Biology subjects

Krohn, S.

Publications and source records attributed to Krohn, S..

14 recordsLinked to original sources

bioRxiv2026

A Novel Natural Killer Cell Expansion Technology for the Development of Cellular Immunotherapies

Adoptive cell therapy based on Natural Killer (NK) cells holds great promise for the treatment of cancer. For all approaches aiming at utilizing NK cells in immunotherapy, efficient ex vivo expansion technologies for the generation on of cytotoxic NK cells are a prerequisite for clinical translation. In this study, a novel multifunctional fusion protein consisting of a CD20-directed Fab-fragment, an agonistic anti-4-1BB single-chain Fragment variable (scFv), the Sushi domain of the interleukin (IL)-15 receptor and human IL-15 was generated. This molecule triggered strong NK cell expansion when bound to co-cultivated autologous B cells, due to trans-presentation of IL-15 and binding to 4-1BB/CD137. Expansion rates of up to 7,500-fold were achieved and the NK cells showed high cytotoxic capacity against a panel of tumor cell lines representing various tumor entities. Importantly, the activated NK cells did not show cytolytic activity against non-malignant B cells indicating that NK cells amplified by our novel approach were still physiologically regulated. The cytotoxic activity of the expanded NK cells was further enhanced by combination with therapeutic antibodies. Our molecule was additionally able to trigger efficient proliferation of NK cells from cord blood as well as multiple myeloma (MM) and acute myeloid leukemia (AML) patients. In conclusion, our novel platform technology provides ex vivo expansion of NK cells by using a single multifunctional fusion protein and may be well-suited for the development of NK cell-based immunotherapies. Key pointsA novel fusion protein that enables NK cell expansion from different sources including peripheral blood, bone marrow and cord blood

immunology↗

bioRxiv2025

A novel Fc-optimized antibody drug conjugate targeting CD7 for the therapy of T-cell acute lymphoblastic leukemia

While treatment for patients with T-cell acute lymphoblastic leukemia (T-ALL) has improved in the last decades, therapeutic options for patients refractory to standard therapy or with relapsing disease are limited. In particular, no immunotherapy option has been approved in T-ALL yet. Here, a novel dual antibody engineering approach for targeting CD7 was evaluated. The chimeric CD7 antibody chimTH69 was modified by Fc engineering to improve antibody-dependent cell-mediated cytotoxicity (ADCC) and antibody-dependent cellular phagocytosis (ADCP). In addition, it was conjugated to monomethyl auristatin E (MMAE), a microtubule-disrupting agent. The resulting Fc-optimized antibody-drug conjugate (ADC), designated chimTH69-DE-vcMMAE, showed a unique set of effector functions in vitro. It triggered ADCC by mononuclear cells at picomolar concentrations, mediated ADCP by macrophages and directly inhibited the growth of a panel of T-ALL cell lines by delivering the cytotoxic compound to induce G2 cell cycle arrest and apoptosis. In addition, due to its specific linker design, chimTH69-DE-vcMMAE demonstrated bystander killing activity against CD7-negative leukemia cells. In mice, CD7-directed therapy with chimTH69-DE-vcMMAE inhibited the growth of subcutaneous CCRF-CEM T-ALL xenografts. Moreover, chimTH69-DE-vcMMAE exerted strong antileukemic effects in a phase II-like patient-derived xenograft preclinical trial in pediatric and adult patients when applied in an experimental overt leukemia setting. ChimTH69-DE-vcMMAE induced minimal residual disease-negativity in one PDX model. These findings indicate that targeting CD7 with the novel Fc-optimized ADC is a potent strategy to trigger anti-leukemia responses and may open a novel therapeutic avenue for T-ALL treatment. Key PointA novel antibody drug conjugate targeting CD7 showed efficient anti-leukemia activity in preclinical models of T-ALL.

cancer biology↗

bioRxiv2025

Memory dysfunction and psychiatric outcomes in anti-NMDA receptor encephalitis are linked to altered structural brain complexity

IntroductionMost patients with anti-N-methyl-D-aspartate receptor encephalitis (NMDARE) experience long-term neuropsychiatric sequelae despite immunotherapy. However, how these residual symptoms relate to structural brain changes in the post-acute phase remains unclear. Recently, fractal dimensionality (FD) has emerged as a sensitive imaging marker of structural brain complexity in related conditions but has not been explored in autoimmune encephalitis. MethodsThis cross-sectional study combined clinical, cognitive, and neuroimaging analyses in 70 patients with post-acute NMDARE (median time from onset: 22 months), and 70 healthy controls matched for age (t=-0.57, p=0.57) and sex ({chi}2=0, p=1). High-resolution T1-weighted magnetic resonance imaging (MRI) data were analyzed with FreeSurfer and computational fractal analysis. Clinical outcomes were assessed with the modified Rankin Scale (mRS) and Clinical Assessment Scale in Autoimmune Encephalitis (CASE). Psychiatric manifestations underwent phenotypical analyses, and memory performance was assessed with standardized neuropsychological tests. ResultsPatients with NMDARE were severely affected at peak illness but showed substantial overall improvement in the post-acute stage (median mRS at peak=5, post-acute=1, z=-7.2, p<0.001; median CASE at peak=11, post-acute=1, z=-7.2, p<0.001). However, 67% of patients showed residual CASE symptoms, with memory dysfunction (61%) and psychiatric symptoms (36%) representing the most prevalent domains. Therein, psychiatric symptoms showed a phenotypical shift from a schizophrenia-like phenotype at peak illness to an affective phenotype in the post-acute stage. Neuroimaging uncovered a characteristic pattern of reduced structural brain complexity, including the hippocampus bilaterally and a fronto-cingulo-temporal cluster in cortical gray matter and cerebral white matter. Importantly, normative modeling revealed that patients with residual symptoms showed stronger alterations of brain complexity than those without (psychiatric: t=-2.65, p=0.010; memory: t=-3.98, p<0.001; both vs. no symptoms: t=-5.46, p<0.001). Similarly, patients with stronger alterations of brain complexity showed lower scores of visuospatial and verbal memory (all pFDR<0.015). DiscussionPost-acute NMDARE is characterized by systematic reductions in structural brain complexity, consistently involving previously implicated regions while identifying changes in the cingulate cortex as a new morphological correlate. These changes are linked to residual psychiatric symptoms and memory dysfunction, highlighting FD as a promising new imaging marker of long-term outcomes. Our findings suggest that current treatment strategies may be insufficient to fully address the residual symptom burden after the acute phase of NMDARE.

neuroscience↗

bioRxiv2025

CD19xCD3 bispecific T cell engager treatment induces remission in experimental pemphigoid disease

Pemphigoid diseases (PDs) are autoimmune disorders marked by autoantibodies (Aab) against skin and mucous membrane proteins, causing muco-cutaneous blistering in predominantly elderly patients. Since current therapeutics are often insufficient, PDs impose a significant morbidity and mortality burden. CD19xCD3 bispecific T cell engagers (TCEs) - originally developed for B cell malignancies - have shown promise in treatment-refractory autoimmune diseases like systemic sclerosis and rheumatoid arthritis. To explore their potential in PDs, we tested a murine CD19xCD3 TCE in a mouse model of epidermolysis bullosa acquisita (EBA), a prototypical PD. The TCE selectively depleted B cells in blood and bone marrow, but not spleen, of healthy mice. Mice with clinically manifest immunization-induced EBA were randomized to receive either the CD19xCD3 TCE or control treatment upon reaching a predefined disease severity. After 13 weeks, 45% of TCE-treated mice achieved remission, versus 23% of controls. This improvement correlated with reduced antigen-specific B cells, though total and antigen-specific IgG levels were unchanged. These findings suggest that CD19xCD3 TCE preferentially target autoreactive B cells and may be effective at lower doses than those used in oncology. Our data support the potential of CD19xCD3 bispecific T cell engagers as a therapeutic strategy for PDs. eTOC SynopsisGross, Jochimsen, Drager and colleagues demonstrate that CD19xCD3 bispecific T cell engagers, can selectively target autoreactive B cells and induce remission in a mouse model of pemphigoid disease, highlighting their potential as a novel therapeutic strategy for autoimmune blistering disorders.

immunology↗

bioRxiv2025

Functional connectivity is linked to symbolic BOLD patterns: replication, extension, and clinical application of the human 'complexome'

Functional connectivity (FC) quantifies the temporal coherence of blood-oxygen-level-dependent (BOLD) signals across brain regions. Recently, the information-theoretic "complexome" framework has linked FC to coinciding complexity drops: transient moments in which regional BOLD signals simultaneously become regular. Here, we replicate this relationship in an independent dataset and extend the framework by (i) integrating it with signal cofluctuation analysis through edge-timeseries, (ii) extending the previous binary concept of simultaneous complexity drops to a continuous, threshold-free calculation, (iii) providing evidence of clinical relevance in the model disease of anti-N-methyl-D-aspartate-receptor encephalitis, and (iv) deriving a novel measure of pairwise dissimilarity in local BOLD patterns. This index of pattern incongruency (IPI) explains clinically relevant FC reductions and maps onto novel associations with cognition. These findings show that global FC is closely related to local patterns within underlying BOLD signals, strengthening the link between complexity dynamics and the brains functional organization as a large-scale network.

neuroscience↗

bioRxiv2025

Myeloid cell-mediated killing of B-ALL by CD38 and CD20IgA antibody variants is enhanced by CD47/SIRPα interference

Enhancing myeloid effector cell recruitment may improve immunotherapy by monoclonal antibodies - including that against acute lymphoblastic leukemia (ALL). To assess expression of target antigens in B-ALL, we compared mRNA profiling of 559 patient leukemia samples across 18 molecular subtypes with that of representative cell lines. The latter served as target cells to compare human IgG1 or IgA2 variants against CD19, CD20 or CD38 in antibody-dependent cellular phagocytosis (ADCP) by macrophages and antibody-dependent cell-mediated cytotoxicity (ADCC) by polymorphonuclear leukocytes (PMN). Interestingly, antibodies against broadly expressed CD19 were negligibly effective in mediating ADCP or ADCC. Antibodies against CD20 or CD38, the former variably expressed across subtypes, triggered ADCP by macrophages both as IgG1 and IgA2. However, PMN mediated ADCC against CD20 or CD38 was only observed with IgA2 variants, but not with respective IgG1 antibodies. Blocking the myeloid checkpoint molecule CD47 with a CD47 antibody or a soluble SIRP-Fc fusion protein enhanced ADCP and ADCC by IgA2 antibodies. The binding site for SIRP on CD47 contains an N-terminal pyroglutamate (pGlu), whose formation is catalyzed by glutaminyl-peptide cyclotransferase like (QPCTL). The direct involvement of pGlu in CD47/SIRP interactions was shown by using engineered CD47 variants. Both CD47 and QPCTL were broadly expressed across BCP-ALL subtypes, indicating QPCTL inhibitors as additional therapeutic option. Importantly, the combination of anti-CD38 IgA2 and CD47 blockade was effective against xenografted B-ALL cells in human FcRI (CD89) transgenic (tg) NXG mice. Together, these studies support the combination of anti-CD38 IgA2 with CD47 interference to improve myeloid effector cell recruitment for immunotherapy of B-ALL. Data sharing statementRNA-Seq data from BCP-ALL patients and B cells from healthy donors are available in the European Genome-Phenome Archive (EGA) accession numbers EGAS00001006107 and EGAS00001007305, respectively. Mass spectrometry data of analyzed proteins will be made available after manuscript acceptance on PRIDE - PRoteomics IDEntifications Database. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=174 HEIGHT=200 SRC="FIGDIR/small/669665v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@15220daorg.highwire.dtl.DTLVardef@eace04org.highwire.dtl.DTLVardef@17b87daorg.highwire.dtl.DTLVardef@1142822_HPS_FORMAT_FIGEXP M_FIG C_FIG Key pointsO_LIIgG1 and IgA2 antibodies against CD38 or CD20 were effective in recruiting macrophages for ADCP, but only IgA2 triggered ADCC by PMN C_LIO_LIMyeloid effector cell activation was enhanced by interfering with the CD47/SIRP axis, especially when IgA2 antibodies were applied C_LI

cancer biology↗

bioRxiv2024

Persistent cognitive deficits in anti-LGI1 encephalitis are linked to a reorganization of structural brain networks

Structured AbstractO_ST_ABSImportanceC_ST_ABSDespite immunotherapy, most patients with anti-leucine-rich, glioma-inactivated 1 encephalitis (LGI1-E) develop long-term cognitive deficits that persist for years after peak illness. However, the structural brain changes that underlie these deficits remain poorly understood. ObjectiveTo study the relationship between cognitive outcomes and white matter (WM) networks in LGI1-E. DesignCross-sectional study. SettingGerman university center (Charite - Universitatsmedizin Berlin). Participants25 patients with LGI1-E (19/25 male [76%], mean age: 63 {+/-} 12 years) and 25 age- and sex-matched healthy controls (HC), recruited between January 2013 and April 2019. Main Outcomes and MeasuresClinical assessments including the modified Rankin Scale (mRS) and Clinical Assessment Scale in Autoimmune Encephalitis (CASE); comprehensive cognitive testing; WM tractography using diffusion-weighted MRI. ResultsAll patients had received first-line immunotherapy, and two-thirds underwent second-line immunotherapy. Patients showed a significant reduction in mRS scores from peak illness to post-acute follow-up (z = -3.8, p < 0.001, n = 20), with 85% presenting "good" functional outcomes (post-acute mRS [≤] 2), paralleled by a significant reduction in CASE scores (z = -3.5, p < 0.001, n = 20). Despite this overall improvement, however, cognitive symptoms were highly prevalent at peak illness (95% of patients affected) and strongly persisted into the post-acute disease stage (85% affected). Neuroimaging at post-acute follow-up (median: 12 months from onset) revealed that LGI1-E is characterized by (i) significantly reduced whole-brain structural connectivity (t = -2.16, p = 0.036, d = -0.61), (ii) a cortico-subcortical hypoconnectivity cluster that strongly affects the hippocampus but also severely impacts extra-limbic brain systems, (iii) systematic limbic and extra-limbic decreases in node degree -- a graph-theoretical measure of overall connectedness, and (iv) a "topological reorganization" of structural brain networks, marked by a bidirectional shift in the relative importance of individual brain regions in the network. Importantly, the extent of this network reorganization was significantly related to persistent cognitive deficits in the domains of verbal memory (r = -0.57, p = 0.007, n = 21), attention (r = -0.47, p = 0.030, n = 21), and executive functions (r = -0.60, p = 0.010, n = 17). Conclusion and RelevanceThis study characterizes LGI1-E as a network disease that affects both limbic and extra-limbic brain systems and shows that a reorganization of WM networks is linked to multi-domain cognitive deficits in the post-acute disease stage - despite immunotherapy and good overall recovery. These findings highlight the need for extended treatment strategies to improve long-term cognitive outcomes and propose a sensitive new neuroimaging marker to include in prospective clinical trials. Key PointsO_ST_ABSQuestionC_ST_ABSWhat structural brain changes underlie the persistent cognitive deficits observed in patients with anti-leucine-rich, glioma-inactivated 1 encephalitis (LGI1-E)? FindingsThis cross-sectional study shows that LGI1-E is characterized by a structural reorganization of white matter networks that affects both limbic and extra-limbic brain systems and correlates with persistent deficits in verbal memory, attention, and executive functions at post-acute follow-up - despite immunotherapy and good overall clinical recovery. MeaningThis study characterizes LGI1-E as a network disease -beyond focal damage to the limbic system- and shows that persistent cognitive deficits relate to immunotherapy-resistant changes in structural brain networks, highlighting the need for extended treatment strategies to improve long-term cognitive outcomes.

neuroscience↗

bioRxiv2023

The formation of brain shape in human newborns

The neonatal period represents a critical phase of human brain development. During this time, the brain shows a dramatic increase in size, but it remains largely unclear how the morphology of the human brain develops in early post-partum life. Here we show that human newborns undergo a rapid formation of brain shape, beyond the expected growth in brain size. Using fractal analysis of structural neuroimaging data, we show that brain shape (i) strongly reflects infant maturity beyond differences in brain size, (ii) significantly outperforms brain size in predicting infant age at scan (mean error ~4 days), (iii) detects persistent alterations in prematurely born infants that are not captured by brain size, (iv) is consistently more sensitive to genetic similarity among neonates, and (v) is superior in predicting which newborns are twin siblings, with up to 97% accuracy. These findings identify the formation of brain shape as a fundamental maturational process in human brain development.

neuroscience↗

bioRxiv2022

Functional connectivity dynamics reflect disability and multi-domain clinical impairment in patients with relapsing-remitting multiple sclerosis

BackgroundFunctional neuroimaging studies have revealed complex and heterogeneous patterns of aberrant functional connectivity (FC) in multiple sclerosis (MS), yet it remains unclear how time-resolved FC relates to variance in clinical disease severity. ObjectivesTo characterize brain activity in MS patients with time-resolved FC analysis and explore the relationship between disease severity, multi-domain impairments, and altered network dynamics. MethodsResting-state functional MRI data were acquired from 101 MS patients and 101 age- and sex-matched healthy controls (HC). Dynamic FC analysis identified five connectivity states that were compared between HC and patients with high vs. low disability. ResultsPatients with higher disease severity exhibited a more widespread spatiotemporal pattern of altered FC and spent more time in a high-connectivity, low-occurrence state compared to patients with lower disease severity and HC. Depressive symptom severity was positively related to functional dynamics on global and network scales in patients, while fatigue and motor impairment were inversely related to frontoparietal network connectivity with the basal ganglia. ConclusionsTime-resolved FC analysis uncovered alterations in network dynamics and clinical correlations that remained undetected with a static account of brain activity. Such time-varying approaches are thus crucial for disentangling the relationship between brain dynamics, disease severity, and symptoms in MS.

neuroscience↗

bioRxiv2022

Reduced resilience of functional state transitions in patients with anti-NMDA receptor encephalitis

ObjectivePatients with anti-NMDA receptor encephalitis suffer from a severe neuropsychiatric syndrome, yet most patients show no abnormalities in routine magnetic resonance imaging. In contrast, advanced neuroimaging studies have consistently identified disrupted functional connectivity in these patients, with recent work suggesting increased volatility of functional state dynamics. Here, we investigate these network dynamics through the spatiotemporal trajectory of meta-state transitions, yielding a time-resolved account of brain state exploration in anti-NMDA receptor encephalitis. MethodsResting-state functional magnetic resonance imaging data were acquired in 73 patients with NMDAR encephalitis and 73 age- and sex-matched healthy controls. Time-resolved functional connectivity was clustered into brain meta-states, giving rise to a time-resolved transition network graph with states as nodes and transitions between brain meta-states as weighted, directed edges. Network topology, robustness, and transition cost of these transition networks were compared between groups. ResultsTransition networks of patients showed significantly lower local efficiency (t = -2.54, pFDR = 0.026), lower robustness (t = -2.01, pFDR = 0.048) and higher leap size (t = 2.33, pFDR = 0.026) compared to controls. Furthermore, the ratio of within-to-between module transitions and state similarity was significantly lower in patients. Importantly, alterations of brain state transitions correlated with disease severity. InterpretationThese findings reveal systematic alterations of transition networks in patients, suggesting that anti-NMDA receptor encephalitis is characterized by reduced stability of brain state transitions and that this reduced resilience of transition networks plays a clinically relevant role in the manifestation of the disease.

neuroscience↗

bioRxiv2021

A spatiotemporal complexity architecture of human brain activity

The human brain operates in large-scale functional networks. These networks are thought to arise from neural variability, yet the principles behind this link remain unknown. Here we report a mechanism by which the brains network architecture is tightly linked to critical episodes of neural regularity, visible as spontaneous complexity drops in functional MRI signals. These episodes support the formation of functional connections between brain regions, subserve the propagation of neural activity, and reflect inter-individual differences in age and behavior. Furthermore, complexity drops define neural states that dynamically shape the coupling strength, topological structure, and hierarchy of brain networks and comprehensively explain known structure-function relationships within the brain. These findings delineate a unifying complexity architecture of neural activity - a human complexome that underpins the brains functional network organization.

neuroscience↗

bioRxiv2021

Fingerprinting and behavioural prediction rest on distinct functional systems of the human connectome

The prediction of inter-individual behavioural differences from neuroimaging data is a rapidly evolving field of research, focusing on individualised methods to describe human brain organisation on the single-subject level. One method that harnesses such individual signatures is functional connectome fingerprinting, which can reliably identify individuals from large study populations. While connectome fingerprints have been previously associated with individual cognitive function, these associations rest on indirect evidence. Contrasting with these previous reports, here we systematically investigate the link between connectome fingerprints and the prediction of behaviour on different levels of brain network organisation (individual edges, network interactions, topographical organisation, and edge variability), using 339 resting-state fMRI datasets from the Human Connectome Project. Our analysis revealed a significant divergence between connectivity signatures that discriminate between individuals and those predictive of behaviour on all levels of network organisation. Across different parcellation schemes, thresholds and prediction algorithms, we consistently find fingerprints in higher-order multimodal association cortices, while neural correlates of behaviour display a more variable topological distribution. Furthermore, we find the standard deviation of connections between subjects to be significantly higher in fingerprinting than in prediction, making inter-individual connection variability a possible separating marker. These results demonstrate that participant identification and behavioural prediction involve highly distinct functional systems of the human connectome, suggesting that connectome fingerprints are not as functionally relevant as previously believed. The present study thus calls for a re-evaluation of the significance of functional connectivity fingerprints in personalized medicine.

neuroscience↗

bioRxiv2020

State-dependent signatures of Anti-NMDA-Receptor Encephalitis: a dynamic functional connectivity study

ObjectiveTraditional static functional connectivity (FC) analyses have shown functional network alterations in patients with anti-NMDA receptor encephalitis (NMDARE). Here, we use a dynamic FC approach that increases the temporal resolution of connectivity analyses from minutes to seconds. We hereby explore the spatiotemporal variability of large-scale brain network activity in NMDARE and assess the discriminatory power of functional brain states in a supervised classification approach. MethodsWe included resting-state fMRI data from 57 patients and 61 controls to extract four discrete connectivity states and assess state-wise group differences in FC, dwell time, transition frequency, fraction time and occurrence rate. Additionally, for each state, logistic regression models with embedded feature selection were trained to predict group status in a leave-one-out cross-validation scheme. ResultsCompared to controls, patients exhibited diverging dynamic FC patterns in three out of four states mainly encompassing the default-mode network and frontal areas. This was accompanied by a characteristic shift in the dwell time pattern and higher volatility of state transitions in patients. Moreover, dynamic FC measures were associated with disease severity, disease duration and positive and negative schizophrenia-like symptoms. Predictive power was highest in dynamic FC models and outperformed static analyses, reaching up to 78.6% classification accuracy. ConclusionsBy applying time-resolved analyses, we disentangle state-specific FC impairments and characteristic changes in temporal dynamics not detected in static analyses, offering new perspectives on functional reorganization underlying NMDARE. Correlation of dynamic FC measures with disease symptoms and severity indicates their clinical relevance and potential as prognostic biomarkers in NMDARE.

neuroscience↗

bioRxiv2017

Sampling Stability And Processing Parameter-Dependent Characteristics Of The 3D Fractal Dimension As A Marker Of Structural Brain Complexity In Magnetic Resonance Images

Fractal analysis represents a promising new approach to structural neuroimaging data, yet systematic evaluation of the fractal dimension (FD) as a marker of structural brain complexity is scarce. Here we present in-depth methodological assessment of FD estimation in structural brain MRI. On the computational side, we show that spatial scale optimization can significantly improve FD estimation accuracy, as suggested by simulation studies with known FD values. For empirical evaluation, we analyzed two recent open-access neuroimaging data sets (MASSIVE and Midnight Scan Club), stratified by fundamental image characteristics including registration, sequence weighting, spatial resolution, segmentation procedures, tissue type, and image complexity. Deviation analyses showed high repeated-acquisition stability of the FD estimates across both data sets, with differential deviation susceptibility according to image characteristics. While less frequently studied in the literature, FD estimation in T2-weighted images yielded robust outcomes. Importantly, we observed a significant impact of image registration on absolute FD estimates. Applying different registration schemes, we found that unbalanced registration induced i) repeated-measurement deviation clusters around the registration target, ii) strong bidirectional correlations among image analysis groups, and iii) spurious associations between the FD and an index of structural similarity, and these effects were strongly attenuated by reregistration in both data sets. Indeed, differences in FD between scans did not simply track differences in structure per se, suggesting that structural complexity and structural similarity represent distinct aspects of structural brain MRI. In conclusion, scale optimization can improve FD estimation accuracy, and empirical FD estimates are reliable yet sensitive to image characteristics.

neuroscience↗