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Siglec-7 represents a glyco-immune checkpoint for non-exhausted effector memory CD8+ T cells with high functional and metabolic capacities

While inhibitory Siglec receptors are known to regulate myeloid cells, less is known about their expression and function in lymphocytes subsets. Here we identified Siglec-7 as a glyco-immune checkpoint expressed on non-exhausted effector memory CD8+ T cells that exhibit high functional and metabolic capacities. Seahorse analysis revealed higher basal respiration and glycolysis levels of Siglec-7+ CD8+ T cells in steady state, and particularly upon activation. Siglec-7 polarization into the T cell immune synapse was dependent on sialoglycan interactions in trans and prevented actin polarization and effective T cell responses. Siglec-7 ligands were found to be expressed on both leukemic stem cells and acute myeloid leukemia (AML) cells suggesting the occurrence of glyco-immune checkpoints for Siglec-7+ CD8+ T cells, which were found in patients’ peripheral blood and bone marrow. Our findings project Siglec-7 as a glyco-immune checkpoint and therapeutic target for T cell-driven disorders and cancer.

While inhibitory Siglec receptors are known to regulate myeloid cells, less is known about their expression and function in lymphocytes subsets. Here we identified Siglec-7 as a glyco-immune checkpoint expressed on nonexhausted effector memory CD8+ T cells that exhibit high functional and metabolic capacities. Seahorse analysis revealed higher basal respiration and glycolysis levels of Siglec-7 + CD8+ T cells in steady state, and particularly upon activation. Siglec-7 polarization into the T cell immune synapse was dependent on sialoglycan interactions in trans and prevented actin polarization and effective T cell responses. Siglec-7 ligands were found to be expressed on both leukemic stem cells and acute myeloid leukemia (AML) cells suggesting the occurrence of glyco-immune checkpoints for Siglec-7 + CD8+ T cells, which were found in patients' peripheral blood and bone marrow. Our findings project Siglec-7 as a glyco-immune checkpoint and therapeutic target for T cell-driven disorders and cancer.

Introduction
Siglecs are surface receptors that are differentially and broadly expressed on immune cells, and have recently emerged as critical immune checkpoints in health, inflammatory disease and cancer (1)(2)(3)(4). These lectin receptors are thought to protect from autoreactivity by recognition of sialic-acid containg carbohydrates (sialoglycans) as so-called self-associated molecular patterns (SAMPs) (5). However, such sialoglycan ligands are overexpressed in a variety of different types of malignancies (6), eventually leading to tumor immune evasion by engagment of inhibitory Siglec receptors (7). Whereas Siglec-mediated suppression of immune responses could be therapeutically exploited in autoimmune and inflammatory disease, targeting Siglecs might restore anti-tumor responses as a form of normalization cancer immunotherapy (8). Indeed, a broad range of anti-Siglec therapies are currently explored in pre-clinical studies and first candidate drugs have been forwarded to evaluation in clinical trials (1,9,10).
The expression of Siglecs has been reported to be low or absent on human T cells (11-13). However, we and others recently reported enhanced Siglec expression on peripheral blood and tumor infiltrating T cells of cancer patients (14,15). Notably, in melanoma tissues the majority of tumor-infiltrating lymphocytes consisted of Siglec-9 + CD8 + T cells (15). Mechanistic studies revealed that Siglec-7 and -9 can directly suppress TCR signaling (12, 15), which results in synergistic effects yet involves disparate signaling pathways compared to the immune checkpoint receptor PD1 (15). Together, these observations invigorate the interest in the role of Siglecs for T cell biology (3).
In the present study, we identified Siglec-7 as a glyco-immune checkpoint receptor on non-exhausted effector memory CD8 + T cells with high functional and metabolic capacities, and a history of previous clonal expansion. Notably, Siglec-7 was found to congregate within the T cell immune synapse which was associated with reduced CD8 + T cell effector functions including cytotoxicity and cytokine production. Primary leukemic cells and stem cells from patients with acute myeloid leukemia (AML), a malignancy so far ineffectively treated with immune checkpoint therapy, expressed high levels of Siglec-7 ligands. This might adversily affect effector responses of Siglec-7 + CD8 + T cells, which were found in the blood and bone marrow of AML patients. The understanding of Siglec-7 as a clonality-associated glyco-immune checkpoint might inspire novel therapeutic approaches to T cell-associated disorders and cancer.

Cells and tissues
Blood from healthy donors was collected upon informed consent or buffy coats were purchased from the Blood Transfusion Center of Bern, Switzerland. Mononuclear cells were obtained by density centrifugation using Pancoll solution (PAN-Biotech, Aidenbach, Germany). For functional experiments, CD8+ T-cells were isolated using the EasySep ™ Human CD8 + T Cell Isolation Kit (StemCell Technologies, Vancouver, Canada), according to the manufacturer's instructions. The purity of isolated cells was >95%. For experiments with CD8 + T cells subsets, cells were isolated using fluorescence-activated cell sorting (FACS Aria, BD Biosciences, Franklin Lakes, USA). Informed consent was obtained from all patients prior to tissue sample collection. Peripheral blood and BM aspiration samples were obtained from untreated AML patients at the University Hospital of Bern (Switzerland) after informed consent. Samples were stored in liquid nitrogen. AML bone marrow samples were thawed using citrate-dextrose solution in a concentration 1:10 in order to avoid cell clumping. Samples were washed and resuspended in FCS-containing medium prior to staining. All studies using human material were in accordance with the Helsinki Declaration and approved by the cantonal ethics committee of Bern, Switzerland. Written informed consent was received from participants prior to inclusion in the study. For redirected cytotoxic assay, the mouse mastocytoma cell line P815 (American Type Culture Collection ATCC, Manassas, VA, USA) was used exclusively between passage 5 and 8. No mycoplasma testing was performed.

RNA analysis on TCGA database
TCGA RNA-seq data were retrieved from the GDC portal (https://portal.gdc.cancer.gov/) using the following filtering rules: Disease Type IS myeloid leukemias AND Workflow Type IS HTSeq -Counts AND Experimental Strategy IS RNA-Seq. The dataset consisted of 818 samples derived from 740 patients (274 primary cancer/bone marrow; 265 primary cancer/peripheral blood; 140 recurrent cancer/bone marrow; 139 recurrent cancer/peripheral blood). We defined the top/bottom 25% (n = 205) samples based on SIGLEC7 (ENSG00000168995.12) and SIGLEC9 (ENSG00000129450.7) expression values (transcript per million), respectively. Differential gene expression analysis was done between the "top" and "bottom" groups of samples (separately for Siglec-7 and Siglec-9) using DESeq2 and raw gene counts. Gene set enrichment analysis was done with GSEA 4.0.3 and the MSigDB v7.0 (16), using the "hallmark gene sets", and the following options: -nperm 1000 -scoring_scheme weighted -plot_top_x 200 -rnd_seed timestamp -set_max 500 -set_min 15. Input genes were all the differentially expressed genes with a padj value below 0.05. Plots were made in R 3.6.3 using ggplot2.
Telomere length measurement by automated multicolor flow-FISH For telomere length analysis, human CD8 + T cells Siglec-9 + , Siglec-7 + and Siglec-9 -/7subsets were isolated from the peripheral blood of 3 healthy donors by fluorescence-activated cell sorting as described above. Telomere length measurement by in situ hybridization and flow cytometry (automated multicolor flow-FISH) was performed as previously done (6): Briefly, 2.5 × 10 3 to 2 × 10 6 cells were used for in situ hybridization. Cells were in cubated with 1 70 m L hybridization mixture containing 75% deionized formamide (Sigma-Aldrich), 20 mM Tris (pH 7.1; Sigma-Aldrich), and 1% BSA (Sigma-Aldrich) with no probe (unstained) or 0.3 mg/mL telomere-specific FITC conjugated (C 3 TA 2 ) 3 peptide nucleic acid (PNA) (Applied Biosystems, Foster City, USA). Denaturation was done at 87°C for 15 min, and hybridization was performed in the dark and at room temperature (RT) for 90 min. Excess and nonspecifically bound telomere PNA probes were removed by 4 washing steps at RT using 1 mL washing solution containing 75% formamide, 10 mM Tris, 0.1% BSA, and 0.1% Tween 20 (Sigma-Aldrich), followed by 1 × 1 mL wash with a solution containing PBS, 0.1% BSA, and 0.1% Tween 20 at RT. DNA counterstaining was performed using a solution containing Sheath Fluid (BD Bioscience), 0.1% BSA, and a subsaturating amount of LDS 751 (0.01 mg/mL; Invitrogen, Waltham, MA, USA) overnight. Acquisition of telomere fluorescence was performed using FACSCalibur (BD Biosciences). For each sample, unstained and telomere-stained samples were tested. FlowJo version 10 (Tree Star Inc.) was used for analysis of telomere length in the specific cell subsets. Specific telomere fluorescence was determined as the difference between the fluorescence of the stained samples minus the (auto-) fluorescence of the corresponding unstained sample. Using calibration beads and an internal standard of cow thymocytes, the telomere fluorescence was calculated into kilobases of telomere length.

Intracellular cytokine measurements
Isolated CD8 + T cells were stimulated for 1 h at 37°C in 5% CO 2 with aCD3 (1 µg/mL, plate bound) and aCD28 (1 µg/ mL, soluble) antibodies or with aCD3 mAb-coated P815 cells (see below). Thereafter, GolgiPlug and GolgiStop (BD Biosciences) were added to the cultures followed by incubation for 5 h. Cells were spun down and incubated with fluorochrome-conjugated mAbs for multiparametric flow cytometric analysis, when required. Cells were then washed, fixed with 2% paraformaldehyde in PBS, permeabilized, and stained intracellularly with fluorochrome-conjugated mAbs against cytokines. Finally, cells were washed and analyzed on a BD FACSVerse (BD Biosciences). Data were analyzed with FlowJo 10.0.6 software (Tree Star Inc., Ashland OR, USA).

Redirected cytotoxicity assay
Cytolytic CD8 + T cell activity was evaluated in a redirected cytotoxicity assay against P815 cells. To this end, the P815 cells were coated with 20 mg/mL of aCD3 (OKT-3) for 1 h. When indicated, P815 cells were treated with neuraminidase (25 mU, Roche Diagnostics) for 30 min at 37°C. CD3-coated P815 cells were co-cultured (3:1 E/T ratio) with CD8 + T cells at 37°C. After 4 h of incubation, the specific lysis of P815 cells was assessed by measuring the LDH activity in the supernatant using the Cytotoxicity Detection Kit PLUS LDH (Roche), according to the manufacturer's instructions. Specific lysis was calculated as (experimentalspontaneous release)/(totalspontaneous release)*100 and expressed as a fold change between treated and untreated groups (specific lysis fold change).

TCRVb sequencing
CD8 + T cells were isolated from peripheral blood of healthy donors and separated by fluorescence-activated cell sorting into Siglec-9 + , Siglec-7 + and Siglec-9 -/7populations as previously described. Genomic DNA from CD8 + T cells subsets was extracted using NucleoSpin ® Tissue kit from Macherey-Nagel according to the manufacturer instructions. Genomic DNA quantity and purity were assessed through spectrophotometric analysis. 1.47 to 29.1 ng/µL of genomic DNA were analyzed by high-throughput sequencing of the TCRVb using the ImmunoSEQ immune profiling platform at the survey level (Adaptive Biotechnologies Corp, Seattle, WA), which represents a detection capacity of 1 cell in 40'000. Raw data can be retrieved from the immuneACCESS repository (DOI:10.21417/haas-2022-fi URL: https://clients.adaptivebiotech.com/pub/haas-2022-fi).

Flow cytometric quantification of Siglec ligands on AML cells
Detection of Siglec-7 ligands by flow cytometry was performed as previously described (6). AML-derived samples were analyzed as previously described (17). In brief, non-specific antibody binding by Fc receptors was blocked using 100 mL of Fc Receptor Blocker (Innovex Biosciences, Richmond, CA, USA) and dead cells were excluded from analysis by staining with a Fixable Viability Dye (ThermoFisher). For the Siglec ligands staining, recombinant human Siglec-7-hFc (R&D Systems, Minneapolis, MN, USA) was pre-incubated with PEconjugated goat anti-human Ig (Jackson ImmunoResearch Laboratories, West Grove, USA) for 1 h at 4°C and then applied to the samples for 1 h at RT together with lineageassociated antibodies. Lineage-positive cells were stained with biotinylated aCD2, aCD14, aCD16, aCD19, aCD56, and aCD235, together with fluorophore-conjugated aCD8, aCD4, aCD45, aCD34, aCD38 (all from BioLegend), followed by a second step with streptavidin-FITC conjugate (BD Biosciences). Cells were washed and analyzed on a BD FACSVerse or BD FACSlyric (BD Biosciences). Data were analyzed using the FlowJo 10.0.6 software (Tree Star Inc.).

Immune synapse analysis
Isolated CD8 + T cells subgroups were obtained by cell sorting as previously described. P815 cells were incubated with 20 mg/mL of aCD3 (OKT-3) for 1 h. When indicated, P815 cells were treated with neuraminidase (25 mU, Roche Diagnostics). CD3-coated P815 cells were co-cultured (3:1 E/T ratio) with CD8 + T cells subgroups for 30 min. After incubation, the cells were centrifuged on poly-lysine (Sigma)-treated coverslips, fixed using 3% paraformaldehyde for 20 min at 4°C and permeabilized with Triton X-100 for 1 min. After extensive washing with fish skin gelatin buffer (PSG), aSiglec-7 antibody and BODIPY 488 Phalloidin (actin dye, Life Technologies) were applied for 1 h at RT. After another round of washing, the secondary antibody (goat anti-mouse, Alexa-Fluor 555, Invitrogen) was applied for 1 h at RT. Coverslips were mounted on slides (Fisherbrand, Thermo Fisher) using ProLong Gold anti-fade reagent (Invitrogen). The mounted slides were cured for 2 d in the dark at RT. Long-time storage at 4°C. Conjugates were analyzed by confocal laser scanning microscopy (LSM510, Carl Zeiss, Jena, Germany). Acquired images were analyzed using the ImageJ software version 1.51 (NIH, Bethesda, MD, USA).

Analysis of bioenergetic profiles
CD8 + T cells subsets were isolated from healthy donors as previously described. T cells were either analyzed directly following sorting or were activated for 7 d using aCD3 and aCD28 (each at 1 µg/mL) as described above. Bioenergetic profiles were assesed using a seahorse approach (18). Briefly, to overcome machine detection limitations, sorted CD8 + T cells from 2 to 4 patients were pooled together for each condition. XF96 cell culture microplate (Agilent, Santa Clara, USA) was treated with 30 mL poly-D-lysine (Sigma-Aldrich) for 1-2 h, before washing with ddH 2 O. Sorted CD8 + T cells subsets were harvested, washed in non-buffered DMEM containing 25 mM glucose, 2 mM L-glutamine and 1 mM sodium pyruvate (Seahorse XF DMEM medium, Agilent). Cells were then resuspended in medium at a concentration of at least 5×10 6 cells/mL. 40 mL of cells were plated into the bottom of the analysis wells (=2x10 5 cells/well). Cells were centrifuged 5 min at 400xg to adhere and form a monolayer at the bottom of the plate. 140 mL of medium was added to each well and cells were incubated at 37°C in a non-CO 2 incubator for 60 min. 10x stocks of compounds (oligomycin, fluoro-carbonyl cyanide phenylhydrazone, rotenone, antimycin A and 2-deoxy-Dglucose; all purchased from Sigma-Aldrich) in medium were prepared and loaded into delivery ports of XFe96 sensor cartridges. Oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) were measured under basal conditions and in response to sequentially injected compounds at a final concentration of 1 mM oligomycin, 1.5 mM fluoro-carbonyl cyanide phenylhydrazone and 100 nM rotenone + 1 mM antimycin A and 50 mM of 2-deoxy-D-glucose using the XF-96 Extracellular Flux Analyzer (Agilent).

Statistics
Statistical analysis was performed using Prism 7.0 (GraphPad Software, San Diego, CA, USA). For quantitative comparisons between two groups the paired Student's t test and between multiple groups one-way ANOVA tests with Bonferroni or Dunn posttest were used. All statistical tests were two-sided and P < 0.05 was considered significant. Unless otherwise indicated, data represent mean ± standard deviation (SD).

Siglec-7 defines a distinct subset of effector memory CD8 + T cells
In line with earlier reports (11, 12), we observed a subset of Siglec-7 + CD8 + T cells in the peripheral blood of healthy individuals ( Figures 1A, B and Supplementary Figure 1A). Our flow cytometric analysis revealed that these cells represented a distinct and more frequent subtype compared to Siglec-9 + CD8 + T cells, and were predominantly negative for NK cell (CD56) and natural killer T cell (NKT, TCR Va24-Ja18) markers (Supplementary Figures 1B, C). Unmasking of potential sialoglycan ligands bound in cis by neuraminidase had no further effect on the flow cytometric assessment of Siglec-7 on CD8 + T cells (Supplementary Figure 2). Further phenotypic analysis based on CCR7 and CD45RA cell surface expression (19), indicated that Siglec-7 + CD8 + T cells predominantly constitute effector memory (EM), and to a lesser extent effector memory cells re-expressing CD45RA (EMRA), T cell subsets ( Figure 1C).
We went on to compare the clonotype repertoires of Siglec-7 + , Siglec-9 + and Siglec-7/9 -/subsets of peripheral blood T cells ( Figure 1F and Supplementary Figure 4). The Siglec-7 + T cell subset enclosed a higher proportion (2.7-10.6%) of the total of all clonotypes, as compared to the Siglec-9 + subset (0.9-2.8%) ( Figure 1F and Supplementary Figure 4), eventually in line with their higher occurrence in the circulation. The analysis of the TCRVb nucleotide chain distribution and clonotypes frequency in Siglec-7 + CD8 + T cells (x-axis) and Siglec-9 + CD8 + T cells (y-axis) from donor TS-02 confirmed the distinct clonotype profile of the Siglec-7 + subset ( Figure 1G). Taken together, these data suggest that Siglec-7 + CD8 + T cells, similarily to their Siglec-9 positive counterparts, are expanded oligoclonal effector memory T cells, but represent a distinct subset in light of the TCR repertoire.

High metabolic capacities of Siglec-7 + CD8 + T cells in steady state and upon activation
Metabolism plays a key role in immune cell functionality and activated effector T cells elevate aerobic glycolysis and oxidative phosphorylation (OXPHOS) (21, 22). Using Seahorse technology, we investigated the oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) in presence of oligomycin (complex V blocker), FCCP (mitochondrial uncoupler), 2-deoxy-D-glucose (2-DG, glycolysis inhibitor), or combined antimycin A (complex III blocker) and rotenone (complex I blocker) treatment (Figures 2A, B). OCR analysis of sorted CD8 + T cell subsets revealed significantly higher basal respiration (Figures 2C, D) and ATP-linked respiration ( Figure 2E) rates of Siglec-7 + CD8 + T cells at steady state. Compared to their Siglec-7 negative counterparts, Siglec-7 + CD8 + T cells also exhibited an overall amplified ECAR profile (Figure 2F), and a trend towards higher basal ECAR ( Figure 2G) and glycolysis ( Figure 2H). The increased OXPHOS capacity of Siglec-7 + CD8 + T cells at steady state matched the metabolic profile previously described for effector T cells (22)(23)(24), corresponding with the surface marker analysis.
Next, we compared the metabolic behavior of Siglec-7 + and Siglec-7 -CD8 + T cells upon activation by aCD3 and aCD28 mAbs co-stimulation for a duration of 7 days (25). In analogy to steady state conditions, upon activation Siglec-7 + CD8 + T cells displayed elevated OCR and ECAR profiles ( Figures 3A, B), significantly increased basal respiration (Figure 3C), and augmented ATP-linked respiration ( Figure 3D). Furthermore, upon activation the basal ECAR ( Figure 3E) and glycolytic capacity ( Figure 3F) of Siglec-7 + CD8 + T cells raised dramatically compared to Siglec-7 -CD8 + T cells at steady- state. Figure 3G highlights the higher basal respiration and glycolysis levels of Siglec-7 + CD8 + T cells compared to Siglec-7 -CD8 + T cells in steady state, and particularly upon activation. The heatmap in Figure 3H summarizes the key metabolic characteristics, illustrating the bioenergetic advantage of activated Siglec-7 + CD8 + T cells over Siglec-7cells, particularly in regard of ATP-linked respiration and spare respiratory capacity.
When redirected against aCD3-coated P815 cancer cells, Siglec-7 + CD8 + T cells demonstrated a higher cytotoxic capacity than their Siglec-7 negative counterparts ( Figure 4B), and costimulation with aCD3 and aCD28 mAbs resulted in stronger IFN-g and TNF-a production in Siglec-7 + CD8 + T cells ( Figures 4C, D). Flow cytometric analysis revealed broad surface expression of chemokine receptors on Siglec-7 + CD8 + T cells ( Figure 4E). Given the significant expression of CCR5 and CXCR3 on this subset, migration towards the chemokines RANTES (CCR5 ligand) and CXCL9 (CXCR3 ligand), was assessed. Indeed, Siglec-7 + CD8 + T cells demonstrated a higher migration capacity towards these chemokines (Figures 4F, G). Together, these data confirm a history of previous clonal expansion for Siglec-7 + CD8 + T cells and indicate that this subset of effector memory T cells is not exhausted but exhibits high functional and chemotactic capabilities.

Inhibition of Siglec-7 + CD8 + T cells by sialoglycans on tumor cells
The formation of an immune synapse (IS) involves the spatio-temporal organization of molecular events at the interface between effector and target cells. For IS formation analysis by confocal microscopy, sorted CD8 + T cell subsets were redirected to aCD3-coated P815 target cells, which express Siglec-7 surface ligands that can be removed by enzymatic digestion with neuraminidase (Supplementary Figure 5). We observed polarization of the Siglec-7 receptor into the IS, which was diminished upon neuraminidase treatment ( Figures 5A-E), indicating the requirement of sialic acid-dependent receptorligand interactions in trans for effective Siglec-7 polarization. Moreover, neuraminidase treatment of target cells further enhanced actin polarization, required for the establishment of a stable and functional IS (27), in synapses formed with Siglec-7 + CD8 + T cells but not with Siglec-7 -CD8 + T cells ( Figure 5F). Functional experiments revealed that the digestion of Siglec-7 ligands by neuraminidase treatment on aCD3-coated P815 target cells increased effector functions of Siglec-7 + , but not Siglec-7 -CD8 + T cells, including redirected cytotoxicity ( Figure 5G), as well as IFN-g and TNF-a ( Figures 5H, I) production. Together, these mechanistic studies provide functional evidence for the sialic acid-Siglec axis as an immune checkpoint that directly regulates effector functions of Siglec-7 + CD8 + T effector memory cells.

Siglec-7 + T cell glyco-immune checkpoints on AML and leukemic stem cells
Using flow cytometry, we went on to analyze the expression of Siglec-7 ligands on leukemic cells (Lin -CD90 -CD34 + CD38 + ) and leukemic stem cells (Lin -CD90 -CD34 + CD38 -) in AML patient-derived peripheral blood (PB) and bone marrow (BM) (17). High surface expression of Siglec-7 ligands was detected on both AML cells and leukemic stem cells in peripheral blood and bone marrow ( Figures 6A-C). An analysis of RNA-seq data from the AML data set (n=818) from The Cancer Genome Atlas (TCGA) project using a clustering algorithm revealed h e t e r o g e n o u s e x p r e s s i o n o f t h e t w e n t y h u m a n sialyltransferases ( Figure 6D), which are involved in the biosynthesis of sialoglycans. Consistently high expression levels were found for sialyltransferases (ST) predicted to be involved in the biosynthesis of Siglec-7 ligands, including ST3GAL1, ST3GAL4, ST6GAL1, and ST6GALNAC6 (27-31). A gene set enrichment analysis of the AML TCGA data revealed a strong correlation between Siglec-7 expression and hallmark gene sets linked to effector CD8 + T cell activity, such as IFN-g response, inflammatory response, glycolysis or IL-2-STAT5 signaling ( Figure 6E).
Next, we used multi-parametric flow cytometry to explore the expression of Siglec-7 on CD8 + T cells in peripheral blood (n=8) and bone marrow (n=5) from AML patients. We observed that the majority of CD8 + T cells in the bone marrow of AML patients expressed Siglec-7, while circulating Siglec-7 + CD8 + T cells in AML patients were found at similar levels as compared to healthy donors ( Figure 6F). Further analysis of Siglec-7 + CD8 + T cells isolated from the bone marrow of four AML patients revealed co-expression with CTLA4, and, to a lesser extent with other check-point receptors, such as PD1, LAG3, BTLA, TIM3 ( Figure 6G). These data suggest a potential role of the sialic acid-Siglec axis as an immune checkpoint in AML.

Discussion
Increased expression of multiple inhibitory receptors is commonly considered a hallmark of exhausted CD8 + T cells (32). However, in this study we observed that in humans Siglec-7 defines a non-exhausted effector memory CD8 + T cell subset characterized by high functional and metabolic capacities. For effective functionality, effector memory CD8 + T cells need to reprogram their metabolism, which also allows to overcome barriers imposed by challenging environments such as the tumor microenvironment (TME) (33). While exhausted T cells are known to progressively undergo metabolic dysfunction (32), Siglec-7 + CD8 + T cells were found to exhibit a high potential for concomitant glycolysis and oxidative phosphorylation upon activation, as assessed by ECAR and OCR measurements, respectively. Indeed, Siglec-7 + CD8 + T cells demonstrated superior functionality in terms of cytotoxicity, cytokine production, and migratory potential compared to Siglec-7 negative cells.
Rather than exhaustion, Siglec-7 expression on CD8 + T cells was linked to clonality. Indeed, Siglec-7 + CD8 + T cells exhibit short telomere length and high TCRvb chain clonality, which together is indicative of a history extensive of previous clonal expansion. The clonotype repertoire of Siglec-7 + CD8 + T cells was distinct and showed higher clonality compared to other CD8 + T cell subsets, including Siglec-9 positive oligoclonal counterparts found at lower frequency in peripheral blood.
Notably, it has been reported that pre-treatment clonality is predictive of response to anti-PD1 treatment, while TCR diversity in tumor-infiltrating lymphocytes (TILs) is prognostic for overall survival in absence of immune checkpoint therapy (34). In line with this observation, results from our study support the conceptual perspective that the expression of at least certain inhibitory receptors is not a defining phenotype of exhausted T cells but is associated with clonality, as a consequence of previous T cell expansion. Furthermore, our data suggest that in combination with T cell repertoire analysis (35), the exploration of clonality-associated immune checkpoints may provide novel avenues for personalized immunotherapy. Recent advances in immune checkpoint therapy highlight the importance of CD8 + T cells in anti-tumor responses and the need for "immune normalization" to restore tumor-induced immune deficiency (34). Current immune checkpoint therapy is successfully used in patient subsets of select solid tumors and lymphomas, but ineffective in other malignancies such as AML in which epigenetic silencing of activating immune checkpoint receptors rather than inhibitory signaling might lead to T cell dysfunction (36). However, in this study we observed high expression of Siglec-7 ligands on leukemic cells and leukemic stem cells in peripheral blood and bone marrow from AML patients. Intriguingly, the majority of CD8 + T cells in the bone marrow of AML patients expressed Siglec-7, with high coexpression of CTLA4, but lower expression of other inhibitory receptors (PD1, LAG3, BTLA, TIM3). These findings suggest that the sialic acid-Siglec axis provides a glyco-immune checkpoint in AML that restrains effective anti-tumor responses of CD8+ T cells in the bone marrow environment. Indeed, in mechanistic experiments, we observed Siglec-7 repolarization on CD8+ T cells into the immune synapse with target cells expressing the cognate ligand, as well as sialic-acid dependent suppression of cytotoxicity and cytokine production selectively of Siglec-7 + CD8+ T cells. There is increasing awareness that reverse translational research from bedside to bench is needed for more personalized pharmacotherapy and to explore the complexity of processes at play in human diseases (37). In this study, we identified Siglec-7 as an immune checkpoint receptor on nonexhausted effector memory CD8+ T cells that is acquired upon clonal expansion. Strategies considering the combined analysis of T cell repertoires and clonality-associated immune checkpoint receptors, such as Siglec-7, may lead to novel and more personalized treatment approaches for T cell-driven autoimmune disorders and for cancer immunotherapy.

Ethics statement
The studies involving human participants were reviewed and approved by the ethics committee of the canton of Bern, Switzerland. The patients/participants provided their written informed consent to participate in this study.

Author contributions
SG designed the study. QH and SG wrote the manuscript. TCGA data were analyzed by AB, CN and QH. Experimental work was performed by QH, NM, LM, MH, and VR under supervision by SG, H-US, GB, CR and CM. Patient material was provided by CR and AO. All authors had full access to the data, helped draft the report or critically revised the draft, contributed to data interpretation, reviewed and approved the final version of the report.