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Klingmueller, U.

Publications and source records attributed to Klingmueller, U..

11 recordsLinked to original sources

Transient suppression of the ECM1 gatekeeper is essential for HGF/c-MET-driven liver regeneration

Hepatocyte growth factor (HGF) is a multifunctional cytokine stored in the extracellular matrix as an inactive precursor and is essential for tissue repair. How HGF activity is dynamically regulated during regeneration remains unclear. Here, we identify extracellular matrix protein 1 (ECM1) as a physiological inhibitor of active HGF during liver regeneration. Following 70% partial hepatectomy, active HGF rapidly increases in parallel with a sharp decline in ECM1, and preventing this downregulation delays liver mass recovery. Mechanistically, ECM1 directly binds the active HGF -subunit through a mechanism dependent on residue R392, thereby suppressing c-MET-ERK-MYC signaling and hepatocyte proliferation. Loss of ECM1 permits activation of this pathway, whereas MYC overexpression rescues ECM1-mediated growth inhibition. In patients, proliferative hepatocytes localize to ECM1-negative regions. Supported by transcriptomic analyses and computational modeling, these findings identify ECM1 as an extracellular gatekeeper whose transient downregulation enables HGF-driven tissue repair. HighlightsO_LIECM1 is temporally downregulated during liver regeneration, while forced ECM1 expression delays liver mass recovery after 70% PHx by suppressing hepatocyte proliferation. C_LIO_LIRapid and transient ECM1 downregulation permits HGF-c-Met-ERK-MYC signaling to drive hepatocyte cell-cycle entry and expansion. C_LIO_LIECM1 directly binds the active HGF -subunit with residue R392 playing a critical role, revealing a novel extracellular mechanism for growth factor inhibition. C_LIO_LILoss of ECM1 marks proliferative hepatocytes in human liver repair, identifying ECM1 as a tunable regulator of regenerative capacity. C_LI

cell biology↗

Loss of the Y chromosome drives epigenetic and transcriptomic plasticity in lung adenocarcinoma

Loss of the Y chromosome (LOY) is associated with poor survival across multiple solid tumors, yet the underlying molecular mechanisms remain poorly understood. Here, we identify LOY as a central driver of lineage plasticity and epigenetic heterogeneity in lung adenocarcinoma. Integrating multi-omic profiling of primary samples with isogenic cellular models, we show that LOY triggers epithelial-to-mesenchymal transition (EMT). Mechanistically, LOY causes haploinsufficiency of dosage-sensitive regulators, leading to widespread DNA hypomethylation at EMT gene promoters, including THY1 and LOX. Single-cell multi-omic analyses demonstrate that LOY induces epigenetic heterogeneity, destabilizes the chromatin landscape, and increases lineage plasticity, enabling rapid cellular adaptation to metabolic and genotoxic stress. Moreover, LOY-induced plasticity facilitates tumor engraftment and metastatic dissemination in vivo. These findings establish Y-linked gene dosage as a critical guardian of epigenetic stability, providing a mechanistic rationale for how its loss amplifies phenotypic diversity and lineage plasticity, ultimately driving adverse clinical outcomes in LOY patients.

cancer biology↗

A quantitative approach to discover nonlinear signaling linking combinatorial environments with cellular responses

Cells constantly integrate diverse inputs from the extracellular environment, yet our understanding of how cells effectively process information from multiple cues at the same time remains limited. We utilized an integrated imaging platform and RNAseq analysis to investigate the combined effects of growth factors on cellular signaling and gene expression. Paired stimuli by receptor ligands revealed diverse signaling signatures-- ranging from antagonism to synergy--driving global signaling programs and gene expression. Notably, correlation networks based on signaling signatures identified vulnerabilities in cancer cells when compared to synergistic drug combinations. Profiling kinase and phosphatase activities uncovered a crucial interplay, where cellular sensitivity and phospho-turnover dynamics are modulated by input history through coordinated basal kinase and phosphatase activities. Our novel methodology sheds light on cellular processing of multiple cues, elucidating intricate mechanisms underlying cellular adaptation to extracellular environmental variations. Based on previous preprint: doi: https://doi.org/10.1101/346957

cell biology↗

msBayesImpute: A Versatile Framework for Addressing Missing Values in Biomedical Mass Spectrometry Proteomics Data

Advancements in mass spectrometry (MS) technologies have significantly improved the ability to quantify proteins and analyse their modifications. However, MS-based proteomics datasets frequently encounter missing values due to a complex interplay of missing at random (MAR) and missing not at random (MNAR) mechanisms. If unaddressed, such missing data can result in information loss and biased outcomes in data pre-processing, such as normalisation, as well as subsequent analyses and interpretations. Few approaches effectively address both MAR and MNAR, and those that do often necessitate manual tuning of mixture percentages between them or rely on two-group experimental designs. To enhance the handling of missing values, we developed msBayesImpute, an innovative computational method that integrates Bayesian factorization with probabilistic dropout models. We evaluated msBayesImpute against several popular imputation methods using both simulated missing values and those generated through a dilution series experiment on samples from lung cancer patients. Our comprehensive benchmark demonstrated superior performance in reconstructing missing values, estimating normalization factors, and identifying differentially expressed proteins across varying levels of missingness. Notably, msBayesImpute does not require predefined experimental designs and is scalable to large-scale studies. This versatility positions msBayesImpute as an effective and robust tool for enhancing the utility of MS datasets in biological research.

bioinformatics↗

Pyjacker identifies enhancer hijacking events in acute myeloid leukemia including MNX1 activation via deletion 7q

Acute myeloid leukemia with complex karyotype (ckAML) is characterized by high genomic complexity, including frequent TP53 mutations and chromothripsis. We hypothesized that the numerous genomic rearrangements could reposition active enhancers near proto-oncogenes, leading to their aberrant expression. We developed pyjacker, a computational tool for the detection of enhancer hijacking events, and applied it to a cohort of 39 ckAML samples. Pyjacker identified motor neuron and pancreas homeobox 1 (MNX1), a gene aberrantly expressed in 1.4% of AML patients, often as a result of del(7)(q22q36) associated with hijacking of a CDK6 enhancer. MNX1-activated cases show significant co-occurrence with BCOR mutations and a gene signature shared with t(7;12)(q36;p13) pediatric AML. We demonstrated that MNX1 is a dependency gene, as its knockdown in a xenograft model reduces leukemia cell fitness. In conclusion, enhancer hijacking is a frequent mechanism for oncogene activation in AML. Statement of significanceThis study examines the consequences of structural alterations and demonstrates that proto-oncogene activation by enhancer hijacking is an overlooked pathomechanism in AML. MNX1 overexpression demonstrates that deletions on chromosome 7q can not only lead to haploinsufficiency, but also to activation of oncogenes by enhancer hijacking, providing a novel leukemogenic mechanism.

cancer biology↗

Basal MET Phosphorylation is an Indicator of Hepatocyte Dysregulation in Liver Disease

Chronic liver diseases are worldwide on the rise. Due to the rapidly increasing incidence, in particular in Western countries, Non-alcoholic fatty liver disease (NAFLD) is gaining importance as the disease can develop into hepatocellular carcinoma. Lipid accumulation in hepatocytes has been identified as the characteristic structural change in NAFLD development, but molecular mechanisms responsible for disease progression remained unresolved. Here, we uncover in primary hepatocytes from a preclinical model fed with a Western diet (WD) a strong downregulation of the PI3K-AKT pathway and an upregulation of the MAPK pathway. Dynamic pathway modeling of hepatocyte growth factor (HGF) signal transduction combined with global proteomics identifies that an elevated basal MET phosphorylation rate is the main driver of altered signaling leading to increased proliferation of WD-hepatocytes. Model-adaptation to patient-derived hepatocytes reveal patient-specific variability in basal MET phosphorylation, which correlates with patient outcome after liver surgery. Thus, dysregulated basal MET phosphorylation could be an indicator for the health status of the liver and thereby inform on the risk of a patient to suffer from liver failure after surgery.

systems biology↗

Glycodelin acts as an immunomodulator in NSCLC and is a predictor of poor prognosis for patients receiving immunotherapy

Lung cancer has been shown to be targetable by novel immunotherapies which reactivate the immune system and enable tumor cell killing. However, treatment failure and resistance to these therapies is common. Consideration of sex as a factor influencing therapy resistance is still rare. We hypothesize that the success of the treatment is impaired by the presence of the immunosuppressive pregnancy-associated glycoprotein glycodelin that is expressed in patients with non-small-cell lung cancer (NSCLC). We demonstrate that the glycan pattern of NSCLC-derived glycodelin detected by a lectin-based enrichment assay highly resembles amniotic fluid-derived glycodelin A, which is known to have immunosuppressive properties. NSCLC-derived glycodelin interacts with immune cells in vitro and regulates the expression of genes associated with inflammatory and tumor microenvironment pathways. In tumor microarray samples of patients, high glycodelin staining in tumor areas results in an impaired overall survival of female patients. Moreover, glycodelin colocalizes to tumor infiltrating CD8+ T cells and pro-tumorigenic M2 macrophages. High serum concentrations of glycodelin prior to immunotherapy are associated with a poor progression-free survival (p < 0.001) of female patients receiving PD-(L)1 inhibitors. In summary, our findings suggest that glycodelin not only is a promising immunological biomarker for early identification of female patients that do not benefit from the costly immunotherapy, but also represents a promising immunotherapeutic target in NSCLC to improve therapeutic options in lung cancer. BackgroundImmunotherapy is one of the major achievements in the last decade of lung cancer treatment. However, resistance to treatment is common und not well understood. Glycodelin is an immunosuppressive protein well described during the establishment of a pregnancy. We investigated its influence on immune cells and patients receiving immunotherapy with a focus on the sex of the patients. Translational relevanceOur study examined that NSCLC-derived glycodelin shares similarities to amniotic fluid-derived glycodelin A and is predictive for a worse response to immunotherapy in female patients. Therefore, glycodelin might be a key player influencing a sex-specific response to immunotherapy in lung cancer.

cancer biology↗

Low level of antioxidant capacity biomarkers but not target overexpression predicts vulnerability to ROS-inducing drugs

Despite a strong rationale for why cancer cells are susceptible to redox-targeting drugs, such drugs often face tumor resistance or dose-limiting toxicity in preclinical and clinical studies. An important reason is the lack of specific biomarkers to better select susceptible cancer entities and stratify patients. Using a large panel of lung cancer cell lines, we identified a set of "antioxidant-capacity" biomarkers (ACB), which were tightly repressed, partly by STAT3 and STAT5A/B in sensitive cells, rendering them susceptible to multiple redox-targeting and ferroptosis-inducing drugs. Contrary to expectation, constitutively low ACB expression was not associated with an increased steady state level of reactive oxygen species (ROS) but a high level of nitric oxide, which is required to sustain high replication rates. Using ACBs, we identified cancer entities with a high percentage of patients with favorable ACB expression pattern, making it likely that more responders to ROS-inducing drugs could be stratified for clinical trials.

cancer biology↗

Pre-analytical processing of plasma and serum samples for combined proteome and metabolome analysis

Metabolomic and proteomic analyses of human plasma and serum samples harbour the power to advance our understanding of disease biology. Pre-analytical factors may contribute to variability and bias in the detection of analytes, especially when multiple labs are involved, caused by sample handling, processing time, and differing operating procedures. To better understand the impact of pre-analytical factors that are relevant to implement a unified proteomic and metabolomic approach in a clinical setting, we assessed the influence of temperature, sitting times, and centrifugation speed on the plasma and serum metabolomes and proteomes from six healthy volunteers. We used targeted metabolic profiling (497 metabolites) and data-independent acquisition (DIA) proteomics (572 proteins) on the same samples generated with well-defined pre-analytical conditions to evaluate criteria for pre-analytical SOPs for plasma and serum samples. Time and temperature showed the strongest influence on the integrity of plasma and serum proteome and metabolome. While rapid handling and low temperatures (4{degrees}C) are imperative for metabolic profiling, the analysed proteome showed variability when exposed to temperatures of 4{degrees}C for more than 2 hours, highlighting the need for compromises in a combined analysis. We formalised a quality control scoring system to objectively rate sample stability and tested this score using external data sets from other pre-analytical studies. Stringent and harmonised standard operating procedures (SOPs) are required for pre-analytical sample handling when combining proteomics and metabolomics of clinical samples to yield robust and interpretable data on a longitudinal scale and across different clinics. To ensure an adequate level of practicability in a clinical routine for metabolomics and proteomics studies we suggest to keep blood samples up to 2 hours on ice (4{degrees}C) prior to snap-freezing as a compromise between stability and operability. Finally, we provide the methodology as an open source R package allowing the systematic scoring of proteomics and metabolomics datasets to assess the stability of plasma and serum samples.

biochemistry↗

Cell-to-cell variability in JAK2/STAT5 pathway components and cytoplasmic volumes define survival threshold in erythroid progenitor cells

Survival or apoptosis is a binary decision in individual cells. Yet, at the cell population level, a graded increase in survival of CFU-E cells is observed upon stimulation with Erythropoietin (Epo). To identify components of JAK2/STAT5 signal transduction that contribute to the graded population response, a cell population-level model calibrated with experimental data was extended to study the behavior in single cells. The single-cell model showed that the high cell-to-cell variability in nuclear phosphorylated STAT5 is caused by variability in the amount of EpoR:JAK2 complexes and of SHP1 as well as the extent of nuclear import due to the large variance in the cytoplasmic volume of CFU-E cells. 24 to 118 pSTAT5 molecules in the nucleus for 120 min are sufficient to ensure cell survival. Thus, variability in membrane-associated processes are responsible to convert a switch-like behavior at the single-cell level to a graded population level response. HighlightsO_LIMathematical modeling enables integration of heterogeneous data C_LIO_LISingle-cell modeling captures binary decision process C_LIO_LIMultiple sources of cell-to-cell variability in erythroid progenitor cells C_LIO_LIMinimal amount of active STAT5 sufficient for survival of erythroid progenitor cells C_LI

systems biology↗

A combinatorial extracellular code tunes the intracellular signaling network activity to distinct cellular responses

Cells constantly survey a complex set of inputs that is processed by the intracellular signaling network, but little is known of how cells integrate input information from more than one cue. We employed a FRET biosensor-based imaging platform to study the effect of combinatorial growth factor levels on the signaling network in human cells. We found that pairwise stimuli caused distinct concentration- and ratio-dependent signaling states through signaling signatures such as antagonism, additivity and synergy. The unique signaling states correlated with differential gene expression and non-additive transcription patterns. We further elucidated how a signal-rich environment can fine-tune the signaling network and adjust physiological outcomes, by kinase and phosphatase activity profiling. We describe how complex extracellular conditions affect phospho-turnover and the basal phosphorylation status. Thus, we provide mechanistic insights into cellular processing of multiple cues and explain part of the complexity of cellular adaptation to changes in the extracellular environment.

cell biology↗