Reversal of in situ T-cell exhaustion during effective human antileukemia responses to donor lymphocyte infusion

Abstract

Increasing evidence across malignancies suggests that infiltrating T cells at the site of disease are crucial to tumor control. We hypothesized that marrow-infiltrating immune populations play a critical role in response to donor lymphocyte infusion (DLI), an established and potentially curative immune therapy whose precise mechanism remains unknown. We therefore analyzed marrow-infiltrating immune populations in 29 patients (22 responders, 7 nonresponders) with relapsed chronic myelogenous leukemia who received CD4(+) DLI in the pre-tyrosine kinase inhibitor era. Immunohistochemical analysis of pretreatment marrow revealed that the presence of >4% marrow-infiltrating CD8(+) (but not CD4(+)) T cells predicted DLI response, even in the setting of high leukemia burden. Furthermore, mRNA expression profiling of marrow-infiltrating T cells of a subset of responders compared with nonresponders revealed enrichment of T-cell exhaustion-specific genes in pretreatment T cells of DLI responders and significant downregulation of gene components in the same pathway in responders in conjunction with clinical response. Our data demonstrate that response to DLI is associated with quantity of preexisting marrow CD8(+) T cells and local reversal of T-cell exhaustion. Our studies implicate T-cell exhaustion as a therapeutic target of DLI and support the potential use of novel anti-PD1/PDL1 agents in lieu of DLI.

Figure 1

Preexisting leukemic burden in the bone marrow inversely correlates with clinical response to DLI. (A) Disease burden in patients with relapsed CML before and at serial time points after DLI therapy demonstrated by both percent of bone marrow cells expressing the Philadelphia chromosome detected by FISH as well as (B) percent marrow cellularity. P < .01 for (A) and (B), Responders (circles) vs Nonresponders (triangles) using the exact Wilcoxon rank-sum test.

Figure 2

Characterization of immune cell subsets in marrow over time after DLI. (A) IHC staining analysis of marrow immune populations from responders and nonresponders before and 3 to 6 and 9 to 12 months after DLI. For each immune cell subset, significant differences between 0 and 3 to 6- or 9 to 12-month time points are noted. (B) Representative IHC of marrow samples from one responder and one nonresponder demonstrates robust marrow infiltration by CD3⁺ T cells in the responder before and subsequent increase after DLI. Images were captured with an Olympus QColor 5 camera on an Olympus BX41 microscope with a x40/0.75 objective using Adobe Photoshop Software (vCS5). (C) Pairwise comparison of individual patients’ marrow before and after DLI therapy revealed significant upregulation of marrow CD8⁺ T cells in the responder cohort after treatment. *P < .05 using the Wilcoxon signed-rank test.

Figure 3

CD8⁺ T-cell infiltrates are significantly increased in pretreatment marrow in responders. Quantification of immune cell subsets (CD3⁺, CD8⁺, CD4⁺, CD20⁺, CD138⁺) performed on marrow from responders and nonresponders before DLI therapy. Whiskers in box plots indicate maximum and minimum values. The line indicates median value; P values refer to responders (R) vs nonresponders (NR) comparison using the exact Wilcoxon rank-sum test.

Figure 4

Preexisting infiltrating CD8⁺ T cells and normal marrow cellularity are sensitive predictors of clinical response to DLI therapy. (A) Correlation of marrow cellularity and CD8⁺ T-cell infiltrates for all patients before DLI. (B) ROC analysis for stratifying clinical response (responders and nonresponders) by either preexisting marrow cellularity ≤70% or CD8⁺ T-cell infiltrate ≥4%. (C) Combining criteria results in 100% sensitivity and specificity.

Figure 5

Expression profiling reveals T-cell exhaustion as a strongly associated signature of response to DLI therapy. Differential gene expression from CD3⁺ T cells isolated from the marrow of DLI responders (R) and nonresponders (NR) before DLI therapy (A) or in response to treatment (B). The annotation of genes within key biological processes is indicated. The asterisks refer to genes selected for qPCR validation (see C-D). (C-D) qPCR validation of changes in microarray gene expression in selected genes (C) differentially expressed between R and NR before therapy and (D) differentially affected by DLI over time in R compared with NR. Data are represented as mean ±SEM, with each sample performed in triplicate. (E-F) GSEAs from the pretreatment and response to treatment comparisons. The bar graphs show P value of enrichment (signed according to enrichment score) for distinct T-cell exhaustion gene sets in R vs NR before (E) or after (F) DLI therapy. Detailed descriptions of gene sets are provided in supplemental Table 4. The shaded region indicates P > .05.

Figure 6

The proposed role of T-cell exhaustion in predicting clinical response to DLI. Our data support the idea that (A) response to DLI is associated with a preexisting reservoir of antitumor CD8⁺ T cells residing at the tumor site, to which CD4⁺ DLI provides immunologic help, not only to expand this reservoir but also to reverse T-cell exhaustion. The presence of T-cell exhaustion may signal that this reservoir exists. In contrast, in the absence of such a reservoir (B), a lack of DLI response is associated with both insufficient quantities of infiltrating T cells and the absence of phenotypic evidence of past T-cell activation.