Biology subjects

Krogsgaard, M.

Publications and source records attributed to Krogsgaard, M..

6 recordsLinked to original sources

bioRxiv2026

Autoantibodies Drive Fc Gamma Receptor-Dependent Colon Inflammation During Immune Checkpoint Blockade

Immune checkpoint inhibitor (ICI)-associated colitis limits effective cancer immunotherapy, yet host determinants of severe toxicity remain undefined. We investigated whether humoral immunity is associated with subsequent severe immune-related colitis (irC). In melanoma patients, baseline serum autoantibody (AAb) profiling identified a composite antigen signature - a signature-level association rather than validated functional specificities - associated with severe irC, marked by retained reactivity to tumor-associated antigens and relative depletion of antibodies recognizing immune- and mucosal-regulatory proteins. To assess functional relevance, we transferred polyclonal IgG from severe- or non-severe-irC patients into wild-type or humanized Fc{gamma} receptor (hFc{gamma}R) mice treated with anti-PD-1 or anti-CTLA-4. IgG alone did not induce inflammation; however, severe-irC IgG amplified checkpoint-driven colonic inflammation in hFc{gamma}R mice, but not in wild-type mice, with checkpoint-specific remodeling of myeloid, lymphoid, and innate lymphoid compartments. These findings suggest that pretreatment humoral immunity conditions susceptibility to irC via the IgG-Fc{gamma}R axis.

cancer biology↗

bioRxiv2025

Persistent Classical and Atypical Memory B Cells Underlie Heterogeneous Vaccine Responses in Ocrelizumab-Treated Multiple Sclerosis

Background and ObjectivesPatients with multiple sclerosis (pwMS) treated with ocrelizumab (OCR), a B-cell-depleting therapy, exhibit heterogeneous humoral responses to SARS-CoV-2 mRNA vaccination. The mechanisms underlying this variability remain incompletely understood. We performed a longitudinal analysis of B-cell subset dynamics and antigen-specific T cell responses in OCR-treated pwMS and healthy controls to determine how immune cell composition, timing of OCR infusion, and lymphocyte dynamics influence humoral response outcomes. MethodsBased on post-vaccination anti-Spike IgG titers measured by multiplex bead immunoassay, pwMS were categorized as super-responders (SR), responders (R), or non-responders (NR). A 35-marker spectral flow cytometry panel was used to characterize T- and B-cell subsets longitudinally, at baseline and following stimulation with a SARS-CoV-2 peptide pool. ResultsCD4+ and CD8+ T cell populations were preserved across OCR-treated pwMS, and SARS-CoV-2-specific T cells remained detectable for more than 6 months after vaccination. In contrast, residual B-cell subset composition distinguished responders from non-responders. DN2-like B cells (CD19+CD27-IgD-T-bet+CD11c+CXCR5-) persisted despite repeated OCR infusions and were enriched in SR compared with NR. Repletion of mature naive B cells in peripheral blood correlated with time since last OCR infusion and with stronger humoral immune responses. ConclusionsB-cell subsets that resist OCR-mediated depletion may contribute to vaccine responsiveness in OCR-treated pwMS. Altered repletion kinetics of naive B cell subsets in non-responders suggest that specific B-cell populations may serve as predictive biomarkers of vaccine-induced humoral immunity, despite preserved T-cell responses.

immunology↗

bioRxiv2025

FGL-1 binding to LAG-3 inhibits T cell activation via disruption of CD28 and TCR signaling

Lymphocyte-activation gene 3 (LAG-3) is known to suppress T cell receptor (TCR) signaling by disrupting CD4/CD8 coreceptor and Lck association in the absence of ligand binding. However, the impact of Fibrinogen-like protein 1 (FGL-1) binding in modulating LAG-3 mediated inhibition and its specific impact on CD28 costimulatory signaling remains unclear. This study investigates the role of LAG-3/FGL-1 interaction in modulating T cell activation. Using phosphoproteomics and confocal microscopy in LAG-3+ Jurkat cells, we demonstrated that LAG-3/FGL-1 interaction suppresses T cell activation by disrupting CD28-mediated recruitment of Lck, impairing its colocalization with CD28. Importantly, this inhibition occurs independently of CD4-bound Lck, indicating that LAG-3 ligand engagement targets both free and membrane-associated Lck pools. Consequently, this leads to suppressed phosphorylation of CD28 and TCR/CD3 signaling components, broadly attenuating downstream tyrosine phosphorylation and T cell effector functions. Our findings identify the CD28-Lck axis as a critical target of LAG-3/FGL-1 inhibitory pathway and provide a rationale for therapeutic strategies that reinvigorate CD28-Lck signaling to enhance anti-tumor immunity.

immunology↗

bioRxiv2025

A pan-cancer atlas of T cell targets

T-cell-based immunotherapies have revolutionized cancer treatment, yet only a minority of patients are eligible for these approaches, significantly constrained by the limited knowledge of tumor-specific antigens. Here we present ImmunoVerse, a comprehensive map of T cell targets across 21 cancer types, revealing actionable tumor-specific targets in 89% of tumors analyzed. To define the repertoire of actionable T cell targets, we conducted an exhaustive pan-cancer analysis, integrating data from 7,188 RNA-Seq, 1,771 immunopeptidomes from 512 biological samples and 208 single-cell cancer datasets using novel AI methods, and compared these against 17,384 normal samples covering 51 tissues. Our analysis uncovered 62 viable surface protein targets and 28,446 tumor-specific HLA-presented antigens, deriving from 11 distinct molecular events, across 21 tumor types. Among these, we identified 5,928 previously uncharacterized neoantigens, new tumor self-antigens, peptides derived from tumor-specific cryptic ORFs, tumor-associated microbial targets and a novel splicing-derived PMEL peptide (sPMEL) with enhanced abundance and safety compared to the canonical clinical targets. We successfully expanded sPMEL-specific T cells, validating the therapeutic potential of these targets in functional assays. We highlight 153 promising new tumor targets and experimentally validate 19 targets representing six antigen classes. In addition to being the most comprehensive atlas of targets in scope, ImmunoVerse offers the most extensively annotated resource with key parameters for target selection, providing critical insights for therapeutic prioritization and clinical translation. To catalyze therapeutic development, we released our pan-cancer target atlas through an interactive web portal (https://www.immuno-verse.com) and made the accompanying toolkits available to the scientific community. This work redefines the landscape of therapeutic T cell targets and provides a foundational resource to unlock immunotherapy development across multiple cancers previously considered intractable.

cancer biology↗

bioRxiv2022

Cooperative ectodomain interaction among TCRαβ, CD3γε, and CD3δε enhances TCR mechanotransduction

TCR signaling poses a mechanical problem: pMHC binding occurs at the TCR{beta} ectodomain (ECD) head, whereas ITAM phosphorylation occurs on CD3 cytoplasmic tails. Chemistry cannot bridge this >10 nm gap, requiring the two events to be coupled through the TCR-CD3 interface, thus involving conformational allostery and being regulatable by force. Although weak ECD cis-interactions between TCR{beta} and CD3 have been proposed to contribute to this coupling, their kinetics and mechanical competence remain elusive. Here, we quantify TCR{beta}-CD3 ECD cis-interactions in a pseudo-cis configuration using two-dimensional binding and single-bond force spectroscopy, finding that TCR{beta}-CD3{gamma}{varepsilon} and TCR{beta}-CD3{delta}{varepsilon} interactions have low affinity and rapid kinetics, yet form catch bonds. Critically, concurrent engagement of CD3{gamma}{varepsilon} and CD3{delta}{varepsilon} produces high cis-cooperativity, yielding a stronger and longer-lasting CD3{gamma}{varepsilon}-TCR{beta}-CD3{delta}{varepsilon} trimolecular catch bond than the sum of the two dimeric bonds, with force-stabilized lifetimes matching those of agonist TCR-pMHC trans-interaction. Molecular dynamics simulations reveal an expanded, cooperative, and asymmetric contact network, making CD3{delta}{varepsilon} more force-responsive and susceptible to conformational change than CD3{gamma}{varepsilon}. Interface mutations do not alter force-free affinities but remodel cooperative cis-bond profiles, leading to an inverse correlation with trans-bond profiles and T cell signaling. These results identify cooperative ECD cis-interaction as a mechanically regulatable allosteric coupling element at the TCR-CD3 junction important to antigen recognition and signal initiation.

immunology↗

bioRxiv2022

In situ cell-surface conformation of the TCR-CD3 signaling complex

T cells play a vital role in adaptive immune responses to infections, inflammation and cancer and are dysregulated in autoimmunity. Antigen recognition by T cells - a key step in adaptive immune responses - is performed by the T cell receptor (TCR)-CD3 complex. The extracellular molecular organization of the individual CD3 subunits (CD3{delta}{varepsilon} and CD3 {gamma}{varepsilon}) around the {beta}TCR is critical for T cell signaling. Here, we incorporated unnatural amino acid (UAA) photo-crosslinkers at specific mouse TCR, TCR{beta}, CD3{delta} and CD3{gamma} sites, based on previous mutagenesis, NMR spectroscopy and cryo-EM evidence, and crosslinking allowing us to identify nearby interacting CD3 or TCR subunits on the mammalian cell surface. Using this approach, we show that CD3{gamma} and CD3{varepsilon}, belonging to CD3{gamma}{varepsilon} heterodimer crosslinks to C{beta} FG loop and C{beta} G strand, respectively and CD3{delta} crosslinks to C{beta} CC loop and C DE loop. Together with computational docking, we identify that in in situ cell-surface conformation, the CD3 subunits exists in CD3{varepsilon}-CD3{gamma}-CD3{varepsilon}-CD3{delta} arrangement around the {beta} TCR. This unconventional technique, which uses the native mammalian cell surface microenvironment, includes the plasma membrane and excludes random, artificial crosslinks, captures a dynamic, biologically relevant, cell-surface conformation of the TCR-CD3 complex, which is compatible with the reported static cryo-EM structures overall CD3 subunits arrangement, but with key differences at the TCR-CD3 interface, which may be critical for experiments in T cell model systems.

immunology↗