ArticleFrontiers in immunology2026
Tumoral immune microenvironment profiling in B-cell non-Hodgkin lymphoma stratifies patients in different prognostic groups.
Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.