Biology subjects

van Kooyk, Y.

Publications and source records attributed to van Kooyk, Y..

9 recordsLinked to original sources

bioRxiv2026

CD44-CD206 axis drives dendritic cell loss and immunosuppression in immaturely glycosylated bladder tumours

Antigen-presenting-cell dysfunction drives immune exclusion, but how tumour glycans disable these cells remains incompletely defined. Immature O-glycosylation, marked by Tn and sialyl-Tn antigens, drives myeloid dysfunction in bladder cancer. Transcriptomics and human tumour profiling linked this state to reduced representation of antigen-presenting myeloid cells and attenuated lymphoid-effector programmes. In glycoengineered models, immature O-glycans promoted immunoregulatory macrophage phenotypes and contact-dependent death of monocyte-derived dendritic cells (moDCs), while surviving cells showed impaired maturation and T-cell activation. Tumour-cell CD44 standard isoform was required for DC death, which was accompanied by inflammasome-associated proteins and gasdermin D cleavage, consistent with pyroptosis. Receptor-discovery approaches converged on CD206, which bound immaturely glycosylated CD44. CD206 blockade restored DC viability. In immunocompetent mice, immature glycosylation accelerated tumour growth and depleted conventional DCs, whereas CD206 blockade restrained tumour progression and restored local and nodal myeloid and lymphoid immunity. These findings identify CD44-CD206 as a targetable glycoimmune checkpoint that promotes immune exclusion.

immunology↗

bioRxiv2026

SIGLEC1 FACILITATES MACROPHAGE-CD8+ T CELL INTERACTIONS AND CORRELATES WITH CANCER IMMUNOTHERAPY RESPONSE

Antigen-presenting cell (APC) interactions with cytotoxic T cells are critical for anti-tumour immunity and response to immune checkpoint blockade (ICB), yet context-specific regulators in the tumour microenvironment remain not fully defined. Here we identify the lectin receptor SIGLEC1 as a key mediator of macrophage-T cell interactions in human melanoma. In a well-characterized patient cohort, SIGLEC1 was selectively upregulated in inflammatory macrophages physically associated with activated/exhausted CD8 T cells. Imaging and functional analyses revealed that SIGLEC1 accumulates at the macrophage-T cell interface and promotes cell clustering. SIGLEC1 ligands were enriched on activated T cells, and their blockade reduced cytotoxic cytokine production ex vivo. Single-cell (spatial) transcriptomics across independent ICB-treated melanoma cohorts showed that SIGLEC1 macrophages localize near CD8 T cells and are enriched in responders, where they also associate with T cells expressing activation/exhaustion markers. These findings define a SIGLEC1-dependent macrophage-T cell niche linked to effective immunotherapy.

immunology↗

bioRxiv2026

Reducing sialylation in melanoma increases classical pathway-mediated complement activation

Based on the success in pre-clinical models, methods that reduce sialylation in tumors have progressed to clinical trials, as this improves anti-tumor cellular responses. Immune responses against cancer can also be mediated by soluble, non-cellular mechanisms, such as the complement system. Dysregulation of the complement cascade and hypersialylation are hallmarks found across tumor types. Sialic acids are known to interact with complement proteins. However, the downstream pathways involved in the regulation of the complement cascade when reducing sialylation in tumors remain unclear. Here, using human melanoma cell lines and patient samples, we show that metabolic or enzymatic targeting of sialylation directly increases the activation of the complement, enhancing C3 opsonization of tumor cells and the formation of the membrane attack complex. This is mediated by the classical pathway of the complement system, in line with increased binding of immunoglobulins to tumor cells when sialylation is impaired. Our work positions the complement cascade as a relevant anti-tumor response playing a role when sialylation is targeted for cancer treatment. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/723302v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1480999org.highwire.dtl.DTLVardef@6e3c44org.highwire.dtl.DTLVardef@1369dd0org.highwire.dtl.DTLVardef@b2c455_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2026

CMAS dampens anti-tumor immunity and associates with response to neoadjuvant immunotherapy in melanoma

Identifying immune-regulatory pathways to predict response is crucial for the efficacy of immune checkpoint blockade (ICB) immunotherapies. Sialylation is upregulated in tumor cells and modulates immune responses in cancer, yet its impact on patient clinical outcome and the spatial organization of the tumor microenvironment remain unclear. Here, using publicly available single-cell RNA sequencing data we show that expression of the sialylation master regulator CMAS in melanoma cells correlates with poorer patient survival. Using a murine melanoma model, we demonstrate that Cmas deletion in tumor cells severely impaired tumor growth and improved anti-tumor lymphoid and myeloid cell responses, increasing tumor cell-intrinsic susceptibility to interferon-gamma-, CD4+ T cell-, and macrophage-mediated killing. Single-cell spatial transcriptomics on neoadjuvant ICB-treated melanoma patient tumor biopsies revealed that CMAS expression in tumor cells inversely correlated with tumor cell proximity to and activation status of T cells and macrophages. Furthermore, expression of CMAS in tumor cells was increased in patients who did not respond to immunotherapy, compared to responders. Overall, our work identifies CMAS as a key modulator of tumor-immune dynamics associated with survival and response to neoadjuvant ICB immunotherapy in melanoma patients.

cancer biology↗

bioRxiv2025

Identification of allo- or orthosteric VHH/single-domain antibodies that enhance or block pathogen binding to Siglec-1 on dendritic cells

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=87 SRC="FIGDIR/small/695420v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@e85819org.highwire.dtl.DTLVardef@1eff6b4org.highwire.dtl.DTLVardef@12daa92org.highwire.dtl.DTLVardef@11959e5_HPS_FORMAT_FIGEXP M_FIG C_FIG BackgroundSiglec-1 (Sialoadhesin/CD169) is expressed on myeloid cells and plays a key role in host defences by capturing incoming sialylated-pathogens such as Campylobacter jejuni. However, binding to Siglec-1 has also been exploited by pathogens such as SARS-CoV-2 for further dissemination. ResultsHere we identified high-affinity VHHs also known as single-domain antibodies or Nanobodies that bind to Siglec-1 and allo- or orthosterically modulate ligand binding. VHH 2C2 was shown to bind directly to the ligand binding site of Siglec-1 and blocked binding of ganglioside liposomes and Campylobacter jejuni to monocyte-derived dendritic cells (moDCs) and ex vivo Siglec-1+ DCs. VHH 2C2 also blocked SARS-CoV-2 binding of moDCs. In contrast, the VHHs 1B5 and 1C1 interacted with Siglec-1 outside the ligand binding site and acted as positive allosteric modulators of Siglec-1 ligand interactions, as was illustrated by increased ganglioside liposome and Campylobacter jejuni binding by moDCs. Our data suggests that mechanistically, the VHH 1B5 and 1C1 interfere with the cis-binding sialic acids present on the Siglec-1-expressing cell and thereby enhance trans-interactions with ligands. ConclusionIn conclusion, we have isolated VHH that enhance or block Siglec-1 ligand binding to a variety of sialylated-pathogens enabling further interrogation of Siglec-1 function. Moreover, unlike conventional blocking antibodies targeting specific pathogens, Siglec-1 binding VHH could potentially serve as broad-spectrum pathogen blocking agents.

immunology↗

bioRxiv2022

The transcriptional landscape of glycosylation-related genes in cancer

Changes in glycosylation patterns have been associated with malignant transformation and clinical outcome in several types of cancer, although no comprehensive analysis has been performed in a pan-cancer setting. Here, we performed an extensive transcriptomic analysis of glycosylation related genes (such as enzymes involved in synthesis and degradation of glycoconjugates, transporters, mucins and galectins), using publicly available bulk and single cell transcriptomic data sets from tumor samples and cancer cell lines. We identified genes and pathways associated with different tumor types, which may represent novel diagnostic biomarkers as 2-3 sialylation for Melanoma, MUC21 for Lung adenocarcinoma and Galectin-7 for Squamous cell carcinomas (SCC). Accordingly, serum levels of Galectin-7 in patients with lung cancer were elevated in SCC respect to adenocarcinomas, supporting its biomarker potential. Moreover, we characterized the contribution of different cell types to the overall glycosylation profiles observed by performing the integration and analysis of 14 single cell RNA-seq datasets. This led us to identify that cancer cells are responsible for the specific tumor glyco-codes identified in bulk transcriptomics, while stromal and immune cells contribute in a conserved manner across various malignancies. Furthermore, our results suggest that the glycosylation-related genes and pathways expressed by cancer cells are influenced by the cell of origin and the oncogenic pathways that led to malignant transformation. Lastly, we described the association of different glycosylation-related genes and pathways with the clinical outcome of patients. Interestingly, while the expression of genes associated to some pathways (as proteoglycan biosynthesis) are consistently associated with a more aggressive disease, the correlation of others pathways with the survival of patients depends on the particular tumor type. Remarkably, the expression of genes associated with the synthesis of CMP-sialic acid was correlated with lower survival of patients in Uveal Melanoma and PDAC, while the opposite was observed for colorectal cancer. The extensive transcriptomic analysis of glycosylation pathways in cancer that we report here can serve as a resource for future research aimed to unravel the glyco-code in cancer related to clinical outcome or biomarker development.

cancer biology↗

bioRxiv2022

Human Milk Oligosaccharide 2'-fucosyllactose inhibits ligand binding to C-type lectin DC-SIGN but not to Langerin

Human milk oligosaccharides (HMOs) and its most abundant component, 2-Fucosyllactose (2-FL), are known to be immunomodulatory. Previously, it was shown that HMOs and 2-FL bind to the C-type lectin receptor DC-SIGN. Here we show, using a ligand-receptor competition assay, that a whole mixture of HMOs from pooled human milk (HMOS) and 2-FL inhibit the binding of the carbohydrate-binding receptor DC-SIGN to its prototypical ligands, fucose and the oligosaccharide Lewis-B, (Leb) in a dose-dependent way. Interestingly, such inhibition by HMOS and 2-FL was not detected for another C-type lectin, Langerin, evolutionary similar to DC-SIGN. The cell-ligand competition assay using DC-SIGN expressing cells confirmed that 2-FL inhibits the binding of DC-SIGN to Leb. Molecular dynamics (MD) simulations show that 2-FL exists in a preorganized bioactive conformation before binding to DC-SIGN and this conformation is retained after binding to DC-SIGN. Leb has more flexible conformations and utilizes two binding modes, which operate one at a time via its two fucoses to bind to DC-SIGN. 2-FL may have a reduced entropic penalty due to its preorganized state compared to Leb, and it has lower binding enthalpy, suggesting better binding to DC-SIGN. Thus, due to the better binding to DC-SIGN, 2-FL may replace Leb from its binding pocket in DC-SIGN. MD simulations also showed that 2-FL does not bind to Langerin. Our studies confirm 2-FL as a specific ligand for DC-SIGN and suggest that 2-FL can replace other DC-SIGN ligands from its binding pocket during ligand-receptor interactions in possible immunomodulatory processes.

biochemistry↗

bioRxiv2020

Novel ACE2-Independent Carbohydrate-Binding of SARS-CoV-2 Spike Protein to Host Lectins and Lung Microbiota

The immediate call for translational research in the field of coronavirus disease (COVID-19) pandemic, needs new and unexplored angles to support and contribute to this important worldwide health problem. The aim of this study is to better understand the pathogenic mechanisms underlying COVID-19, deciphering the carbohydrate-mediated interactions of the SARS-CoV-2 spike protein. We studied the carbohydrate-binding receptors that could be important for viral entry and for immune-modulatory responses, and we studied the interactions of the spike protein with the host lung microbiota. Exploring solid-phase immunoassays, we evaluated the interactions between the SARS-CoV-2 spike protein and a library of 12 different human carbohydrate-binding proteins (C-type lectins and Siglecs) involved in binding, triggering and modulation of innate and adaptive immune-responses. We revealed a specific binding of the SARS-CoV-2 spike protein to the receptors DC-SIGN, MGL, Siglec-9 and Siglec-10 that are all expressed on myeloid immune cells. In addition, because the lung microbiota can promote or modulate viral infection, we studied the interactions between the SARS-CoV-2 spike protein and a library of Streptococcus pneumoniae capsular polysaccharides, as well as other bacterial glyco-conjugates. We show specific binding of the spike protein to different S. pneumoniae capsular polysaccharides (serotypes 19F and 23F but not to serotype 14). Moreover we demonstrated a specific binding of SARS-CoV-2 spike protein to the lipopolysaccharide from the opportunistic human pathogen Pseudomonas aeruginosa, one of the leading cause of acute nosocomial infections and pneumonia. Interestingly, we identified rhamnosylated epitopes as one of the discriminating structures in lung microbiota to bind SARS-CoV-2 spike protein. In conclusion, we revealed novel ACE2-independent carbohydrate-mediated interactions with immune modulating lectins expressed on myeloid cells, as well as host lung microbiota glyco-conjugates. Our results identified new molecular pathways using host lectins and signalling, that may contribute to viral infection and subsequent immune exacerbation. Moreover we identified specific rhamnosylated epitopes in lung microbiota to bind SARS-CoV-2, providing a hypothetical link between the presence of specific lung microbiota and SARS-CoV-2 infection and severity.

immunology↗

bioRxiv2019

Comparison of intradermal injection and epicutaneous laser microporation for anti-tumor vaccine delivery in a human skin explant model

Human skin is a prime vaccination site containing multiple antigen presenting cells (APC), including Langerhans cells (LC) and dendritic cells (DC). APC deliver antigens to lymph nodes for induction of adaptive immunity through stimulating antigen specific T- and B-cells. Since intradermal (ID) injections require specific training, easy applicable delivery systems like laser microporation are emerging. In mice, combination of laser treatment and allergen injection showed enhanced T-cell responses and skewing of B-cell responses without adjuvants. However, it remains to be elucidated whether laser microporation can alter human skin DC phenotype and function without adjuvants. In an ex-vivo human skin explant model, we compared ID injection and laser microporation as anti-tumor vaccination strategy. A melanoma specific synthetic long peptide and multivalent dendrimer with gp100 antigen were used as vaccine formulation to measure APC phenotype, emigration and ability to stimulate gp100 specific CD8+ T-cells. We show that skin APC phenotype and emigration capacity was similar after laser microporation and ID injection. However, laser microporation reduced vaccine uptake by APC, resulting in decreased induction of gp100 specific CD8+ T-cell activation. To conclude, in our human skin model ID injection remains the most potent strategy to deliver antigens to skin APC for T-cell induction. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/861930v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@5b7191org.highwire.dtl.DTLVardef@17d16fcorg.highwire.dtl.DTLVardef@1701e08org.highwire.dtl.DTLVardef@1c3ab3d_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗