Large B-cell lymphoma imprints a dysfunctional immune phenotype that persists years after treatment

Abstract

Immunotherapy has become standard of care in the treatment of diffuse large B-cell lymphoma (DLBCL). Changes in immunophenotypes observed at first diagnosis predict therapy outcome but little is known about the resolution of these alterations in remission. Comprehensive characterization of immune changes from fresh, peripheral whole blood revealed a functionally relevant increase of myeloid-derived suppressor cells, reduced naïve T cells, and an increase of activated and terminally differentiated T cells before treatment, which aggravated after therapy. Suggesting causal relation, injection of lymphoma in mice induced similar changes in the murine T cells. Distinct immune imprints were found in those who have survived breast cancer and acute myeloid leukemia. Identified alterations persisted beyond 5 years of ongoing complete remission and correlated with increased proinflammatory markers such as interleukin-6, β2-microglobulin, or soluble CD14 in DLBCL. The chronic inflammation was associated with functionally blunted T-cell immunity against severe acute respiratory syndrome coronavirus 2-specific peptides, and reduced responses correlated with reduced naïve T cells. Persisting inflammation was confirmed by deep sequencing and by cytokine profiles, together pointing toward a compensatory activation of innate immunity. The persisting, lymphoma-induced immune alterations in remission may explain long-term complications, have implications for vaccine strategies, and are likely relevant for immunotherapies.

Graphical abstract

Figure 1.

Elevated HLA-DR^low CD14⁺ myeloid cells persist in patients with DLBCL after achieving CR and show characteristic features of MDSCs. (A) CD14⁺/HLA-DR^low monocytes were measured by flow cytometry from fresh peripheral whole blood from HCs, patients with DLBCL in CR, when ND, or when R/R. Symbols indicate individual patients, median is indicated. P values determined by the ordinary 1-way analysis of variance (ANOVA) including 2-group comparison using the Šidák multiple comparison when indicated. (B) Time point of individual CD14⁺/HLA-DR^low monocytes shown in panel A. In addition, 27 patients were measured longitudinally and normalized to the first measurement. The red lines indicate linear regression over time including 95% confidence interval (CI) and slope. (C) Rate of CD14⁺/HLA-DR^low cells at CR in subgroups of cell of origin (COO), R-IPI, Ann Arbor stage, age, sex, or tumor bulk, significance determined by the unpaired t test. (D) Intracellular phosphrylated signal transducer and activator of transcription 3 (pSTAT3) by flow cytometry in CD14⁺/HLA-DR^low monocytes compared with HCs, P value determined by ANOVA using the Šidák multiple comparison. (E) Intracellular staining of indoleamine 2,3-dioxygenase 1 (IDO1), arginase-1 (Arg1), and cyclooxygenase 2 (COX2) in CD14⁺/HLA-DR^low and respective DR^high cells of patients with CR, P value determined by the paired t test. (F) Proliferation of activated T cells alone or in coculture with indicated CD14⁺ cell population from n = 15 patients in CR with indicated ratios of myeloid cells to T cells; P values determined by the ordinary 1-way ANOVA. For all panels, ∗P < .05; ∗∗P < .01; ∗∗∗P < .001; ∗∗∗∗P < .0001. GCB, germinal center B cell; HLA-DR, human leukocyte antigen type DR; MFI, mean fluorescence intensity; ns, not significant.

Figure 2.

Altered T-cell phenotype correlates with impaired adaptive vaccine response in patients in CR after DLBCL. (A-B) Analysis of total counts and fractions of indicated T-cell subpopulation measured by flow cytometry in HCs and patients with DLBCL in CR, when ND, or when R/R. Each symbol represents an individual patient, P values determined by ordinary 1-way ANOVA including 2-group comparison using Šidák multiple comparison when indicated. (C) Time point of individual CD4⁺ T-cell or of T_n cell measurement from panels A and B, respectively. The red lines indicate linear regression over time including 95% CI and slope. (D) CD4⁺ T cells or T_n cells of 27 patients were measured longitudinally and normalized to the first measurement. The red lines indicate linear regression over time including 95% CI and slope. (E) Rate of peripheral CD4⁺ T_n cell counts in regard to cell of origin (COO), revised international prognostic index (R-IPI), Ann Arbor stage, age, sex, or tumor bulk. Each symbol represents a single patient, P values determined by unpaired t tests. (F) Flow cytometry–based measurements of activated HLA-DR⁺/CD4⁺ or CD69⁺/CD4⁺ T cells. Each symbol represents individual patients, 2 group comparison by ordinary 1-way ANOVA using the Šidák multiple comparison. (G) After antigen-specific stimulation (SARS-CoV-2 peptides) of T cells from HCs or patients in CR, interferon-γ (IFN-γ) in the supernatant and intracellular IFN-γ in CD8⁺ T cells were compared. Significance was determined by unpaired t tests. (H) Correlogram of the ratio of cell subsets frequencies and anti-spike SARS-CoV-2 T-cell responses across vaccinated HCs and patients in CR. Colored circles represent correlations with P ≤ .05 as determined by the Spearman analysis. Blue and red circles indicate positive and negative correlations, respectively. Color intensity and the size of the circle are proportional to the correlation coefficients. (I) A PCA was performed among patients with DLBCL in CR combining all phenotypic myeloid and T-cell parameters from flow cytometry with HCs and patients with R/R disease mapped using a fixed parameter distribution. Although patients in CR show a diffuse pattern, indicating no clear separation among those patients, the respective HC and R/R clusters separate within the map. Large symbols indicate the centroids of the corresponding groups. For all panels, ∗P < .05; ∗∗P < .01; ∗∗∗P < .001; ∗∗∗∗P < .0001. Dim, dimension; GCB, germinal center B cell; MFI, mean fluorescence intensity; ns, not significant.

Figure 3.

Molecular analyses confirm similar inflammation in CR and AD compared with HCs. (A) CD14⁺ HLA-DR^low monocytes and activated (HLA-DR⁺) T cells were sorted from fresh peripheral blood PBMCs for bulk RNA sequencing. (B) The transcription profile of activated (HLA-DR⁺) T cells of CR DLBCL was compared with those from patients with AD and HCs in an unsupervised clustering. (C) Pathway analysis of the significantly differentially expressed genes of activated (HLA-DR⁺) T cells highlights signature 1 with reduction of mitochondrial respiration and electron transport in AD and CR compared with HCs. Changes of gene expression levels were determined by Z values. (D) Transcription profiles of CD14⁺/HLA-DR^low monocytes from HCs and patients in CR or with AD were unsupervised clustered. (E) CR samples from panel D were manually annotated to either HC-like CR or AD-like CR and unsupervised clustering repeated with the 4 distinct subgroups. (F) Exemplary signature of the 4-group analysis with upregulation of the IFN-α/β signature. Changes of gene expression levels were determined by Z values. (G) Visualizing of the patients HC- and AD-like profiles in the previously shown immunophenotypic pattern PCA from Figure 2H. (H) Cytokine profile of 92 cytokines Olink analysis from serum of patients in CR was clustered by K-means in 2 subgroups by the Elbow method. HC- (green circle) and AD-like samples (blue circles) from the RNA sequencing are indicated. (I) The differentially expressed cytokines of cluster 1 were subtracted by cluster 2 and plotted against their significance levels given by the logarithm of the adjusted P value, that is, −log₁₀ (adj.p). AD., active disease; Dim., dimension; fig., figure; HLA-DR., human leukocyte antigen type DR; IFNa/b, interferon alpha or beta; IL-6, interleukin-6; TNF, tumor necrosis factor.

Figure 4.

Persisting systemic inflammation in CR is distinct from AD. (A) Serum levels of soluble CD25 (sCD25), CXCL9, and CXCL10 or (B) of proinflammatory IL-6, beta-2-microglobuline (B2M), and soluble CD14 (sCD14) were determined from serum samples of HCs and patients in CR, ND patients or patients with R/R disease by enzyme-linked immunosorbent assay. Each symbol indicates individual patients, P values were determined by ANOVA including 2-group comparison using the Šidák multiple comparison when indicated. (C) Serum IL-6 concentration was correlated with absolute M-MDSCs per μL from the peripheral blood of patients in CR, R² of matching is indicated. (D) Monocytes of HCs were differentiated using GM-CSF with or without IL-6 in vitro, and rate of HLA-DR^low monocytes was determined by flow cytometry. Each symbol represents an individual HC, P values were determined by the matched-pair ordinary ANOVA. (E) Absolute counts of CD4⁺ T_n cells were correlated with serum levels of IL-6. (F) Cytokine profiles of 72 patients with DLBCL in relapse were compared with profiles of 43 patients with DLBCL in remission to assess the different inflammation profile between the 2 groups. Each circle corresponds to an individual patient with R/R disease (blue) or CR (red). (G) Volcano plot showing the fold change and significance level of significantly upregulated or downregulated serum cytokines in R/R compared with CR. For all panels, ∗P < .05; ∗∗P < .01; ∗∗∗P < .001; ∗∗∗∗P < .0001. adj., adjusted; CXCL, C-X-C motif chemokine ligand; FASLG, fas ligand; GM-CSF, granulocyte-macrophage colony-stimulating factor; ns, not significant; OX40, TNF receptor superfamily member 4; Stim., stimulated; Tn, naive T cells; TRAIL, tumor necrosis factor-related apoptosis-inducing ligand.

Figure 5.

Specific immune changes in patients with BC, patients with CLL, AML, and lymphoma-bearing mice. (A) Determination of CD14⁺ HLA-DR^low monocytes by flow cytometry in patients with BC when ND and in CR compared with matched HCs. Each symbol represents an individual patient. Significance determined by the ordinary 1-way ANOVA using the Šidák multiple comparison. (B) Staining for intracellular enzymes that correlate with inhibitory function IDO1, Arg1, and COX2 in CD14⁺/HLA-DR^low compared with respective in-patient control of DR^high myeloid cells of patients in CR. Each symbol represents an individual patient, significance determined by the paired t tests. (C) The count of CD14⁺/HLA-DR^high is blotted against the time point of the individual blood draw. Each symbol indicates a single patient. Red line indicates linear regression. (D) Relative and absolute CD4⁺ T-cell activation (HLA-DR) and exhaustion (PD1) in survivors of BC was measured by flow cytometry compared with HCs. Each symbol represents an individual patient, P values were determined by ordinary 1-way ANOVA using the Šidák multiple comparison. (E) The rate of activated (HLA-DR) CD4⁺ T-cells was blotted against the time point of the individual blood draw. Each symbol indicates a single patient. Red line indicates linear regression. (F) Indicated T-cell subsets were measured by flow cytometry from untreated CLL in watch-and-wait. Each symbol represents an individual patient. Two-group comparison was done using the ordinary 1-way ANOVA using the Šidák multiple comparison. (G) Indicated T-cell subset changes of respective disease entities including AML were normalized to the mean of their own HC group as 1 and allow for data comparison between the groups as indicated using the ANOVA group comparisons. Gray boxes indicate disease-specific significant alterations. (H) Scheme of the BL6 systemic BCL mouse model. (I) Indicated organs were analyzed for alterations in the indicated T-cell populations including respective markers after tumor injection compared with tumor-free mice by flow cytometry. Each symbol indicates values from an individual mouse, P values were determined by unpaired t tests. For all panels, ∗P < .05; ∗∗P < .01; ∗∗∗P < .001; ∗∗∗∗P < .0001. Arg1, arginase-1; BL6, black 6; COX2, cyclooxygenase 2; IDO-1, indoleamine 2,3-dioxygenase 1; mCD4, murine CD4; ns, not significant; PD1, programmed cell death protein 1; periph., peripheral; Tn, naive T cells; w&w, watch-and-wait.