Blood Res.  2022 Jun;57(2):117-128. 10.5045/br.2022.2021145.

Diffuse large B-cell lymphoma (DLBCL) is infiltrated with activated CD8⁺ T-cells despite immune checkpoint signaling

• Greenbaum AM
• Fromm JR
• Gopal AK
• Houghton AM

• KMID: 2530875
• DOI: http://doi.org/10.5045/br.2022.2021145

Abstract

Background
B-cell non-Hodgkin lymphomas (NHL) are hematologic malignancies that arise in the lymph node. Despite this, the malignant cells are not cleared by the immune cells present. The failure of anti-tumor immunity may be due to immune checkpoints such as the PD-1/PDL-1 axis, which can cause T-cell exhaustion. Unfortunately, unlike Hodgkin lymphoma, checkpoint blockade in NHL has shown limited efficacy.
Methods
We performed an extensive functional analysis of malignant and non-malignant lymph nodes using high dimensional flow cytometry. We compared follicular lymphoma (FL), diffuse large B-cell lymphoma (DLBCL), and lymph nodes harboring reactive hyperplasia (RH).
Results
We identified an expansion of CD8⁺PD1⁺ T-cells in the lymphomas relative to RH. Moreover, we demonstrate that these cells represent a mixture of activated and exhausted T-cells in FL. In contrast, these cells are nearly universally activated and functional in DLBCL. This is despite expression of counter-regulatory molecules such as PD-1, TIM-3, and CTLA-4, and the presence of regulatory T-cells.
Conclusion
These data may explain the failure of single-agent immune checkpoint inhibitors in the treatment of DLBCL. Accordingly, functional differences of CD8⁺ T-cells between FL and DLBCL may inform future therapeutic targeting strategies.

Keyword

Lymphoma; Immune microenvironment; Immune checkpoint inhibition

Figure

• 

  Fig. 1 Dimensional reduction of T-cells using UMAP algorithm. (A) U-MAP plot of T-cells generated from combined data from RH, FL, and DLBCL. Each color represents an identified population using the PhenoGraph algorithm. (B) Overlay of reactive hyperplasia (red) on to U-MAP plot. Numbers represent populations not present RH. (C–G) Heat maps showing expression of CD45RA, FoxP3, CXCR5, PD-1, and TIM-3. Histologies were FL (N=7), DLBCL (N=6), and RH (N=2). DLBCL subtypes included 4 GCB type, 1 ABC type, and one unknown.

• 

  Fig. 2 Populations enriched in each histology. (A) Tfh, (B) Treg, (C) NK cells, (D) CD4+ PD-1-, (E) CD4+ PD-1int, (F) CD4+ PD-1int TIM-3+, (G) CD8+ PD-1-, (H) CD8+ PD-1+, (I) CD8+ PD-1+ TIM-3+. Graphs represent a separate cohort of patients from Fig. 1 except panels F and I. Histologies for new cohort were RH (N=4), FL (N=16), DLBCL (N=20). P-values as indicated.

• 

  Fig. 3 Functional characterization of CD8+ cells. The percentage of (A) naïve/central memory (CM)/ effector memory (EM) T-cells by each histology and (B) by ex-pression of PD-1 and TIM-3 ex-pression. (C) Percent of total CD8+ T-cells that produce IFNγ . (D) IFNγ production by histology and memory subset. (E, F) Linear regression of CD8+ cells producing IFNγ and IL-2 versus the percentage of cells expressing PD-1. (G) IFNγ and (H) IL-2 production by CD8+ T-cells by expression of PD-1, TIM-3, and CTLA-4. Histologies were RH (N=2), FL (N=5), DLBCL (N=6). P-values as indicated.

• 

  Fig. 4 Cytotoxicity, cell cycling, and apoptosis in DLBCL. (A) The percentage of CD8+ T-cells lacking both granzyme B and perforin by PD-1 and TIM-3 expression (N=4). (B) The percentage of CD8+ T-cells that degranulate in response to PMA/ionomycin by PD-1, TIM-3, and CTLA-4 expression (N=4). (C) The percentage of CD8+ T-cells that are actively cycling by PD-1 and TIM-3 expression (N=4). (D) Percentage of CD8+ T-cells that are undergoing apoptosis by PD-1 and TIM-3 expression. Early apoptosis is defined as cleaved PARP+ viability dye-, and late apoptosis as cleaved PARP+ viability dye+ (N=4). P-values as indicated.

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