as reactive also had longer median PFS compared to FL cases clustering as E/E (79 months vs 45 months, HR=0.24; p=0.05). These findings emphasize the clinical relevance of T cell status in the TIM in NHL. In terms of OS, we did not observe significant differences.
Conclusions: Our results confirmed the different crosstalk between B and T cells in NHL marked by the expression of inhibitory ligands in tumor cells, HLA-I downmodulation, lower CD4+ T cell frequency and higher T cell exhaustion. In addition, T cell-based clustering identified two groups of patients with different PFS, showing how a TIM rich in CD4+ T cells and with low T cell exhaustion is related to better prognosis. Overall, our study points out the potential benefits of deeper immunophenotyping of T cells from TIM to predict patient outcomes.