Biology subjects

Buscher, K.

Publications and source records attributed to Buscher, K..

5 recordsLinked to original sources

bioRxiv2025

Glucose Metabolism Sustains Aberrant STAT3 Signaling in Colorectal Cancer via Glycosylated Paracrine Factors.

The JAK-STAT3 signaling pathway is a key driver of colorectal cancer (CRC) progression. While STAT3 is canonically activated by cytokines such as IL-6, this activation is typically transient due to negative feedback mechanisms. In CRC, however, STAT3 is aberrantly and persistently activated, promoting tumor cell proliferation and survival. Here, we demonstrate that glucose sustains STAT3 activation independent of cytokine availability. By manipulating glucose metabolism, we show that both glucose and its downstream metabolite, GlcNAc, are essential for maintaining STAT3 activation. Moreover, cells with high basal STAT3 activity produce glucose-dependent glycosylated proteins that can activate STAT3 in neighboring cells via paracrine signaling. Proteomic analysis identified multiple candidate proteins involved in this process; however, no single protein was sufficient to fully activate STAT3, suggesting that a combination of glycosylated proteins likely acts synergistically. In vivo, inhibition of glycolysis reduces STAT3 activation in tumors, and genetic deletion of STAT3 in subcutaneous tumor models significantly decreases tumor growth. Together, these findings uncover a novel mechanism by which glucose metabolism supports sustained STAT3 activation in CRC, highlighting a potential metabolic vulnerability for therapeutic targeting.

cancer biology↗

bioRxiv2025

Labile iron pool dynamics do not drive ferroptosis potentiation in colorectal cancer cells

Colorectal cancer (CRC) is the second leading cause of cancer-related mortality in the United States. CRC tumors exhibit aberrant iron accumulation, which supports tumor cell proliferation through multiple metabolic pathways. However, the oncogenic benefits of elevated iron must be counterbalanced by its potential to catalyze oxidative damage via reactive oxygen species generated from labile, redox-active iron. Ferroptosis is a regulated, non-apoptotic form of cell death characterized by iron-dependent lipid peroxidation. This process is tightly controlled by the selenoenzyme glutathione peroxidase 4 (GPX4), which reduces lipid peroxides and can be pharmacologically inhibited by agents such as RSL3 and JKE1674. A key source of redox-active iron is the labile iron pool (LIP), yet its role in regulating ferroptosis remains incompletely defined. To examine this, we supplemented CRC cells with exogenous iron following pharmacologic induction of ferroptosis. Iron supplementation significantly reduced cell viability, suggesting that expansion of the LIP potentiates ferroptotic cell death. However, whether ferroptosis is accompanied by dynamic changes in the LIP, and if such changes are mechanistically required for its potentiation, were unknown. To further characterize this response, we profiled the expression of iron regulatory genes under ferroptotic conditions and observed no change in transcriptional response in iron homeostasis genes. Using a reactivity-based probe of labile iron, we found that the LIP did not measurably increase during ferroptosis induction with GPX4 inhibition or inhibition of the SLC7A11 cysteine/glutamate antiporter. These findings suggest that the LIP does not expand upon pharmacological initiated ferroptosis, despite the potentiating effect of exogenous iron supplementation.

cancer biology↗

bioRxiv2024

Microvascular immunity is organ-specific and concealed in peripheral blood

Blood tests are a common method for diagnosing and monitoring various health conditions. Nevertheless, the extent to which phlebotomy can offer insights into immune and organ dysfunction remains uncertain. Here, we conducted a comprehensive analysis of blood-borne leukocytes in the microvasculature of different mouse organs and compared it to peripheral blood and parenchymal samples. We observed that microvascular immune cells outnumber tissue-resident counterparts in the kidney, liver and lung. Classical monocytes and lymphocytes are diminished while nonclassical and SSC-high monocytes are enriched compared to blood. Utilizing single-cell sequencing, we identified specific cell populations up to 100-fold expanded in the kidney vasculature including macrophages, plasmacytoid dendritic cells, B cells, and innate lymphoid cells type 2. Microvascular enrichment could trigger a local phenotype switch as shown in glomerulus-restricted B cells. Peritonitis and acute kidney injury (AKI) elicited a multifaceted and systemic response of microvascular leukocytes. It involved remote organ effects, such as a 16-fold increase of leukocytes in the splenic circulation or 64-fold increase of SSC-high monocytes in the liver circulation that was not detectable in the peripheral blood or the tissue. Following full recovery from AKI, persistent and complex changes were observed predominantly in the renal vasculature, while most leukocytes in the peripheral blood had already returned to baseline levels. Collectively, our findings suggest a paradigm of organ- and disease-specific microvascular immunity that largely eludes conventional blood and tissue analysis.

immunology↗

bioRxiv2018

Single-cell transcriptomics identifies drivers of local inflammation in multiple sclerosis

Cerebrospinal fluid (CSF) protects the central nervous system (CNS) and analyzing CSF aids the diagnosis of CNS diseases, but our understanding of CSF leukocytes remains superficial. Here, we firstly provide a transcriptional map of single leukocytes in CSF compared to blood. Leukocyte composition and transcriptome were compartment-specific with CSF-enrichment of myeloid dendritic cells and a border-associated phenotype of monocytes.\n\nWe secondly tested how multiple sclerosis (MS) - an autoimmune disease of the CNS - affected both compartments. MS increased transcriptional diversity in blood, while it preferentially increased cell type diversity in CSF. In addition to the known expansion of B lineage cells, we identified an increase of cytotoxic-phenotype and follicular T helper (TFH) cells in the CSF. In mice, TFH cells accordingly promoted B cell infiltration into the CNS and severity of MS animal models. Immune mechanisms in MS are thus highly compartmentalized and indicate local T/B cell interaction.

immunology↗

bioRxiv2018

PRESTO, a new tool for integrating large-scale -omics data and discovering disease-specific signatures

BackgroundCohesive visualization and interpretation of hyperdimensional, large-scale -omics data is an ongoing challenge, particularly for biologists and clinicians involved in current highly complex sequencing studies. Multivariate studies are often better suited towards non-linear network analysis than differential expression testing. Here, we present PRESTO, a PREdictive Stochastic neighbor embedding Tool for Omics, which allows unsupervised dimensionality reduction of multivariate data matrices with thousands of subjects or conditions. PRESTO is intuitively integrated into an interactive user interface that helps to visualize the multidimensional patterns in genome-wide transcriptomic data from basic science and clinical studies.\n\nResultsPRESTO was tested with multiple input omics platforms, including microarray and proteomics from both mouse and human clinical datasets. PRESTO can analyze up to tens of thousands of genes and shows no increase in processing time with a large number of samples or patients. In complex datasets, such as those with multiple time points, several patient groups, or diverse mouse strains, PRESTO outperformed conventional methods. Core co-expressed gene networks were intuitively grouped in clusters, or gates, after dimensionality reduction and remained consistent across users. Networks were identified and assigned to physiological and pathological functions that cannot be gleaned from conventional bioinformatics analyses. PRESTO detected gene networks from the natural variations among mouse macrophages and human blood leukocytes. We applied PRESTO to clinical transcriptomic and proteomic data from large patient cohorts and detected disease-defining signatures in antibody-mediated kidney transplant rejection, renal cell carcinoma, and relapsing acute myeloid leukemia (AML). In AML, PRESTO confirmed a previously described gene signature and found a new signature of 10 genes that is highly predictive of patient outcome.\n\nConclusionsPRESTO offers an important integration of powerful bioinformatics tools with an interactive user interface that increases data analysis accessibility beyond bioinformaticians and coders. Here, we show that PRESTO out performs conventional methods, such as DE analysis, in multi-dimensional datasets and can identify biologically relevant co-expression gene networks. In paired samples or time points, co-expression networks could be compared for insight into longitudinal regulatory mechanisms. Additionally, PRESTO identified disease-specific signatures in clinical datasets with highly significant diagnostic and prognostic potential.

bioinformatics↗