Intra-Tumoral CD8+ T-Cells in Follicular Lymphoma Contain Large Clonal Expansions That Are Amenable to Dual-Checkpoint Blockade

Introduction. Intra-tumoral T-cell infiltration is associated with R-CHOP responsiveness in aggressive B-cell lymphoma (Keane, Lancet Haem 2015). These patients also have a broad (i.e. diverse) intra-tumoral T-cell receptor (TCR) repertoire with a ~20% superior survival compared to those with a narrow (i.e. clonal) repertoire after R-CHOP therapy. Here, the major contributor to the TCR clonal expansion were CD8+ T cells (Keane, CCR 2017). Paradoxically, our recent results in Follicular Lymphoma (FL) (Tobin, JCO in press) found that clonal T-cell expansions were markedly enriched in those patients that experienced progression of disease within 24 months (POD24). Given that FL is a histological subtype associated with a tumor microenvironment distinct from DLBCL including numerous CD4+ T-follicular helper cells (TFH), we now expand upon these findings by comparing TCR repertoires across histological subtypes. We then established whether the TCR repertoire in FL is related to differential TCR clonal expansions between different T-cell subsets and immune checkpoints. Finally, the overlap between tissue and blood TCR repertoires was investigated. Methods. Firstly, unbiased, high-throughput TCRβ sequencing (ImmunoSEQ, Adaptive Biotechnologies) was compared in 164 FFPE tissues (12 healthy nodes, 40 FL, 88 DLBCL, and as a comparator tumor known to be sensitive to checkpoint blockade and to have a high neoantigen burden, 24 melanoma tissues). Next, to determine the contribution of individual T-cell subsets to overall clonality, a further 21 fresh de-aggregated/cryopreserved FL tumor samples were FACS sorted into four T-cell groupings: CD8+ cytotoxic T-lymphocytes (CTLs), CD4+ TFH, CD4+ regulatory T-cells (TREGs) and 'other' (non-TFH/TREG) CD4+ T-cells. Flow cytometry quantified the expression of the checkpoints LAG3, TIM3 and PD1. Then, 5 FL paired tissue/blood samples were tested for shared TCR clones. Results. FL exhibited strikingly reduced TCR repertoire clonality (higher diversity) compared to DLBCL, melanoma and healthy lymph nodes (Fig 1A). Analysis of de-aggregated sorted nodal T-cells revealed a more complex TCR repertoire. The outcome measure was median clonality index (CIx ranging from '0' or minimal, to '1' or maximal clonality). Large T-cell clones in FL (CIx=0.12) predominantly resided within the CTL subset (34% all T-cells). By contrast, there was marked T-cell diversity in TFH (CIx=0.04; 27% all T-cells), TREG (CIx=0.02; 7% all T-cells) and 'other' CD4+ T-cells (CIx=0.02; 32% all T-cells) (Fig 1B). The CTL population had a bimodal expression for PD1 (+51%/-49%), a marker in FL that has been shown to remain functionally active unless co-expressed with LAG3 and/or TIM3 (Yang, Oncotarget 2017). These dual-checkpoint expressing CTLs have reduced capacity to produce cytokines or lytic granules (i.e. they are 'exhausted'). Notably, 54% of the PD1+ CTLs co-expressed either LAG3 or TIM3. Put together, these results are consistent with expanded CTL clones that are frequently functionally exhausted. In contrast, TFH, TREG and 'other' CD4+ T-cells had a low expression of LAG3 and TIM3, although PD1 was frequently found (as expected, particularly in the TFH cells). Finally, in paired tissue/blood samples, there was weak overlap between the circulating and intra-tumoral TCR repertoire in CTLs and TFH T-cells. Conclusion. Although FL has a markedly less clonal TCR repertoire compared to DLBCL, melanoma and even healthy nodes, this result is misleading. Detailed analysis on sorted intra-tumoral T-cell subsets in FL revealed large clonal expansions in CTLs, with approximately half of these classified as functionally exhausted (dual-positive for PD1 and LAG3 and/or TIM3), a state potentially amenable to reversal by dual-checkpoint blockade. The explanation for TCR repertoire diversity lies in CD4+ T-cells (representing approximately two-thirds of T-cells, including the large TFH subset). T-cells in blood did not reflect FL tissue T-cell clones, further highlighting the need for sorted intra-tumoral nodal tissues to accurately assess TCR repertoires in FL. Further characterization of the neo-antigenic targets that CTL clones potentially recognize is required. These results have implications for therapeutic vaccine design and selective recruitment of patients for immune checkpoint blockade. Disclosures Keane: MSD: Consultancy; Gilead: Consultancy; Celgene: Consultancy; Roche: Consultancy, Other: Travel Grant; BMS: Research Funding. Gandhi:Roche: Honoraria, Other: Travel Support; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Honoraria, Research Funding.

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Synergistic Role of Leukemic and Non-Leukemic Immune Repertoires in CD8+ T-Cell Large Granular Lymphocytic Leukemia As Identified By Single-Cell Transcriptomics

Blood ◽

10.1182/blood-2021-146539 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 1318-1318

Author(s):

Dipabarna Bhattacharya ◽

Jani Huuhtanen ◽

Matti Kankainen ◽

Tapio Lönnberg ◽

Cassandra M Kerr ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Board Of Directors ◽

Research Funding ◽

Lymphocytic Leukemia ◽

Leukemic Cells ◽

Healthy Controls ◽

Advisory Committees ◽

Cell Clones ◽

Tcr Repertoire

Abstract Background: T-cell large granular lymphocytic leukemia (T-LGLL), a rare lymphoproliferative disorder of mature T cells, is characterized by the accumulation of activated effector T cells leading to a clonally restricted T-cell receptor (TCR) repertoire. Chronic antigen stimulation together with activating somatic STAT3 mutations have been proposed to lead to clonal expansion of leukemic cells. However, no holistic research has been done to show how leukemic and non-leukemic cells liaise to sustain abnormal immune reactivity in T-LGLL. Methods: We investigated the transcriptome and TCR repertoire in T-LGLL using: 1) single-cell RNA and TCR (scRNA+TCRαβ) sequencing from CD45+ sorted blood cells (T-LGLL n=11, healthy n=6), 2) TCRβ sequencing from blood mononuclear cells (T-LGLL n=48, healthy n=823), 3) bulk RNA sequencing (T-LGLL n=15, healthy n=5), 4) plasma cytokine profiling (T-LGLL n=9, healthy n=9), and 5) flow cytometry validations (T-LGLL n=6, healthy n=6) (Figure) Results: ScRNA+TCRαβ-seq data revealed that in healthy controls, hyperexpanded CD8+ T-cell clones (at least 10 cells with identical TCRs) preferentially had an effector memory phenotype, whereas in T-LGLL, the hyperexpanded clonotypes represented a more cytotoxic (increased expression of GZMB, PRF1, KLRB1) and exhausted (LAG3 and TIGIT) phenotype. Using flow cytometry, we confirmed that upon anti-CD3/CD28/CD49 antibody stimulation, T-LGLL clones (CD8+CD57+) expressed higher levels of cytotoxic proteins (GZMA /GZMB , PRF1) but were deficient in degranulation responses and cytokine secretion as measured by expression of CD107a/b and TNFα/IFNγ, respectively. Focused re-clustering of the extracted T-LGLL clones from the scRNA+TCRαβ-seq data revealed considerable heterogeneity among the T-LGLL clones and partly separated the mutated (mt) STAT3 and wild type (wt) STAT3 clones. STAT3wt clones upregulated T-cell activation and TCR signaling pathways, with a higher cytotoxicity and lower exhaustion score as compared to STAT3mt clones. This was validated with bulk RNA-seq data. To understand the antigen specificities of the T-LGLL clones, we combined previously profiled T-LGLL TCRs with our data to form the largest described dataset of 200 T-LGLL clones from 170 patients. Notably, T-LGLL clones were found to be private to each patient. Furthermore, the analysis by GLIPH2 algorithm grouping TCRs did not reveal detectable structural similarities, suggesting the absence of a unifying antigen in T-LGLL. However, in 67% of T-LGLL patients, the TCRs of leukemic clones shared amino acid level similarities with the rest of the non-leukemic TCR repertoire suggesting that the clonal and non-clonal immune repertoires are connected via common target antigens. To analyze the non-clonal immune repertoire in T-LGLL in detail, we compared our data to other published scRNAseq data from solid tumors (n=4) and hematologic cancers (n=8) and healthy controls (n=6). The analysis revealed that in T-LGLL also the non-leukemic CD8+ and CD4+ T cells were more mature, cytotoxic, and clonally restricted. When compared to healthy controls and other cancer patients, in non-leukemic T-LGLL the most upregulated pathway was IFNγ response. Finally, most of the upregulated cytokines in T-LGLL (e.g., CCL2/3/7, CXCL10/11, IL15RA) were secreted predominantly by monocytes and dendritic cells, which also had upregulated HLA class II expression and enhanced scavenging potential in T-LGLL patients. Ligand-receptor analysis with CellPhoneDB revealed that the number of predicted cell-cell interactions was significantly higher in T-LGLL as compared to reactive T-cell clones in healthy controls. The most co-stimulatory interactions (e.g., CD2-CD58, TNFSF14-TNFRSF14) occurred between the IFNγ secreting T-LGLL clones and the pro-inflammatory cytokine secreting monocytes. Conclusions: Our study shows a synergistic interplay between the leukemic and non-leukemic immune cell repertoires in T-LGLL, where an aberrant antigen-driven immune response including hyperexpanded CD8+ T-LGLL cells, non-leukemic CD8+ cells, CD4+ cells, and monocytes contribute to the persistence of the T-LGLL clones. Our results provide a rationale to prioritize therapies that target the entire immune repertoire and not only the T-LGLL clones in patients with T-LGLL. Figure 1 Figure 1. Disclosures Loughran: Kymera Therapeutics: Membership on an entity's Board of Directors or advisory committees; Bioniz Therapeutics: Membership on an entity's Board of Directors or advisory committees; Keystone Nano: Membership on an entity's Board of Directors or advisory committees; Dren Bio: Membership on an entity's Board of Directors or advisory committees. Maciejewski: Alexion: Consultancy; Novartis: Consultancy; Regeneron: Consultancy; Bristol Myers Squibb/Celgene: Consultancy. Mustjoki: Novartis: Research Funding; BMS: Research Funding; Janpix: Research Funding; Pfizer: Research Funding.

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The NLPHL Tumor Microenvironment Is Markedly Enriched in the Tigit and PD-1 Signalling Axes Compared to Classical Hodgkin Lymphoma

Blood ◽

10.1182/blood-2021-145840 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 3513-3513

Author(s):

Jay Gunawardana ◽

Muhammed B. Sabdia ◽

Karolina Bednarska ◽

Soi C. Law ◽

Sandra Brosda ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Board Of Directors ◽

Immune Checkpoint ◽

Research Funding ◽

Immune Checkpoint Blockade ◽

Checkpoint Blockade ◽

Immune Checkpoints ◽

Advisory Committees ◽

Tcr Repertoire

Abstract Nodular lymphocyte predominant Hodgkin lymphoma (NLPHL) comprises 5% of all Hodgkin lymphomas (HL). Its biology remains poorly characterized. Like classical HL (cHL), it contains minimal malignant cells embedded within a T cell rich intra-tumoral microenvironment (TME). Unlike cHL, it can transform to diffuse large B cell lymphoma (DLBCL). Immune-checkpoint blockade is effective in cHL but has minimal activity in DLBCL. No data is currently available regarding the potential to reactivate host anti-tumoral activity via immune-checkpoint blockade in NLPHL. Diagnostic FFPE samples from 49 NLPHL patients retrospectively collected from 4 Australian centres were interrogated. Inclusion criteria were sample availability and centrally confirmed histological NLPHL. Characteristics were in line with the literature: median age 45 years, range 13-82 years; F:M 1:3.5; stage I/II 55%, III/IV 35% (10% stage unknown) with the majority of cases were of immuno-architectural types A or C. RNA was digitally quantified using the NanoString 770-gene PanCancer Immune panel. Multi-spectral immunofluorescent (mIF) microscopy, plasma soluble PD-1 quantification, cell sorting, T cell receptor (TCR) repertoire analysis and functional immuno-assays were also performed. Results were compared with samples from 38 cHL and 35 DLBCL patients. We initially compared gene expression of NLPHL and cHL, looking for molecular similarities and differences. Ten non-lymphomatous nodes (NLN) were included as controls. Unsupervised clustering showed all but 3 NLPHL cases segregated from the cHL cluster. All NLN congregated in a discrete sub-cluster. As expected, RNA analysis showed significant enrichment for CD20 in NLPHL and CD30 in HL. Volcano plots (Fig. 1a), corrected for false-discovery showed marked variation in gene expression. For NLPHL (vs. cHL) there were 105 upregulated and 337 down regulated genes. Strikingly, the most significantly differentially over-expressed genes in NLPHL were all T cell related (CD247: CD3 zeta chain; CD3D: CD3 delta chain; GZMK: granzyme K; EOMES: marker of CD8 + T cell tolerance; and the immune checkpoints PDCD1: encodes for PD-1; and TIGIT). CD8B expression was increased in NLPHL. For cHL, the most over-expressed genes included macrophage-derived chemokines CCL17 and CCL22. Gene set enrichment analysis revealed activation of the PD-L1 expression and PD-1 checkpoint pathway and 9 of the top 10 Gene Ontology (GO) term enrichment scores involved lymphocyte signalling in NLPHL (Fig. 1b). To better appreciate the impact of the relevant immune checkpoints on their signalling axis, we compared gene ratios for PD-1 and TIGIT receptors with their ligands (PD-L1/L2 and PVR, respectively). NLPHL showed the highest enrichment ratios of these signalling pathways vs. cHL, DLBCL and NLN (Fig. 1c). Although it is known that CD4 +PD-1 +T cells form rosettes around NLPHL cells, the differential cellular localization of immune proteins has not been compared between HL entities. Using mIF, the proportion of intra-tumoral PD-1 + was markedly higher for CD4 + (~7-fold; p<0.0001) and CD8 + (~5-fold; p<0.001) T cells in NLPHL. However, the proportion of T cells expressing LAG3 was similar. Soluble PD-1 was elevated for both NLPHL and cHL, indicating circulating blood is influenced by the TME. For both HL entities over 80% of circulating CD4 + and CD8 + T cells expressed PD-1 alone or in combination with TIGIT. TCR repertoire analysis of sorted T cell subsets showed large intra-tumoral clonal T cell expansions were also detectable in circulating T cells. T cell clones were predominantly PD1 +CD4 + T cells in both HL types. Finally, we developed a functional assay using PD-L1/PD-L2 expressing NLPHL and cHL cell lines. These were co-cultured with genetically engineered PD-1 +CD4 + T cells that express a luciferase reporter. Similar levels of heightened T cell activation were seen with immune-checkpoint blockade for both HL entities, indicating that immune-checkpoint inhibition may also be of benefit in NLPHL. In conclusion, our multi-faceted analysis of the immunobiological features of the TME in NLPHL, provides a compelling rationale for early phase clinical studies that incorporate immune-checkpoint blockade in NLPHL. Figure 1 Figure 1. Disclosures Hawkes: Bristol Myers Squib/Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Specialised Therapeutics: Consultancy; Merck KgA: Research Funding; Merck Sharpe Dohme: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Antigene: Membership on an entity's Board of Directors or advisory committees; Regeneron: Speakers Bureau; Janssen: Speakers Bureau; Gilead: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Roche: Membership on an entity's Board of Directors or advisory committees, Other: Travel and accommodation expenses, Research Funding, Speakers Bureau. Swain: Janssen: Other: Travel expenses paid; Novartis: Other: Travel expenses paid. Keane: BMS: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy; Karyopharm: Consultancy; MSD: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees. Talaulikar: Takeda: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Jansenn: Honoraria, Research Funding; Roche: Honoraria, Research Funding; EUSA Pharma: Honoraria, Research Funding. Gandhi: janssen: Research Funding; novartis: Honoraria.

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Modulation of the IL-6/STAT3 Signaling Axis in CD4+ T Cells As a Potential Immune Mechanism of Action of Azacytidine in High-Risk Myelodysplastic Syndromes

Blood ◽

10.1182/blood-2019-126504 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 2988-2988

Author(s):

Eleftheria Lamprianidou ◽

Chrysoula Kordella ◽

Anastasiya Kazachenka ◽

Emmanouela Zoulia ◽

Elsa Bernard ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Board Of Directors ◽

Cd4 T Cells ◽

Research Funding ◽

Mononuclear Cells ◽

T Cell Subsets ◽

Advisory Committees ◽

Stat Signaling ◽

Signaling Axis

Azacytidine (AZA), the mainstay of therapy in high risk Myelodysplastic syndromes (HR-MDS), affects CD4+ T-cell polarization and function, but the effect of these changes on tumor immunity is unclear. Signal transducer and activator of transcription (STAT) proteins are key regulators of differentiation and polarization of CD4+ T-cells in both health and cancer, but the STAT signaling architecture of CD4+ T-cell subsets in HR-MDS and its modulation by AZA are currently unknown. We applied single-cell phosphospecific flow cytometry in peripheral blood mononuclear cells from 67 HR-MDS patients at various time-points during AZA therapy. Unsupervised clustering of pretreatment STAT signaling profiles (SPs) of CD4+ T-cells revealed three signaling clusters (SCs), mainly differing in the potentiated responses of STAT3 to IL-6 stimulation (IL-6/STAT3 node). Compared to SC#1 and SC#3, patients in SC#2 displayed higher IL-6/STAT3 levels, higher levels of naïve (TN, p=0.05) and lower levels of PD1+ (p=0.04) and central memory ( TCM, p=0.04) CD4+ T-cells, and longer median overall survival (mOS, p=0.028, fig 1A). Moreover, comparisons of single signaling nodes revealed that the IL-6/STAT3 node correlated inversely with PD1+ (p=0.02) and IL-4+ (p=0.04) and positively with naïve CD4+ (p=0.04) and IFNγ+CD8+ T-cells (p=0.01). No other differences in clinicobiologic parameters, CD4+ and CD8+ T-cell subpopulations (FOXP3, IFNγ, IL-4, IL-17, Perforin and Helios) were noted among the 3 SCs and all other single nodes. To assess the effect of AZA on STAT signaling, we clustered the fold fold-change of pre- versus 6-month post-AZA SPs in CD4+ T-cells. Again the IL6/STAT3 node was the only differentiator among the clusters, and, by single node analysis, downregulation of IL6/STAT3 at 6th cycle (n=26) was associated with better response to AZA (p=0.02) and longer mOS (p=0.03), compared to upregulation of the same node (n=22); the latter also accompanied by an increase of IFNγ+CD8+ cells after AZA, (p=0.02, fig 1B). Further supporting a direct and beneficial modulation of the IL-6/STAT3 axis in CD4+ T-cells by AZA, the kinetics of IL-6/STAT3 during AZA therapy revealed a marked downregulation of the former node both at day15 (p=0.04) and cycle 6 after AZA (p=0.04) in responders (n=5), while no changes were observed in non-responders (n=7). We further compared the transcriptional profiles of isolated bone marrow CD4+ T-cells between responders (n=4) and non-responders to AZA (n=4) by RNA-seq, both prior and after AZA. No significant differences in pretreatment gene expression were identified. By contrast, 105 genes were differentially expressed at cycle 6 compared to pretreatment in responders (FDR<0.2) and 145 genes in non-responders. Gene set enrichment (GSEA) revealed a significant downregulation of the IL-6/STAT3 pathway and the overall inflammatory response after AZA in responders, but a marked upregulation in non-responders, confirming the flow cytometry results (fig 1C). To trace the molecular background associated with the differential regulation of the IL-6/STAT3 pathway we constructed mutational profiles by targeted DNA sequencing of 156 genes in blood mononuclear cells. No associations were found between pre or post-treatment IL-6/STAT3 node and mutational burden. By contrast, mutations in RNA splicing and STAG2 correlated with lower (p=0.02) and higher (p=0.017) pretreatment levels of IL6/STAT3, respectively. Notably, all 5 patients with NPM1/DNMT3A double mutation upregulated significantly IL6/STAT3 after AZA (p=0.03, fig 1D). Collectively, our results reveal for the first time that downregulation of the IL-6/STAT3 signaling axis in CD4+ T cells may represent an immune-mediated mechanism of action of AZA. However, the antileukemic activity of IL-6/STAT3LowCD4+ T-cells appears to be independent from modulation of common metrics of tumor immunity, as, paradoxically, the detrimental IL-6/STAT3 upregulation was linked with an expansion of antitumor T cell subsets and decrease of the immunosuppressive ones. The IL-6/STAT3 axis is notoriously pro-tumorigenic and pharmacologic inhibition of various individual modules of this pathway in cancer is under development. Our findings may serve as a guidepost for the ongoing investigation of IL-6/STAT3 axis inhibition as a therapeutic strategy to overcome azacytidine resistance in HR-MDS. Figure 1 Disclosures Vassilakopoulos: Celgene / GenesisPharma: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; WinMedica: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Pappa:Gilead: Honoraria, Research Funding; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Research Funding; Novartis: Honoraria, Research Funding, Speakers Bureau; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene / GenesisPharma: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Research Funding. Papaemmanuil:Celgene: Research Funding. Kotsianidis:Celgene: Research Funding.

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Pre-Existing T Cell Subsets Determine Anti-PD1 Blockade Response in Richter's Transformation

Blood ◽

10.1182/blood-2020-138601 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 42-43

Author(s):

Prajish Iyer ◽

Lu Yang ◽

Zhi-Zhang Yang ◽

Charla R. Secreto ◽

Sutapa Sinha ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Single Cell ◽

Board Of Directors ◽

Peripheral Blood ◽

Research Funding ◽

Gene Signature ◽

T Cell Subsets ◽

Rna Seq ◽

Advisory Committees

Despite recent developments in the therapy of chronic lymphocytic leukemia (CLL), Richter's transformation (RT), an aggressive lymphoma, remains a clinical challenge. Immune checkpoint inhibitor (ICI) therapy has shown promise in selective lymphoma types, however, only 30-40% RT patients respond to anti-PD1 pembrolizumab; while the underlying CLL failed to respond and 10% CLL patients progress rapidly within 2 months of treatment. Studies indicate pre-existing T cells in tumor biopsies are associated with a greater anti-PD1 response, hence we hypothesized that pre-existing T cell subset characteristics and regulation in anti-PD1 responders differed from those who progressed in CLL. We used mass cytometry (CyTOF) to analyze T cell subsets isolated from peripheral blood mononuclear cells (PBMCs) from 19 patients with who received pembrolizumab as a single agent. PBMCs were obtained baseline(pre-therapy) and within 3 months of therapy initiation. Among this cohort, 3 patients had complete or partial response (responders), 2 patients had rapid disease progression (progressors) (Fig. A), and 14 had stable disease (non-responders) within the first 3 months of therapy. CyTOF analysis revealed that Treg subsets in responders as compared with progressors or non-responders (MFI -55 vs.30, p=0.001) at both baseline and post-therapy were increased (Fig. B). This quantitative analysis indicated an existing difference in Tregs and distinct molecular dynamic changes in response to pembrolizumab between responders and progressors. To delineate the T cell characteristics in progressors and responders, we performed single-cell RNA-seq (SC-RNA-seq; 10X Genomics platform) using T (CD3+) cells enriched from PBMCs derived from three patients (1 responder: RS2; 2 progressors: CLL14, CLL17) before and after treatment. A total of ~10000 cells were captured and an average of 1215 genes was detected per cell. Using a clustering approach (Seurat V3.1.5), we identified 7 T cell clusters based on transcriptional signature (Fig.C). Responders had a larger fraction of Tregs (Cluster 5) as compared with progressors (p=0.03, Fig. D), and these Tregs showed an IFN-related gene signature (Fig. E). To determine any changes in the cellular circuitry in Tregs between responders and progressors, we used FOXP3, CD25, and CD127 as markers for Tregs in our SC-RNA-seq data. We saw a greater expression of FOXP3, CD25, CD127, in RS2 in comparison to CLL17 and CLL14. Gene set enrichment analysis (GSEA) revealed the upregulation of genes involved in lymphocyte activation and FOXP3-regulated Treg development-related pathways in the responder's Tregs (Fig.F). Together, the greater expression of genes involved in Treg activation may reduce the suppressive functions of Tregs, which led to the response to anti-PD1 treatment seen in RS2 consistent with Tregs in melanoma. To delineate any state changes in T cells between progressors and responder, we performed trajectory analysis using Monocle (R package tool) and identified enrichment of MYC/TNF/IFNG gene signature in state 1 and an effector T signature in state 3 For RS2 after treatment (p=0.003), indicating pembrolizumab induced proliferative and functional T cell signatures in the responder only. Further, our single-cell results were supported by the T cell receptor (TCR beta) repertoire analysis (Adaptive Biotechnology). As an inverse measure of TCR diversity, productive TCR clonality in CLL14 and CLL17 samples was 0.638 and 0.408 at baseline, respectively. Fifty percent of all peripheral blood T cells were represented by one large TCR clone in CLL14(progressor) suggesting tumor related T-cell clone expansion. In contrast, RS2(responder) contained a profile of diverse T cell clones with a clonality of 0.027 (Fig. H). Pembrolizumab therapy did not change the clonality of the three patients during the treatment course (data not shown). In summary, we identified enriched Treg signatures delineating responders from progressors on pembrolizumab treatment, paradoxical to the current understanding of T cell subsets in solid tumors. However, these data are consistent with the recent observation that the presence of Tregs suggests a better prognosis in Hodgkin lymphoma, Follicular lymphoma, and other hematological malignancies. Figure 1 Disclosures Kay: Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Sunesis: Research Funding; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; MEI Pharma: Research Funding. Ansell:AI Therapeutics: Research Funding; Takeda: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Bristol Myers Squibb: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; ADC Therapeutics: Research Funding. Ding:Astra Zeneca: Research Funding; Abbvie: Research Funding; Octapharma: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; alexion: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees; DTRM: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding. OffLabel Disclosure: pembrolizumab

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CD4+ T Cell Fate in Multiple Myeloma

Blood ◽

10.1182/blood-2018-99-117674 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 4494-4494

Author(s):

Rachel Elizabeth Cooke ◽

Jessica Chung ◽

Sarah Gabriel ◽

Hang Quach ◽

Simon J. Harrison ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Board Of Directors ◽

Cd8 T Cells ◽

Cd4 T Cells ◽

Research Funding ◽

Flow Cytometric Analysis ◽

Advisory Committees ◽

Mitochondrial Mass ◽

Flow Cytometric

Abstract The average incidence of multiple myeloma (MM) is in the 7th decade that coincides with the development of immunosenescence and thymic atrophy, meaning that lymphocyte recovery after lymphopenia-inducing therapies (most notably autologous stem cell transplant, ASCT) is largely reliant on homeostatic proliferation of peripheral T cells rather than replenishing the T cell pool with new thymic emigrants. We have previously shown that there is a significant reduction in circulating naïve T cells with a reciprocal expansion of antigen-experienced cells from newly diagnosed MM (NDMM) to relapsed/refractory disease (RRMM). This results in a reduced TCR repertoire and the accumulation of senescence-associated secretory phenotype cytotoxic T cells, which maintain the ability to produce IFNγ but lose proliferative potential. A reduction in CD4:8 ratio is also a characteristic finding in MM with disease progression, which can be explained by high IL-15 levels in lymphopenic states that preferentially drive expansion of CD8+ memory T cells. We wanted to further evaluate what changes were occurring in the CD4+ T cell population with disease progression in MM. We analyzed paired peripheral blood (PB) samples from patients with NDMM and RRMM, and compared with age-matched normal donors (ND). In the NDMM cohort, we examined T cells from PB samples at baseline, after 4 cycles of lenalidomide and dexamethasone (len/dex), and after ASCT; and in the RRMM cohort samples from baseline and after 6 cycles of len/dex. We firstly confirmed in flow cytometric analysis of T cells at serial intervals in NDMM patients that the reduction in circulating naïve T cells and in CD4:8 ratio occurs post ASCT and does not recover by time of last follow-up. We next utilised RNA-seq to analyse differences in CD4+ T cells from NDMM, RRMM and ND. CD4+ T cells from RRMM showed downregulation of cytosolic ribosomal activity but maintenance of mitochondrial ribosomal activity and significant upregulation of pathways involved with calcium signalling. To this end, we evaluated mitochondrial biogenesis and metabolic pathways involved with mitochondrial respiration. Flow cytometric analysis of mitochondrial mass showed a marked increase in RRMM compared with ND, in keeping with a shift towards memory phenotype. Key rate-limiting enzymes in fatty acid β-oxidation (CPT1-A, ACAA2 and ACADVL) were all significantly increased in RRMM compared with ND. To analyse whether these cells were metabolically active, we also measured mitochondrial membrane potential and reactive oxygen species (ROS), gating on cells with high mitochondrial mass. Mitochondrial membrane potential was significantly increased in RRMM compared with ND, although ROS was reduced. The significance of this is not clear, as ROS are not only implicated in cell senescence and activation-induced cell death, but are also positively involved in tyrosine kinase and PI3K-signalling pathways. PD-1 has been shown to play a role in transitioning activated CD4+ T cells from glycolysis to FAO metabolism, and elevating ROS in activated CD8+ T cells. We analysed PD-1 expression on T cells in RRMM and at treatment intervals in NDMM (as described earlier). The proportion of CD4+ and CD8+ T cells expressing PD-1 was increased 4-6 months post-ASCT and remained elevated in CD4+ T cells 9-12 months post-ASCT, but normalised to baseline levels in CD8+ T cells. Increased PD-1 expressing CD4+ T cells was also evident in RRMM patient samples. This may suggest that in the lymphopenic state, PD-1 expression enhances longevity in a subset of CD4+ T cells by promoting reliance on mitochondrial respiration; however, their ability to undergo homeostatic proliferation is impaired. In CD8+ T cells, high PD-1 expression may lead to cell death via ROS accumulation, and these cells do not persist. ASCT remains a backbone of myeloma treatment in medically fit patients. However, this leads to significant permanent defects in the T cell repertoire, which may have unintended adverse outcomes. Additionally, T cells post-ASCT may not be metabolically adequate for the production of CAR-T cells, nor respond to checkpoint blockade therapies. Disclosures Quach: Amgen: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Sanofi Genzyme: Research Funding; Janssen Cilag: Consultancy. Harrison:Janssen-Cilag: Other: Scientific advisory board. Prince:Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen Cilag: Honoraria, Membership on an entity's Board of Directors or advisory committees.

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The Spatial Heterogeneity in Newly Diagnosed Multiple Myeloma Patients - from Sub-Clonal Architecture to the Immune Microenvironment

Blood ◽

10.1182/blood-2021-150937 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 729-729

Author(s):

Lukas John ◽

Alexandra Poos ◽

Stephan M Tirier ◽

Jan-Philipp Mallm ◽

Nina Prokoph ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Medicinal Product ◽

Board Of Directors ◽

Research Funding ◽

Tumor Heterogeneity ◽

Investigational Medicinal Product ◽

Mutational Signatures ◽

Advisory Committees ◽

Cell Clones

Abstract Tumor heterogeneity plays a significant role in the development of therapy resistance in multiple myeloma (MM). Focal lesions (FLs), which are nodular accumulations of MM cells, have been shown to be hotspots of genetic spatial tumor heterogeneity, which is characterized by unique tumor sub-clones at different sites in the bone marrow (BM). However, little is known about the mechanisms leading to mutations in FLs, the architecture of the tumor microenvironment (ME) at these sites, and the link between FL sub-clones and relapse. We applied whole genome sequencing (WGS) to CD138 + MM cells from paired FL and iliac crest random BM aspirates (RBMA) of 15 newly diagnosed MM (NDMM) patients. For 7 of these patients, single cell (sc) analyses were performed, including sc gene expression (scRNA) and T-cell receptor (TCR)-sequencing and sc assay for transposase-accessible chromatin (ATAC)-sequencing for paired BM CD138 + MM and CD138 - ME, as well as peripheral blood mononuclear cells (PBMC). WGS data was analyzed using inhouse pipelines. Mutations, copy-number-variations and mutational signatures were called using mpileup, ACESeq and mmsig. Neoantigen epitopes were predicted using NeoPredPipe. Sc data was generated using the 10X Genomics platform. Pre-processing and analysis of the sc data was performed with CellRanger and the R-packages Seurat, ArchR and inferCNV. In 13/15 patients we found significant differences in chromosomal and mutational profiles between FLs and paired RBMAs, with major unshared mutations (mutation seen in > 60% cells) being enriched at the FL site (mean 310 vs. 123, p<0.05). Mutations in driver genes, such as KRAS, CYLD, CDKN2C and TP53, were site-unique or strongly enriched in FLs in 6/15 patients. To identify the mechanisms underlying heterogeneous mutations, we analyzed mutational signatures and found COSMIC signature SBS18 in these mutations, suggesting a role of reactive oxygen species. Combining WGS and sc sequencing, we observed between 3 and 6 sub-clones per patient. Sub-clones, which dominated in FLs, showed increased regulatory accessibility and expression of genes associated with disease aggressiveness and drug resistance such as CXCR4 and members of the NFKB- and interferon pathways, implying that FLs could play a significant role in the development of treatment resistance. Indeed, comparing sub-clones at baseline and at relapse after high-dose melphalan and autologous stem cell transplantation in one patient, we observed expansions of tumor cells at relapse, which were closely related to the main FL sub-clone at baseline. On average, 23 (range 0-83) site-unique baseline mutations were predicted to be neoantigens. Thus, we hypothesized that spatial tumor heterogeneity could be associated with heterogeneity in the tumor ME. We did not observe expansion of site-unique T cell clones, but some of the clones were enriched up to 10-fold at one of the two sites. These clones were typically seen in the PB at low frequency. Expanded T-cells clones were almost exclusively found in the CD8 +-compartment, with 65% and 27% of expanded T-cell clones being CD45RO +/CD57 +-memory- and CD69 +-effector-T-cells, respectively. Besides differences in the T-cell clonality, we observed changes in proportions of other cell types, including a depletion of CD14+- and CD16+-macrophages in FLs (p<0.05). Furthermore, we observed gene expression differences between FL and RBMA macrophages, especially for genes involved in TNFα, IL-6 and JAK/STAT3 signaling. While CCL2, CD44, CXCL2/3, KLF2/4 and CCR1 were significantly higher expressed in FLs compared to RBMAs, BTG2, DUSP1 and HIF1A were down-regulated. In conclusion, our results strengthen the concept of MM as a spatially heterogeneous disease, suggest that reactive oxygen species result in site-specific mutagenesis, and support the hypothesis that FLs are the origin of aggressive disease. We demonstrate spatial heterogeneity at single-cell level in the BM immune ME for the first time, which implies that understanding the complex biology of FLs could be important in the context of novel immune therapies such as bispecific antibodies and CAR-T-cells. Disclosures John: Janssen: Consultancy. Müller-Tidow: Janssen Cilag: Consultancy, Research Funding; Bioline: Consultancy, Research Funding; Pfizer: Consultancy, Research Funding. Goldschmidt: Takeda: Consultancy, Research Funding; Sanofi: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Dietmar-Hopp-Foundation: Other: Grant; Novartis: Honoraria, Research Funding; Mundipharma: Research Funding; MSD: Research Funding; Molecular Partners: Research Funding; Johns Hopkins University: Other: Grant; Janssen: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Incyte: Research Funding; GSK: Honoraria; Chugai: Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; BMS: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Celgene: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Adaptive Biotechnology: Consultancy; Amgen: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding. Raab: Janssen: Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy; GSK: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Consultancy, Honoraria; BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees. Weinhold: Sanofi: Honoraria.

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Long-Term Remission of CLL Sustained By Pauciclonal Anti-CD19 Chimeric Antigen Receptor T (CTL019) Cell Clones

Blood ◽

10.1182/blood-2018-99-117390 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 699-699 ◽

Cited By ~ 2

Author(s):

J. Joseph Melenhorst ◽

David L. Porter ◽

Lifeng Tian ◽

Simon F Lacey ◽

Christopher L Nobles ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Board Of Directors ◽

Research Funding ◽

Integration Site ◽

Advisory Committees ◽

Car T Cells ◽

Car T Cell ◽

Cell Clones ◽

Car T

Abstract We recently demonstrated that sustained remission in 41 CLL patients treated with the CD19-specific, 4-1BB/CD3zeta-signaling chimeric antigen receptor (CAR19) T-cells correlated strongly with the expansion and persistence of the engineered T cells and that important pathways such as T cell exhaustion, glycolysis and T cell differentiation segregated responders from non-responders (Fraietta et al., 2018, Nature Medicine). We here report two advanced, chemotherapy-resistant CLL patients with the longest (7 years) follow-up on any trial of CART19 cells. Both patients had received five therapies before being treated at the University of Pennsylvania with autologous, murine CTL019 (tisagenlecleucel) cells for their CLL in 2010, receiving 1.1e9 and 1.4e7 CAR19+ T cells, respectively. Both patients have persistence of CAR-engineered T cells and both patients are still in remission as determined by flow cytometry and deep sequencing of IgH rearrangements for 5.5-7 years. Thus, the infused CAR-T cells have maintained these patients in deep molecular remission of their disease for the longest period of time that has been reported to date. To understand the fate of the infused CAR-T cells we determined the phenotype, function, and clonal nature of the persisting CTL019 cells. Flow cytometric CART19 cell analyses demonstrated that early during the anti-leukemia response, activated, HLA-DR-expressing CD8+ CAR-T cells rapidly expanded, followed by similarly activated CD4+ CAR-T cells. With tumor clearance the CAR-T cell population contracted, but an activated CD4+ CAR-T cell population was maintained and was still detectable at the last follow-up of 7 years. The CD8+ CAR-T cell pool remained present at low frequencies. Both populations had acquired and maintained an effector memory phenotype, a phenotype most consistent with active disease control. Furthermore, the analysis of the classical immune checkpoint inhibitory markers PD1, TIM3, LAG3, and CTLA4 showed that only PD1 was expressed from the earliest to the latest time point on >80% of all CAR-T cells, whereas LAG3 and TIM3 were expressed only early on but lost after tumor clearance. These data suggest that the initial tumor clearance was mediated by CD8+ CAR-T cells, but sustained by a CD4+ CAR-T cell population that still actively engages with target cells. To understand the clonal nature of these long-term persisting CAR-T cells we used two complementary methods: a) CAR T cells were sorted from post-infusion aliquots during the first two years for T cell receptor-beta deep-sequencing (TCR-seq); b) the CAR integration sites in the genome were sequenced in the infusion product and in circulating CAR-T cells. TCR-seq analysis of early post-infusion time points demonstrated that the circulating CAR-T cell populations consisted of hundreds to thousands of distinct clones which in patient 1 and 2 displayed clonal focusing by 21 and 1 month post-infusion, respectively, with some clones making up as much as 12% (patient 1) and 48% (patient 2) of the CAR-T cell repertoire. The analysis of clonotype sharing at the various time points via Morisita's overlap index analysis similarly showed repertoire stabilization late (21 months; patient 1) and early (1 month; patient 2) after infusion. Lastly, fate mapping of the infused CART19 cells via CAR integration site analysis in the infusion product until the latest time point indicated that the infusion products for both patients had a very diverse, non-clonal make-up, containing over 8,000 and 3,700 integration sites in patients 1 and 2, respectively. The higher degree of clonality in patient 2 but not 1 CAR-T cells as seen by TCR-seq was confirmed by integration site analysis, as was the sharing of CAR-T cell clones over time. Importantly, whereas the CAR integration site repertoire in patient 1 was diverse in the first two years, it stabilized and trended towards oligoclonality 21 months after infusion. Lastly, CAR integration site analysis revealed a high degree of clonal persistence, suggesting that tumor control and B cell aplasia were maintained by few, highly functional CD4+ CAR-T cell clones. In summary, we demonstrate that in both patients with the longest persistence of CAR-T cells reported thus far, early and late phases of the anti-CLL response are dominated by highly activated CD8+ and CD4+ CAR-T cells, respectively, largely comprised of a small number of persisting CD4+ CAR-T cell clones. Disclosures Melenhorst: Parker Institute for Cancer Immunotherapy: Research Funding; Incyte: Research Funding; Casi Pharmaceuticals: Consultancy; novartis: Patents & Royalties, Research Funding; Shanghai UNICAR Therapy, Inc: Consultancy. Porter:Genentech: Other: Spouse employment; Novartis: Other: Advisory board, Patents & Royalties, Research Funding; Kite Pharma: Other: Advisory board. Lacey:Novartis Pharmaceuticals Corporation: Research Funding; Tmunity: Research Funding; Novartis Pharmaceuticals Corporation: Patents & Royalties; Parker Foundation: Research Funding. Fraietta:Novartis: Patents & Royalties: WO/2015/157252, WO/2016/164580, WO/2017/049166. Frey:Novartis: Consultancy; Servier Consultancy: Consultancy. Young:Novartis: Patents & Royalties, Research Funding. Siegel:Novartis: Research Funding. June:Novartis Pharmaceutical Corporation: Patents & Royalties, Research Funding; Immune Design: Membership on an entity's Board of Directors or advisory committees; Tmunity Therapeutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; Immune Design: Membership on an entity's Board of Directors or advisory committees; Celldex: Consultancy, Membership on an entity's Board of Directors or advisory committees; Novartis Pharmaceutical Corporation: Patents & Royalties, Research Funding; Tmunity Therapeutics: Equity Ownership, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding.

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Transcriptomic Analysis of CD4+ T Cell Dysfunction during Gvhd: Evidence for Profound Reprograming of T Cell Signaling during Acute Gvhd That Is Controlled during CD28:CD80/86 Costimulation Blockade with Abatacept

Blood ◽

10.1182/blood-2019-131955 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 596-596

Author(s):

Benjamin Watkins ◽

Yvonne Suessmuth ◽

Kayla Betz ◽

Alison Yu ◽

Brandi Bratrude ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Board Of Directors ◽

T Cell Activation ◽

Cd4 T Cells ◽

Research Funding ◽

Costimulation Blockade ◽

Research Support ◽

Advisory Committees ◽

Highly Correlated

Although acute graft-versus-host-disease (AGVHD) is one of the major causes of non-relapse mortality after hematopoietic stem cell transplant (HCT), we are still unable to predict which patients will develop the most severe form of this disease, or which molecular pathways are dysregulated in the T cells that cause disease. Thus, understanding the molecular features of AGVHD is a critical unmet need. To address this, we have performed a companion mechanistic study as a part of our completed Phase 2 trial of abatacept, a CD28:CD80/86 costimulation blockade agent, for severe AGVHD prevention (Clinicaltrials.gov # NCT01743131, 'ABA2'). ABA2 has demonstrated significant improvement in AGVHD in patients prophylaxed with abatacept in addition to calcineurin inhibition (CNI) + Methotrexate (MTX) compared to controls receiving CNI/MTX alone. To begin to uncover mechanisms responsible for the control of AGVHD with abatacept, and given that CD4+ T cells have been consistently documented to be the main therapeutic target of this drug, we interrogated the transcriptome of CD4+ T cells reconstituting in patients prophylaxed with abatacept compared to CNI/MTX. To perform this analysis, we flow cytometrically sorted CD4+ T cells on Days 21-28 post-transplant from all patients on ABA2, as well as a cohort of 12 untransplanted healthy controls, and subsequently performed mRNA-sequencing on these cells. Weighted Gene Correlation Network Analysis (WGCNA) was performed on the top 6000 most variant transcripts from the resulting sequencing data. Hierarchical clustering of the WGCNA co-expression matrix enabled the identification of self-assembling modules (SAMs) that met a threshold of coexpression (Figure 1A). For the ABA2 dataset, we considered the following variables in the WGCNA model: patient cohort (7/8 patients, 8/8 patients, healthy controls), +/- prophylaxis with abatacept, CMV reactivation, EBV reactivation, Grade of GVHD (0-4), relapse, non-relapse mortality, and all-cause mortality. The WGCNA clustering analysis resulted in the identification of 4 discrete SAMs, which were highly correlated with clinical variable metamodules. This analysis revealed a strong positive correlation of a 476-gene SAM (the Turquoise module) in patients prophylaxed with CNI/MTX + placebo and anti-correlation of this module in patients prophylaxed with CNI/MTX + abatacept, as demonstrated in both the WGCNA heatmap and through Gene Set Enrichment Analysis (Figure 1 A-B). These opposing correlations suggested that interrogation of this module would reveal mechanistic correlates with standard prophylaxis that were decoupled by abatacept. Pathway analysis using the Reactome database (Figure 1C) revealed the turquoise SAM to be dominated by four types of pathways: (1) Those that define canonical cell-cycle pathways (2) Those involved in T cell metabolism (3) Those involved in apoptosis and (4) Those involved in T cell activation, consistent with upregulation of these transcripts in placebo versus abatacept patients. In addition to being highly correlated with patients receiving placebo, the expression of a subset of the transcripts in the Turquoise module were also directly correlated with the severity of AGVHD in these patients. Thus, linear regression analysis of the 476 transcripts in this module identified a subset of 93 genes for which transcript expression level was increased both in placebo compared to abatacept, and for which expression level also positively correlated with Grade of AGVHD. As with the Turquoise module as a whole, this subset of genes also formed a highly correlated network, linking transcripts involved in T cell proliferation, apoptosis, activation, metabolism as well as the T cell checkpoint (Figure 1D). This analysis represents the first comprehensive interrogation of the transcriptomic correlates of AGVHD. It identifies a novel set of transcripts which positively associate with the severity of AGVHD, and which costimulation blockade with abatacept down-regulates and de-couples from AGVHD severity. These results suggest a profound reprograming of T cell activation with abatacept that is correlated with the control of AGVHD. Disclosures Qayed: Bristol-Myers Squibb: Honoraria. Langston:Astellas Pharma: Other: Research Support; Incyte: Other: Research Support; Jazz Pharmaceuticals: Other: Research Support; Chimerix: Other: Research Support; Takeda: Other: Research Support; Kadmon Corporation: Other: Research Support; Novartis: Other: Research Support; Bristol Myers Squibb: Other: Research Support. Blazar:Fate Therapeutics, Inc.: Research Funding; RXi Pharmaceuticals: Research Funding; Alpine Immune Sciences, Inc.: Research Funding; Abbvie Inc: Research Funding; Leukemia and Lymphoma Society: Research Funding; Childrens' Cancer Research Fund: Research Funding; KidsFirst Fund: Research Funding; Tmunity: Other: Co-Founder; BlueRock Therapeutics: Membership on an entity's Board of Directors or advisory committees; Kamon Pharmaceuticals, Inc: Membership on an entity's Board of Directors or advisory committees; Five Prime Therapeutics Inc: Co-Founder, Membership on an entity's Board of Directors or advisory committees; Regeneron Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Magenta Therapeutics and BlueRock Therapeuetics: Membership on an entity's Board of Directors or advisory committees. Kean:HiFiBio: Consultancy; BlueBirdBio: Research Funding; Gilead: Research Funding; Regeneron: Research Funding; EMDSerono: Consultancy; FortySeven: Consultancy; Magenta: Research Funding; Kymab: Consultancy; Jazz: Research Funding; Bristol Meyers Squibb: Patents & Royalties, Research Funding. OffLabel Disclosure: Abatacept: Approved for Rheumatoid Arthritis; used in this trial for prevention of GVHD.

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Increased TACE (Tumor necrosis factor-alpha±-converting enzyme; ADAM17) Activity Associates with Decreased CD62L Expression, Increased Soluble CD62L Plasma Levels and Predicts Molecular Response to Nilotinib Therapy in Patients with Early Chronic Phase Chronic Myelogenous Leukemia (CML-CP): Results from an ENEST1st Substudy

Blood ◽

10.1182/blood.v126.23.4033.4033 ◽

2015 ◽

Vol 126 (23) ◽

pp. 4033-4033 ◽

Cited By ~ 1

Author(s):

Sieghart Sopper ◽

Satu Mustjoki ◽

Angelica Loskog ◽

Bjorn T. Gjertsen ◽

Guenther A. Gastl ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Board Of Directors ◽

Research Funding ◽

Immune Cell ◽

T Cell Subsets ◽

Molecular Response ◽

Advisory Committees ◽

Expression Levels

Abstract Background and Aim: Tyrosine kinase inhibitors (TKI) imatinib and dasatinib modulate immune responses in vitro and in vivo. Immunological surveillance in the MRD-situation might be of particular relevance for long-term control or even elimination of CML-repopulating stem cells. Moreover, baseline immunological characteristics may be associated with response to TKI therapy. Little is known about potential immune-modulatory effects of nilotinib in vivo. The ENEST1st study (NCT01061177) evaluated the role of first-line nilotinib therapy in CML-CP. The primary endpoint was the MR4 rate at 18 months. A comprehensive immunological monitoring program within this ENEST1st substudy characterized baseline and therapy-induced immunological variables to correlate them with biological disease characteritics and clinical response parameters. Methods: Peripheral blood was taken prior to treatment initiation and after 6 and12 months (mo) from 52 patients. Samples were analyzed by nine colour flow cytometry employing six panels of optimized antibodies to determine various leukocyte populations (e.g. T cell subpopulations including Treg and NKT cells, NK cells, B cells, monocytes, MDSC, dendritic cell subsets). Plasma concentrations of soluble CD62L (sCD62L) and TACE (tumor necrosis factor-α-converting enzyme; ADAM17, CD156b), the metalloproteinase inducing proteolytic cleavage of CD62L from the cell surface, were either measured by ELISA or (in case of the enzymatic activity of TACE) using a fluorogenic assay. Changes in immune cell parameters were correlated to biological disease features and clinical endpoints. Results: The most striking finding of this study is the drastic loss of the lymph-node homing marker CD62L on immune cells (T cell subsets and granulocytes) at baseline (basCD62L), which increased back to normal levels during nilotinib therapy. The proportion of basCD62L+ cells among both CD4+ and CD8+ T cell subsets significantly correlated with Sokal score (both as continous and categorial variable, i.e. high vs. low/int). Low basCD62L expression levels on both T cell subsets correlate with increased spleen size, higher BM and PB blast and WBC counts as well as it correlates to higher BCR-ABL copy numbers at almost all time points during treatment. Similarly, lower basCD62L on either CD4+ or CD8+ T cells is linked to a longer duration to reach the respective molecular endpoint. Patients reaching MR4 at 18 months (primary study endpoint) had significantly higher levels of basCD62L on both CD4+ (p=0.02) and CD8+ (p=0.008) T cells. Consequently, MR4 at 18 months was attained in a significantly higher percentage of patients in the basCD62hi compared to the CD62lo patients (63% vs. 13.0%). Vice versa, patients who reached MR4 at 18 months had significantly higher proportions of basCD62L expressing cells among both CD4+ and CD8+ T cells. Moreover, as depicted by a cumulative response rate, patients with high proportions of basCD62Lhi T cells, achieved MMR and MR4 significantly earlier and in a higher proportion throughout the observation period. A detailed characterization of other T cell differentiation marker (CD45RA, CD45R0, CD28, CD27, and CD95) did not reveal significant baseline T cell subset alterations as explanation for altered CD62L expression. In contrast to low basCD62L surface expression levels, its shed form sCD62L is significantly increased at diagnosis but subsequently drops back during nilotinib therapy. Similar to surface CD62L expression, also sCD62L associates with biological disease features and molecular response to nilotinib. Finally, low CD62L surface expression was associated with elevated sCD62L levels and increased proteolytic activity but not total amount of TACE. Conclusion: At baseline, increased proteolytic activity of TACE sheds CD62L from the immune cell surface. During nilotinib therapy, TACE activity gets normalized leading to re-expression of CD62L on T cells and vice versa a drop of sCD62L. Low baseline T cell expression levels of CD62L and increased sCD62L levels correlate to a more aggressive CML phenotype and are linked to inferior molecular response to nilotinib in early CML-CP. Larger prospective studies including also other TKIs are needed to confirm the prognostic relevance of sCD62L/CD62L expression as response-prediction marker, as this marker is easy to measure by ELISA in plasma samples or flow-cytometry. Disclosures Mustjoki: Finnish Cancer Institute: Research Funding; Sigrid Juselius Foundation: Research Funding; Academy of Finland: Research Funding; the Finnish Cancer Societies: Research Funding; Pfizer: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding; Signe and Ane Gyllenberg Foundation: Research Funding. Loskog:RePos Pharma AB: Membership on an entity's Board of Directors or advisory committees; Vivolux AB: Membership on an entity's Board of Directors or advisory committees; Lokon Pharma AB: Employment, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties, Research Funding; NEXTTOBE AB: Membership on an entity's Board of Directors or advisory committees; Alligator Bioscience AB: Patents & Royalties. Gjertsen:Haukeland University Hospital: Research Funding. Giles:Novartis: Consultancy, Honoraria, Research Funding. Ossenkoppele:Pfizer: Honoraria, Research Funding; ARIAD: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Novartis: Honoraria, Research Funding. Porkka:Bristol-Myers Squibb: Honoraria; Celgene: Honoraria; Novartis: Honoraria; Pfizer: Honoraria.

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Galectin-3 Signaling in Donor T Cells Regulates Acute Graft Versus Host Disease (aGvHD) after Allogenic Transplantation

Blood ◽

10.1182/blood-2021-150777 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 2765-2765

Author(s):

Hemn Mohammadpour ◽

Takemasa Tsuji ◽

Cameron R. MacDonald ◽

Joseph L. Sarow ◽

Jingxin Qiu ◽

...

Keyword(s):

Cell Proliferation ◽

T Cells ◽

T Cell ◽

Board Of Directors ◽

Cd4 T Cells ◽

Research Funding ◽

T Cell Proliferation ◽

Advisory Committees ◽

Human T Cells ◽

Donor T Cells

Abstract Galectin-3 (Gal-3) is a unique member of the galectin family of lectins. Gal-3 possesses immune-regulatory functions depending on the immune cell and the immunologic situation. There are no studies that specifically delineate the role of Gal-3 in the setting of acute GvHD but mounting research suggests that dysregulation of pathways involving the galectin family may contribute to the pathogenesis of other immune disorders. Gal-3 is expressed by many types of immune cells, including T-cells. It suppresses signaling downstream of the TCR, decreases effector T-cell cytokine production, but increases the development and differentiation of memory T cells, myeloid cells, and macrophages. We investigated the mechanisms and downstream events of Gal-3 signaling in donor T cells after Allo-HCT, using Gal-3 knockout (Gal-3 -/-) mice. We further studied the effect of Gal-3 in controlling aGvHD incidence and severity while preserving the Graft-versus Leukemia (GvL) effect by overexpressing Gal-3 in human T cells. We utilized both a major MHC-mismatch (C57B/6 (H-2 b) into BALB/c (H-2 k) model and a MHC-matched, multiple minor histocompatibility antigen (miHA) mismatched B6 (H-2 b) into C3H/SW (H-2 b) model. Lethally irradiated recipient BALB/c and C3H/SW WT animals were injected with T cell depleted bone marrow alone (3 ×10 6) or with splenic T cells derived from allogeneic WT or Gal-3 -/- B6 donors (0.7 × 10 6 T cells in B6 → BALB/c and 1.5 × 10 6 in B6 → C3H/SW). We found that donor T cells express Gal-3 after Allo-HCT and that Gal-3 expression in WT T cells plays an important role in controlling GvHD, as evidenced by less severe weight loss, decreased clinical GvHD scores, and longer survival when compared to mice receiving Gal-3 -/- donor T cells (Figure 1A). We studied the mechanisms by which Gal-3 signaling controls the severity of aGvHD. Using flow cytometry analysis, we determined that Gal-3 plays a critical role in T cell proliferation and exhaustion. Gal-3 -/- T cells have a cytotoxic T phenotype with increased IFN-ℽ and GM-CSF production in T cells from the spleen and liver tissues on days 7 and 14 after Allo-HCT when compared to WT T cells (Figure 1B). There was a significant increase in T cell proliferation in Gal-3 -/- CD4 +T cells with a significantly higher level of IFN- ℽ mediated activation induced cell death (AICD) when compared to WT T cells. Gal-3 expression in T cells significantly increased the expression of exhaustion markers evidenced by a higher percentage of Slamf6 + Tim-3 + in WT T cells when compared to Gal-3 -/- T cells (Figure 1B). Gal-3 induced T cell exhaustion by through overactivation of NFAT signaling (data not shown). We sought to determine whether overexpression of Gal-3 in human T cells could control GvHD without affecting GVL. Gal-3 was overexpressed in human T cells using retrovirus containing Gal-3, vector alone and control T cells: Gal-3 T cells (T RV-Gal-3), GFP T cells (T RV-GFP) and control T cells were injected in irradiated NSG-HLA-A2 mice. All human cells expressed HLA-A2. Gal-3 overexpression in T cells effectively controlled the severity and mortality of GvHD after Allo-HCT in this humanized murine model of GvHD, evidenced by decreased body weight loss and decreased GvHD clinical scores in recipients transplanted with Gal-3 T cells when compared to control or GFP T cells (Figure 1C). Gal-3 overexpression did not impair the GvL effect when T cells cultured with Raji and THP-1 cell lines in vitro (data not shown). Gal-3 overexpression in T cells increased the frequencies of exhausted CD4 + T cells, and central memory CD4 + T cells while decreasing the percentage of effector CD4 T cell and INF-ℽ + CD4 + T cells. Clinical GI colon biopsies from patients undergoing allo-HCT were evaluated for Gal-3 expression in T cells using the multi-color Vectra 3 Automated Quantitative Pathology Imaging System. T cells in the colon biopsies expressed Gal-3. There was a significant correlation between Gal-3 MFI in CD4+ T cells, and GI histopathology score when analyzing Gal-3 intensity on Gal-3-expressing T cells. The Gal-3 MFI in CD4+ T cells was significantly lower in biopsies with higher colon GI histopathology scores (III-IV) compared to with lower colon GI histopathology scores I-II. In conclusion, these data reveal how Gal-3 can influence donor T cell proliferation and function in preclinical aGvHD models and point to the feasibility of manipulation of Gal-3 signaling to ameliorate aGvHD in the clinical setting. Figure 1 Figure 1. Disclosures Blazar: Rheos Medicines: Research Funding; Carisma Therapeutics, Inc: Research Funding; Equilibre Pharmaceuticals Corp: Research Funding; Tmunity Therapeutics: Other: Co-founder; BlueRock Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Magenta Therapeutics: Membership on an entity's Board of Directors or advisory committees. McCarthy: Magenta Therapeutics: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bluebird: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Juno: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees.

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