Page 25 - Haematologica Vol. 110 - January 2025

EDITORIAL
A. Dogan and M. Roshal
Stephan and colleagues approach this question by har- nessing the power of spectral flow cytometry (FC) to per- form an extensive analysis of the immune background in TCL. The approach allows for a detailed analysis of T-cell phenotypes with a relatively limited analysis of additional subsets including B cells, macrophages, and dendritic cells. The data illustrate the ability of spectral FC to quickly and relatively inexpensively facilitate the analysis of hundreds of thousands of cells per case. As the study requires viable tumor cell suspensions, the number of cases that could be studied was quite limited but the study was nevertheless informative. One of the most striking findings is the signif- icant difference in the TCL microenvironment compared to normal lymphoid tissue. This is primarily driven by remark- able heterogeneity in the so-called CD4+ ‘conventional’ T cells (Tconv). The authors attempted to explicitly clarify whether the signal was derived from neoplastic or benign T cells using both automated and manual gating approaches. Unfortunately, they were not fully successful. The antibody panels were primarily designed to assess physiological T-cell subsets but not necessarily to define the neoplas- tic T cells. This ambiguity of the signal derivation remains the main limitation of the study. More precise information can be obtained for T-cell subsets such as T-regulato- ry cells (Tregs) and CD8+ T-cell subsets as these can be readily distinguished from neoplastic T cells. As seen in most other lymphoid neoplasms, the study reports that in TCL there is a marked increase in Tregs and an exhausted phenotype in CD8+ cytotoxic T cells raising the possibility
References
1. Stephan P, Perrot J, Voisin A, et al. Deep phenotyping of nodal T-cell lymphomas reveals immune alterations and therapeutic targets. Haematologica. 2025;110(1):129-141.
2. Ansell SM, Lesokhin AM, Borrello I, et al. PD-1 blockade with nivolumab in relapsed or refractory Hodgkin’s lymphoma. N Engl J Med. 2015;372(4):311-319.
3. Brudno JN, Kochenderfer JN. Chimeric antigen receptor T-cell therapies for lymphoma. Nat Rev Clin Oncol. 2018;15(1):31-46.
4. Falchi L, Vardhana SA, Salles GA. Bispecific antibodies for the treatment of B-cell lymphoma: promises, unknowns, and opportunities. Blood. 2023;141(5):467-480.
5. Patel SS, Weirather JL, Lipschitz M, et al. The microenvironmental niche in classic Hodgkin lymphoma is enriched for CTLA-4-positive T cells that are PD-1-negative. Blood. 2019;134(23):2059-2069.
6. Pourmaleki M, Jones CJ, Mellinghoff SD, et al. Multiplexed spatial profiling of Hodgkin Reed-Sternberg cell neighborhoods in classic Hodgkin lymphoma. Clin Cancer Res. 2024;30(17):3881-3893.
7. Han G, Deng Q, Marques-Piubelli ML, et al. Follicular lymphoma microenvironment characteristics associated with tumor cell mutations and MHC Class II expression. Blood Cancer Discov.
of novel therapeutic approaches. In addition, the analysis identifies heterogeneity of CD39 expression, an important immune checkpoint in cancer biology. The authors also explore the potential value of high CD39 expression as an adverse prognostic factor in a separate cohort of angio- immunoblastic TCL.
The study by Stephan et al. demonstrates the feasibility of deep and relatively inexpensive phenotypic analysis of the immune microenvironment in TCL at the single-cell level, while also highlighting the numerous challenges in this field. To address these challenges and develop effective immuno-oncology therapies for TCL, a major shift in ap- proach is required. This shift should include the acquisition of well-annotated, viable biospecimens and the implemen- tation of analytical methods that can be scaled up within the context of clinical trials. These methods must enable not only the unequivocal identification of neoplastic and benign T cells, but also the characterization of other immune components, such as B cells, macrophages, and dendritic cells, as well as the elucidation of the spatial relationships between different components of the immune system.
Disclosures
AD reports research support from Roche and AstraZeneca unrelated to the submitted work. MR has no conflicts of interest to disclose.
Contributions
AD and MR both developed and wrote the manuscript.
2022;3(5):428-443.
8. Cerchietti L. Genetic mechanisms underlying tumor
microenvironment composition and function in diffuse large
B-cell lymphoma. Blood. 2024;143(12):1101-1111.
9. Ham JS, Park HY, Ryu KJ, Ko YH, Kim WS, Kim SJ. Elevated
serum interleukin-10 level and M2 macrophage infiltration are associated with poor survival in angioimmunoblastic T-cell lymphoma. Oncotarget. 2017;8(44):76231-76240.
10. Sugio T, Miyawaki K, Kato K, et al. Microenvironmental immune cell signatures dictate clinical outcomes for PTCL-NOS. Blood Adv. 2018;2(17):2242-2252.
11. Zhu Q, Deng X, Yao W, et al. Novel tumour-infiltrating lymphocyte-related risk stratification based by flow cytometry for patients with de novo angioimmunoblastic T cell lymphoma. Ann Hematol. 2021;100(3):715-723.
12. Pritchett JC, Yang ZZ, Kim HJ, et al. High-dimensional and single-cell transcriptome analysis of the tumor microenvironment in angioimmunoblastic T cell lymphoma (AITL). Leukemia. 2022;36(1):165-176.
13. Suma S, Suehara Y, Fujisawa M, et al. Tumor heterogeneity and immune-evasive T follicular cell lymphoma phenotypes at single-cell resolution. Leukemia. 2024;38(2):340-350.
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