Biology subjects

Schulte, J.

Publications and source records attributed to Schulte, J..

12 recordsLinked to original sources

bioRxiv2026

Acute perilesional excitability explains long-term motor recovery after stroke

Stroke is a leading cause of disability, and changes in neuronal excitability in perilesional regions may critically influence patients recovery. While reduced excitability is often associated with impaired recovery, increased excitability following injury may support reparative mechanisms. Although animal studies have shown how synaptic transmission adapts after stroke, a mechanistic understanding of how these excitability changes in the perilesional area relate to recovery in acute patients remains unclear. Here, we apply patient-specific (N = 96) computational whole-brain models to infer regional excitability, focusing on both perilesional and non-perilesional sites. Specifically, we estimate the firing sensitivity of local excitatory neuronal populations. Our findings indicate large inter-subject variability, with patients displaying both relative perilesional hypo- and hyper-excitability. Notably, perilesional excitability emerges as a robust predictor (P = 0.002) of motor recovery one year after the stroke, but not of acute post-stroke motor impairment, emphasizing its significance in specifically shaping long-term recovery. This synaptic modulation of excitability exhibits a strong correlation with gamma-aminobutyric acid A (GABA-A) receptor density distributions before the stroke, providing a potential biological substrate. These findings highlight the subject-specific nature of perilesional excitability, positioning it as a compelling target for personalized interventions to optimize post-stroke motor recovery.

neuroscience↗

bioRxiv2026

The ITCC-P4 PDX platform of pediatric cancers for preclinical testing

Cancer is the leading cause of disease-related deaths among children in high-income countries. Tumor heterogeneity and lack of mechanism-of-action-based therapeutic options are key challenges to overcome in order to improve pediatric cancer patients survival. Here, we report the EU-IMI-2 funded public-private partnership "ITCC-Pediatric Preclinical Proof-of-Concept Platform" (ITCC-P4), which has built a large repertoire of patient-derived xenograft (PDX) models, representing all major solid pediatric cancer types, for in vivo drug testing. Three-hundred-fifty-three PDX models from diagnostic and relapsed pediatric cancers have been established and molecularly characterized, together with matched germline/tumor samples. As proof-of-concept, we present in vivo drug screening data in neuroblastoma and rhabdomyosarcoma models. PDX data, accessible at http://r2platform.com/itcc-p4, allow the selection of models based on oncogenic drivers and/or potential biomarkers for preclinical testing. Operated by a non-profit entity (www.itccp4.com), this sustainable platform aids academic and industrial researchers in developing and prioritizing innovative therapies for pediatric cancer. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/703023v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@195ba30org.highwire.dtl.DTLVardef@f2c2d9org.highwire.dtl.DTLVardef@1d63f4dorg.highwire.dtl.DTLVardef@d60027_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2023

Time-of-day effects of drugs revealed by high-throughput deep phenotyping

The circadian clock, a fundamental biological regulator, governs essential cellular processes in health and disease. Circadian-based therapeutic strategies are increasingly gaining recognition as promising avenues. Aligning drug administration with the circadian rhythm can enhance treatment efficacy and minimize side effects. Yet, uncovering the optimal treatment timings remains challenging, limiting their widespread adoption. In this work, we introduce a novel high-throughput approach integrating live-imaging and data analysis techniques to deep-phenotype cancer cell models, evaluating their circadian rhythms, growth, and drug responses. We devised a streamlined process for profiling drug sensitivities across different times of the day, identifying optimal treatment windows and responsive cell types and drug combinations. Finally, we implement multiple computational tools to uncover cellular and genetic factors shaping time-of-day drug sensitivity. Our versatile approach is adaptable to various biological models, facilitating its broad application and relevance. Ultimately, this research leverages circadian rhythms to optimize anti-cancer drug treatments, promising improved outcomes and transformative treatment strategies.

cancer biology↗

bioRxiv2023

Cell free expression in proteinosomes prepared from native protein-PNIPAAm conjugates

Towards the goal of building synthetic cells from the bottom-up, the establishment of micrometer-sized compartments that contain and support cell free transcription and translation that couple cellular structure to function is of critical importance. Proteinosomes, formed from crosslinked cationized protein-polymer conjugates offer a promising solution to membrane-bound compartmentalisation with an open, semi-permeable membrane. Critically, to date, there have been no demonstration of cell free transcription and translation within water-in-water proteinosomes. Herein, we present a novel approach to the fabrication of proteinosomes directly from native protein-polymer (BSA-PNIPAAm) conjugates. We show that these native proteinosomes offer an excellent alternative as artificial cell chassis. Significantly, the native proteinosomes are stable under high salt conditions and can consequently support cell free transcription and translation. The native proteinosomes offer enhanced protein expression compared to proteinosomes prepared from traditional methodologies. Furthermore, we demonstrate the integration of proteinosomes into higher order cellular architectures with membrane free compartments and liposomes. The integration of bioinspired architectural elements with the central dogma is an essential building block for realizing minimal synthetic cells and is key for exploiting artificial cells in real-world applications.

synthetic biology↗

bioRxiv2023

The global communication architecture of the human brain transcends the subcortical - cortical - cerebellar subdivisions

The white matter is made of anatomical fibres that constitute the highway of long-range connections between different parts of the brain. This network is referred to as the brains structural connectivity and lays the foundation of network interaction between brain areas. When analysing the architectural principles of this global network most studies have mainly focused on cortico-cortical and partly on cortico-subcortical connections. Here we show, for the first time, how the integrated cortical, subcortical, and cerebellar brain areas shape the structural architecture of the whole brain. We find that dense clusters vertically transverse cortical, subcortical, and cerebellar brain areas, which are themselves centralised by a global rich-club consisting similarly of cortical and subcortical brain areas. Notably, the most prominent hubs can be found in subcortical brain regions, and their targeted in-silico lesions proved to be most harmful for global signal propagation. Individually, the cortical, subcortical, and cerebellar sub-networks manifest distinct network features despite some similarities, which underline their unique structural fingerprints. Our results, exposing the heterogeneity of internal organisation across cortex, subcortex, and cerebellum, and the crucial role of the subcortex for the integration of the global anatomical pathways, highlight the need to overcome the prevalent cortex-centric focus towards a global consideration of the structural connectivity.

neuroscience↗

bioRxiv2022

Single-cell multi-omics reveals dynamics of purifying selection of pathogenic mitochondrial DNA across human immune cells

Cells experience intrinsic and extrinsic pressures that affect their proclivity to expand and persist in vivo. In congenital disorders caused by loss-of-function mutations in mitochondrial DNA (mtDNA), metabolic vulnerabilities may result in cell-type specific phenotypes and depletion of pathogenic alleles, contributing to purifying selection. However, the impact of pathogenic mtDNA mutations on the cellular hematopoietic landscape is not well understood. Here, we establish a multi-omics approach to quantify deletions in mtDNA alongside cell state features in single cells derived from Pearson syndrome patients. We resolve the interdependence between pathogenic mtDNA and lineage, including purifying selection against deletions in effector/memory CD8 T-cell populations and recent thymic emigrants and dynamics in other hematopoietic populations. Our mapping of lineage-specific purifying selection dynamics in primary cells from patients carrying pathogenic heteroplasmy provides a new perspective on recurrent clinical phenotypes in mitochondrial disorders, including cancer and infection, with potential broader relevance to age-related immune dysfunction.

genetics↗

bioRxiv2022

Amplicon structure creates collateral therapeutic vulnerability in cancer

Although DNA amplifications in cancers frequently harbor passenger genes alongside oncogenes, the functional consequence of such co-amplifications and their impact for therapy remains ill-defined. We discovered that passenger co-amplifications can create amplicon structure-specific collateral vulnerabilities. We present the DEAD-box helicase 1 (DDX1) gene as a bona fide passenger co-amplified with MYCN in cancers. Survival of cancer cells with DDX1 co-amplifications strongly depends on the mammalian target of rapamycin complex 1 (mTORC1). Mechanistically, aberrant DDX1 expression inhibits the tricarboxylic acid cycle through a previously unrecognized interaction with dihydrolipoamide S-succinyltransferase, a component of the alpha-ketoglutarate dehydrogenase complex. Cells expressing aberrant DDX1 levels compensate for the metabolic shift by enhancing mTORC1 activity. Consequently, pharmacological mTORC1 inhibition triggered cell death specifically in cells harboring the DDX1 co-amplification. This work highlights a significant contribution of passenger gene alterations to the therapeutic susceptibility of cancers. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/506647v2_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@58b27dorg.highwire.dtl.DTLVardef@12e2fccorg.highwire.dtl.DTLVardef@1440f33org.highwire.dtl.DTLVardef@141e933_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2022

Multiple lineages of Monkeypox virus detected in the United States, 2021-2022

Monkeypox is a viral zoonotic disease endemic in Central and West Africa. In May 2022, dozens of non-endemic countries reported hundreds of monkeypox cases, most with no epidemiological link to Africa. We identified two lineages of Monkeypox virus (MPXV) among nine 2021 and 2022 U.S. monkeypox cases. A 2021 case was highly similar to the 2022 MPXV outbreak variant, suggesting a common ancestor. Analysis of mutations among these two lineages revealed an extreme preference for GA-to-AA mutations indicative of APOBEC3 cytosine deaminase activity that was shared among West African MPXV since 2017 but absent from Congo Basin lineages. Poxviruses are not thought to be subject to APOBEC3 editing; however, these findings suggest APOBEC3 activity has been recurrent and dominant in recent West African MPXV evolution.

genomics↗

bioRxiv2020

The Impact of Digital Histopathology Batch Effect on Deep Learning Model Accuracy and Bias

The Cancer Genome Atlas (TCGA) is one of the largest biorepositories of digital histology. Deep learning (DL) models have been trained on TCGA to predict numerous features directly from histology, including survival, gene expression patterns, and driver mutations. However, we demonstrate that these features vary substantially across tissue submitting sites in TCGA for over 3,000 patients with six cancer subtypes. Additionally, we show that histologic image differences between submitting sites can easily be identified with DL. This site detection remains possible despite commonly used color normalization and augmentation methods, and we quantify the digital image characteristics constituting this histologic batch effect. As an example, we show that patient ethnicity within the TCGA breast cancer cohort can be inferred from histology due to site-level batch effect, which must be accounted for to ensure equitable application of DL. Batch effect also leads to overoptimistic estimates of model performance, and we propose a quadratic programming method to guide validation that abrogates this bias.

bioinformatics↗

bioRxiv2020

SOX11 is a lineage-dependency factor and master epigenetic regulator in neuroblastoma

The pediatric extra-cranial tumor neuroblastoma (NB) is characterised by a low mutation burden while copy number alterations are present in most high-risk cases. We identified SOX11 as a strong lineage dependency transcription factor in adrenergic NB based on recurrent chromosome 2p focal gains and amplifications, its specific expression in the normal sympatho-adrenal lineage and adrenergic NBs and its regulation by multiple adrenergic specific cis-interacting (super-)enhancers. Adrenergic NBs are strongly dependent on high SOX11 expression levels for growth and proliferation. Through genome-wide DNA-binding and transcriptome analysis, we identified and validated functional SOX11 target genes, several of which implicated in chromatin remodeling and epigenetic modification. SOX11 controls chromatin accessibility predominantly affecting distal adrenergic lineage-specific enhancers marked by binding sites of the adrenergic core regulatory circuitry. During normal sympathoblast differentiation we find expression of SOX11 prior to members of the adrenergic core regulatory circuitry. Given the broad control of SOX11 of multiple epigenetic regulatory complexes and its presumed pioneer factor function, we propose that adrenergic NB cells have co-opted the normal role of SOX11 as a crucial regulator of chromatin accessibility and cell identity.

cancer biology↗

bioRxiv2019

Deep learning detects virus presence in cancer histology

Oncogenic viruses like human papilloma virus (HPV) or Epstein Barr virus (EBV) are a major cause of human cancer. Viral oncogenesis has a direct impact on treatment decisions because virus-associated tumors can demand a lower intensity of chemotherapy and radiation or can be more susceptible to immune check-point inhibition. However, molecular tests for HPV and EBV are not ubiquitously available.\n\nWe hypothesized that the histopathological features of virus-driven and non-virus driven cancers are sufficiently different to be detectable by artificial intelligence (AI) through deep learning-based analysis of images from routine hematoxylin and eosin (HE) stained slides. We show that deep transfer learning can predict presence of HPV in head and neck cancer with a patient-level 3-fold cross validated area-under-the-curve (AUC) of 0.89 [0.82; 0.94]. The same workflow was used for Epstein-Barr virus (EBV) driven gastric cancer achieving a cross-validated AUC of 0.80 [0.70; 0.92] and a similar performance in external validation sets. Reverse-engineering our deep neural networks, we show that the key morphological features can be made understandable to humans.\n\nThis workflow could enable a fast and low-cost method to identify virus-induced cancer in clinical trials or clinical routine. At the same time, our approach for feature visualization allows pathologists to look into the black box of deep learning, enabling them to check the plausibility of computer-based image classification.

cancer biology↗

bioRxiv2017

Therapeutic targeting of PGBD5-induced DNA repair dependency in pediatric solid tumors

Despite intense efforts, the cure rates of childhood and adult solid tumors are not satisfactory. Resistance to intensive chemotherapy is common, and targets for molecular therapies are largely undefined. We have now found that the majority of childhood solid tumors, including rhabdoid tumors, neuroblastoma, medulloblastoma and Ewing sarcoma, express an active DNA transposase PGBD5 that can promote site-specific genomic rearrangements in human cells. Using functional genetic approaches, we found that mouse and human cells deficient in non-homologous end joining (NHEJ) DNA repair cannot tolerate the expression of PGBD5. In a chemical screen of DNA damage signaling inhibitors, we identified AZD6738 as a specific sensitizer of PGBD5-dependent DNA damage and apoptosis. We found that expression of PGBD5, but not its nuclease activity-deficient mutant, was sufficient to induce hypersensitivity to AZD6738. Depletion of endogenous PGBD5 conferred resistance to AZD6738 in human tumor cells. PGBD5-expressing tumor cells accumulated unrepaired DNA damage in response to AZD6738 treatment, and underwent apoptosis in both dividing and G1 phase cells in the absence of immediate DNA replication stress. Accordingly, AZD6738 exhibited nanomolar potency against the majority of neuroblastoma, medulloblastoma, Ewing sarcoma and rhabdoid tumor cells tested, while sparing non-transformed human and mouse embryonic fibroblasts in vitro. Finally, treatment with AZD6738 induced apoptosis and regression of human neuroblastoma and medulloblastoma tumors engrafted in immunodeficient mice in vivo. This effect was potentiated by combined treatment with cisplatin, including significant anti-tumor activity against patient-derived primary neuroblastoma xenografts. These findings delineate a therapeutically actionable synthetic dependency induced in PGBD5-expressing solid tumors.

cancer biology↗