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Updated: Aug 8, 2026

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Tumoral immune microenvironment profiling in B-cell non-Hodgkin lymphoma stratifies patients in different prognostic
Daniel Medina-Gil1,2, Víctor Navarro3, Juan C Nieto1,2
1Experimental Hematology, Vall d'Hebron Institute of Oncology (VHIO), Instituto de Investigación Sanitaria Hospital Universitari Vall d'Hebron (IIS IR-HUVH), Barcelona, Spain.
Background:
Non-Hodgkin lymphomas (NHL) represent a heterogeneous group of B-cell-derived malignancies. Previous studies showed that tumor immune microenvironment (TIM) components are associated with tumor development and progression. Furthermore, recent transcriptomic analyses revealed that TIM status can stratify patients into distinct prognostic groups; however, these insights are not clinically exploited.
Methods:
We characterized the TIM of 64 NHL biopsies and 16 reactive lymphoid tissues (rLT) controls using multi-parameter flow cytometry, including major subpopulations, T-cell subsets and immune checkpoint expression on healthy/malignant B and T cells. Individuals were stratified by TIM profiles, and prognostic values were evaluated. The mutational landscape was also assessed by targeted DNA sequencing.
Results:
Flow cytometry analysis revealed HLA-I downregulation in a patient subset and increased expression of inhibitory ligands, particularly in diffuse large B-cell lymphoma (DLBCL). T cells showed a shift toward effector profiles and higher exhaustion marker expression compared with rLT. TIM composition did not differ substantially between patients with specific mutations. TIM-based clustering identified three distinct groups primarily defined by T-cell exhaustion. We assessed the prognostic impact of TIM classification in follicular lymphoma (FL), the most prevalent diagnosis in our cohort. FL patients in cluster C1, characterized by higher frequencies of CD4+ and naïve T cells, showed longer time to treatment, overall survival and progression-free survival outcomes compared with FL cases from cluster C2.
Conclusions:
The classification of TIM profiles by flow cytometry in NHL patients predicts the outcome of FL patients, highlighting its value for risk stratification and identifying potential immunotherapeutic targets in NHL.
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