Biology subjects

Schneider, M. A.

Publications and source records attributed to Schneider, M. A..

14 recordsLinked to original sources

bioRxiv2026

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↗

bioRxiv2025

MetAlyzer to Perform Streamlined, Interactive, and Pathway-Mapping Analysis of Targeted Metabolomics Data from the biocrates Platform

Mass spectrometry (MS)-based metabolomics has emerged as a powerful tool to address multifaceted biological questions. Commercial solutions like the ones developed at biocrates allow reliable and quantitative targeted metabolic profiling, including the conversion of the raw MS spectra into absolute concentrations of metabolites. These results can be exported for further analysis under several formats with varying levels of human-vs. machine-readability. The default output format is an Excel spreadsheet that favours human readability and therefore requires extra preparation steps for downstream bioinformatic analysis and data exploration. To streamline this next step for users of this platform, we developed MetAlyzer, an R package (https://github.com/Lu-Group-UKHD/MetAlyzer) specifically designed to handle the spreadsheets generated by WebIDQ, the biocrates workflow manager software. MetAlyzer converts WebIDQ-generated spreadsheets into flexible SummarizedExperiment objects and provides functions for data preprocessing, statistical testing, and visualization of differential metabolites. To further support data exploration and hypothesis generation by users without coding experience, we also developed an interactive and intuitive Shiny app (https://metalyzer.shinyapps.io/MetAlyzer_ShinyApp/) that interfaces with MetAlyzers core functionality, enabling users to execute the complete analysis workflow without writing code. This combination can help scientists deepen their understanding of metabolomics results, supporting the broader adoption of metabolomics in the life sciences community.

bioinformatics↗

bioRxiv2025

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↗

bioRxiv2025

Obesity promotes conserved inflammatory and metabolic transcriptional programs in mouse and human colon tumors

BackgroundThe global prevalence of obesity, an established risk and progression factor for colon cancer, is high and rising. Unfortunately, the mechanisms underlying the obesity-colon cancer association are incompletely understood, and new molecular targets enabling more effective intervention strategies to break the obesity-colon cancer link are urgently needed. ObjectiveThis study integrated RNA sequencing data from mouse and human colon tumor samples, as well as human adipose samples, to rigorously establish obesity-associated transcriptomic signatures conserved between the two species. MethodsWe employed a mouse colon cancer model with colonoscopy-guided orthotopic transplantation of syngeneic Apc-null;KrasG12D/+;Trp53-null;Smad4-null;tdTomato colon tumor organoids. Epithelial cell adhesion molecule (EpCAM)-positive cells from murine tumors, and 193 human colon tumors and 188 human mesenteric adipose tissue samples from the ColoCare cohort underwent transcriptomic analyses. ResultsDiet-induced obesity reduced survival in the mouse model of colon cancer. Integrated transcriptomic analyses of EpCAM-positive murine tumor cells and bulk human tumors revealed obesity-driven enrichment of inflammation and metabolic pathways, including upregulation of genes involved in innate immune sensing (TLR2, MYD88, IRF4) and tumor microenvironment remodeling (MMP9, TGFB1, SERPINE1). Analysis of paired mesenteric visceral adipose tissue and tumor samples from the ColoCare cohort indicated that obesity amplifies inflammatory signaling pathways through unique adipose ligand-tumor receptor interactions. ConclusionsThese results establish obesity-associated adipose tissue dysregulation as a key inter-tissue modulator of biology, with concordant cross-species effects on tumor cell-intrinsic inflammatory and metabolic programs.

cancer biology↗

bioRxiv2024

Epitranscriptomic rRNA fingerprinting reveals tissue-of-origin and tumor-specific signatures

Mammalian ribosomal RNA (rRNA) molecules are highly abundant RNAs, decorated with over 220 rRNA modifications. Previous works have shown that some rRNA modification types can be dynamically regulated; however, how and when the mammalian rRNA modification landscape is remodeled remains largely unexplored. Here, we employ direct RNA nanopore sequencing to chart the human and mouse rRNA epitranscriptome across tissues, developmental stages, cell types and disease. Our analyses reveal multiple rRNA sites that are differentially modified in a tissue- and/or developmental stage-specific manner, including previously unannotated modified sites. We demonstrate that rRNA modification patterns can be used for tissue and cell type identification, which we hereby term epitranscriptomic fingerprinting. We then explore rRNA modification patterns in normal-tumor matched samples from lung cancer patients, finding that epitranscriptomic fingerprinting accurately classifies clinical samples into normal and tumor groups from only 250 reads per sample, demonstrating the potential of rRNA modifications as diagnostic biomarkers.

molecular biology↗

bioRxiv2023

A single-sample workflow for joint metabolomic and proteomic analysis of clinical specimens

Understanding the interplay of the proteome and the metabolome aids in understanding cellular phenotypes. To enable more robust inferences from such multi-omics analyses, combining proteomic and metabolomic datasets from the same sample provides major benefits by reducing technical variation between extracts during the pre-analytical phase, decreasing sample variation due to varying cellular content between aliquots, and limiting the required sample amount. We evaluated the advantages, practicality and feasibility of a single-sample workflow for combined proteome and metabolome analysis. In the workflow, termed MTBE-SP3, we combined a fully automated protein lysis and extraction protocol (autoSP3) with a semi-automated biphasic 75% EtOH/MTBE extraction for quantification of polar/non-polar metabolites. Additionally, we compared the resulting proteome of various biological matrices (FFPE tissue, fresh-frozen tissue, plasma, serum and cells) between autoSP3 and MTBE-SP3. Our analysis revealed that the single-sample workflow provided similar results to those obtained from autoSP3 alone, with an 85-98% overlap of proteins detected across the different biological matrices. Additionally, it provides distinct advantages by decreasing (tissue) heterogeneity by retrieving metabolomics and proteomic data from the identical biological material, and limiting the total amount of required material. Lastly, we applied MTBE-SP3 to a lung adenocarcinoma cohort of 10 patients. Integrating the metabolic and proteomic alterations between tumour and non-tumour adjacent tissue yielded consistent data independent of the method used. This revealed mitochondrial dysfunction in tumor tissue through deregulation of OGDH, SDH family enzymes and PKM. In summary, MTBE-SP3 enables the facile and confident parallel measurement of proteins and metabolites obtained from the same sample. This workflow is particularly applicable for studies with limited sample availability and offers the potential to enhance the integration of metabolomic and proteomic datasets.

cancer biology↗

bioRxiv2023

Cancer-associated fibroblasts promote drug resistance in ALK-driven lung adenocarcinoma cells by upregulating lipid biosynthesis

Targeted therapy interventions using tyrosine kinase inhibitors (TKIs) provide encouraging treatment responses in ALK-rearranged lung adenocarcinomas, yet resistances occur almost inevitably. Apart from tumor cell-intrinsic resistance mechanisms, accumulating evidence supports a role of cancer-associated fibroblasts (CAFs) in affecting the therapeutic vulnerability of lung cancer cells. Here, we aimed to investigate underlying molecular networks shaping the therapeutic susceptibility of ALK-driven lung adenocarcinoma cells via tumor microenvironmental cues using three-dimensional (3D) spheroid co-culture settings. We show that CAFs promote therapy resistance of lung tumor cells against ALK inhibition by reducing apoptotic cell death and increasing cell proliferation. Using single-cell RNA-sequencing analysis, we show that genes involved in lipogenesis constitute the major transcriptional difference between TKI-treated homo- and heterotypic lung tumor spheroids. CAF-conditioned medium and CAF-secreted factors HGF and NRG1 were both able to promote resistance of 3D-cultured ALK-rearranged lung tumor cells via AKT signaling, which was accompanied by enhanced de novo lipogenesis and supression of lipid peroxidation. Notably, simultaneous targeting of ALK and SREBP-1 was able to overcome the established CAF-driven lipid metabolic-supportive niche of TKI-resistant lung tumor spheroids. Our findings highlight a crucial role of CAFs in mediating ALK-TKI resistance via lipid metabolic reprogramming and suggest new ways to overcome resistance towards molecular directed drugs by targeting vulnerabilities downstream of oncogenic signaling.

cancer biology↗

bioRxiv2023

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↗

bioRxiv2022

High-resolution epigenetic profiling identifies novel regulators of COPD in human lung fibroblasts

Patients with chronic obstructive pulmonary disease (COPD) are still waiting for curative treatments. Considering the environmental cause of COPD (e.g., cigarette smoke) and disease phenotypes, including stem-cell senescence and impaired differentiation, we hypothesized that COPD will be associated with altered epigenetic signaling in lung cells. We generated genome-wide DNA methylation maps at single CpG resolution of primary human lung fibroblasts (HLFs) isolated from distal parenchyma of ex-smoker controls and COPD patients, with both mild and severe disease. The epigenetic landscape is markedly changed in lung fibroblasts across COPD stages, with DNA methylation changes occurring predominantly in regulatory regions, including promoters and enhancers. RNA sequencing of matched fibroblasts demonstrated dysregulation of genes involved in proliferation, DNA repair, and extracellular matrix organization. Notably, we identified epigenetic and transcriptional dysregulation already in mild COPD patients, providing unique insights into early disease. Integration of profiling data identified 110 candidate regulators of disease phenotypes, including epigenetic factors. Using phenotypic screens, we verified the regulator capacity of multiple candidates and linked them to repair processes in the human lung. Our study provides first integrative high-resolution epigenetic and transcriptomic maps of human lung fibroblasts across stages of COPD. We reveal novel transcriptomic and epigenetic signatures associated with COPD onset and progression and identify new candidate regulators involved in the pathogenesis of chronic respiratory diseases. The presence of various epigenetic factors among the candidates demonstrates that epigenetic regulation in COPD is an exciting research field that holds promise for novel therapeutic avenues for patients.

cell biology↗

bioRxiv2022

Profibrotic priming of airway cell types and drug responses in early-stage idiopathic pulmonary fibrosis

Early genetic studies hinted the role of airway epithelial cells in the development of idiopathic pulmonary fibrosis (IPF), while recent single-cell RNA sequencing (scRNA-seq) atlases utilized explant IPF lungs and therefore represent late-stage disease. Here, we used air liquid interface (ALI) cultures of primary cells taken from the subsegmental bronchi of newly diagnosed IPF patients, reflecting early-stage fibrosis, to interrogate the transcriptional landscape of the airway mucosa. Profiling of 129,986 cells identified a shared proinflammatory state in epithelial cells and an early activation state of fibroblasts. Moreover, IPF basal cells initiated awry repair mechanisms and primed the airway mucosa for TGF-{beta} activation. Treatment with nintedanib, pirfenidone, both established antifibrotic drugs, and saracatinib, an Src kinase inhibitor that can limit IPF progression, only significantly affected certain IPF signatures. This study provides insight into the early disease mechanisms of IPF and may serve as a resource to further investigate pharmacological inhibition effects.

molecular biology↗

bioRxiv2022

Quantitative imaging reveals PI3Kδ inhibition reduces rhinovirus-induced damage of small airway epithelia in ex vivo cultured human precision cut lung slices from COPD patients

Chronic obstructive pulmonary disease (COPD) is one of the major causes of disability and death worldwide and a significant risk factor for respiratory infections. Rhinoviral infections are the most common trigger of COPD exacerbations which lead to a worsening of disease symptoms, decline in lung function and increased mortality. The lack of suitable disease models to study the relevant cellular and molecular mechanism hinders the discovery of novel medicines that prevent disease progression in exacerbating COPD patients. We used quantitative multi-color imaging of COPD and control patient derived human precision-cut lung slices (hPCLS) to study the impact of rhinovirus infection on the structure and function of the small airway epithelium. Data analysis highlighted that COPD-derived hPCLS have a higher cellular density and basal cell hyperplasia, more unciliated airway surface areas with mucus overproduction, and shorter cilia length compared to control hPCLS. In response to rhinovirus 16 infection, COPD-derived hPCLS secreted higher amounts of pro-inflammatory cytokines and displayed decreased epithelial integrity and reduced airway ciliation. Finally, treatment with a selective PI3K{delta} inhibitor reduced secretion of rhinovirus-induced cytokines and ameliorated rhinovirus-induced damage to COPD small airway epithelia. Thus, these data demonstrate the potential of quantitative imaging to assess complex airway functions in a patient-derived lung tissue model system, and indicate that targeting PI3K{delta} might be a promising therapeutic opportunity to limit rhinovirus-induced airway damage in exacerbating COPD patients. SummaryPI3K{delta} inhibition reduces rhinovirus-mediated damage of small airway epithelia from chronic obstructive pulmonary disease (COPD) patients

pathology↗

bioRxiv2021

Intratumoural heterogeneity and immune modulation in lung adenocarcinoma of female smokers and never smokers

Lung cancer is still the leading cause of cancer death worldwide despite declining smoking prevalence in industrialised countries. Although lung cancer is highly associated with smoking status, a significant proportion of lung cancer cases develop in patients who never smoked, with an observable bias towards female never smokers. A better understanding of lung cancer heterogeneity and immune system involvement during tumour evolution and progression in never smokers is therefore highly warranted. We employed single nucleus transcriptomics of surgical lung adenocarcinoma (LADC) and normal lung tissue samples from patients with or without smoking history. Immune cells as well as fibroblasts and endothelial cells respond to tobacco smoke exposure by inducing a highly inflammatory state in normal lung tissue. In the presence of LADC, we identified differentially expressed transcriptional programmes in macrophages and cancer-associated fibroblasts, providing insight into how the niche favours tumour progression. Within tumours, we distinguished eight subpopulations of neoplastic cells in female smokers and never smokers. Through pseudotemporal ordering, we inferred a trajectory towards two differentiated tumour cell states implicated in cancer progression and invasiveness. A proliferating cell population sustaining tumour growth exhibits differential immune modulating signatures in both patient groups. Our results resolve cellular heterogeneity and immune interactions in LADC, with a special emphasis on female never smokers and implications for the design of therapeutic approaches.

cancer biology↗

bioRxiv2020

SARS-CoV-2 receptor ACE2 and TMPRSS2 are predominantly expressed in a transient secretory cell type in subsegmental bronchial branches

The SARS-CoV-2 pandemic affecting the human respiratory system severely challenges public health and urgently demands for increasing our understanding of COVID-19 pathogenesis, especially host factors facilitating virus infection and replication. SARS-CoV-2 was reported to enter cells via binding to ACE2, followed by its priming by TMPRSS2. Here, we investigate ACE2 and TMPRSS2 expression levels and their distribution across cell types in lung tissue (twelve donors, 39,778 cells) and in cells derived from subsegmental bronchial branches (four donors, 17,521 cells) by single nuclei and single cell RNA sequencing, respectively. While TMPRSS2 is expressed in both tissues, in the subsegmental bronchial branches ACE2 is predominantly expressed in a transient secretory cell type. Interestingly, these transiently differentiating cells show an enrichment for pathways related to RHO GTPase function and viral processes suggesting increased vulnerability for SARS-CoV-2 infection. Our data provide a rich resource for future investigations of COVID-19 infection and pathogenesis.

genomics↗

bioRxiv2017

Resolving Drug Effects In Patient-Derived Cancer Cells Links Organoid Responses To Genome Alterations

Cancer drug screening in patient-derived cells holds great promise for personalized oncology and drug discovery but lacks standardization. Whether cells are cultured as conventional monolayer or advanced organoid cultures influences drug effects and thereby drug selection and clinical success. To precisely compare drug profiles in differently cultured primary cells, we developed DeathPro, an automated microscopy-based assay to resolve drug-induced cell death and proliferation inhibition. Using DeathPro, we screened cells from ovarian cancer patients in monolayer or organoid culture with clinically relevant drugs. Drug-induced growth arrest and efficacy of cytostatic drugs differed between the two culture systems. Interestingly, drug effects in organoids were more diverse and had lower therapeutic potential. Genomic analysis revealed novel links between drug sensitivity and DNA repair deficiency in organoids that were undetectable in monolayers. Thus, our results highlight the dependency of cytostatic drugs and pharmacogenomic associations on culture systems, and guide culture selection for drug tests.

cancer biology↗