Biology subjects

Wess, M.

Publications and source records attributed to Wess, M..

7 recordsLinked to original sources

bioRxiv2026

Fibroblast-derived Collagen VI shapes the structure and function of the tumor-immune microenvironment in clear cell renal cell carcinoma

The importance of the extracellular matrix (ECM) influencing tumor biology in stroma-rich tumors is well established. However, the relevance of individual ECM proteins in rather stroma-poor cancers such as clear cell renal cell carcinoma (ccRCC) is ill-defined. Using bulk proteomics, spatial imaging, and single-cell transcriptomics, we identify collagen VI (COL6) as a predominant ECM component of the ccRCC interstitial stroma, synthesized primarily by fibroblasts and pericytes. Using cell-derived matrix (CDM) models, we demonstrate that COL6 is essential for maintaining an isotropic ECM network architecture and governs the broader matrisomal composition, with direct pro-proliferative consequences for tumor cells both in vitro and in situ. Granular spatial analysis reveals that COL6-rich stromal septa constrain tumor-infiltrating T cells to boundary zones, where CD8+PD1+ phenotypes predominate. Importantly, tyrosine kinase inhibition (TKI) with cabozantinib suppresses COL6 expression in fibroblasts in vitro and in ex vivo tumor models, mirroring COL6-depleted CDM phenotypes. Our findings establish COL6 as a central stromal regulator of ccRCC tumor biology and immune contexture, revealing ECM remodeling as an underappreciated mechanism of TKI action, with implications for combination immunotherapy strategies.

cancer biology↗

bioRxiv2026

Integrated multi-omics profiling uncovers the epigenetic, transcriptional, and metabolic landscape of prostate cancer progression

A comprehensive understanding of the underlying molecular mechanisms of prostate cancer is essential for the development of precise diagnostic biomarkers. In this study, we applied unsupervised multi-omics factor analysis (MOFA) to integrate DNA methylation, gene expression, and metabolic profiles derived from the same individuals, aiming to characterize the biological landscape of normal, malignant, and aggressive prostate tissue. Our analysis identified distinct molecular pathways associated with aggressive disease, specifically those involved in zinc metabolism, cell cycle regulation, smooth muscle architecture, immune activation, and tissue morphology. Key metabolites within the TCA cycle, amino acid metabolism, and lipid pathways were central to these signatures. Furthermore, we observed a consistent co-enrichment of SP1 and CTCFL binding regions among factor-associated CpGs, suggesting a model of global epigenetic reprogramming. These findings indicate a novel interplay between Polycomb deregulation, CTCFL-mediated chromatin remodeling, and SP1-driven transcriptional activation in shaping the prostate cancer epigenome. Apart from immune activation, the identified molecular signatures were validated in the TCGA cohort and demonstrated significant predictive value for disease recurrence. Overall, these results underscore the power of multi-omics integration in providing a holistic understanding of prostate cancer biology and its potential for clinical translation into prognostic biomarkers.

cancer biology↗

bioRxiv2024

Spatial Integration of Multi-Omics Data using the novel Multi-Omics Imaging Integration Toolset

To truly understand the cancer biology of heterogenous tumors in the context of precision medicine, it is crucial to use analytical methodology capable of capturing the complexities of multiple omics levels, as well as the spatial heterogeneity of cancer tissue. Different molecular imaging techniques, such as mass spectrometry imaging (MSI) and spatial transcriptomics (ST) achieve this goal by spatially detecting metabolites and mRNA, respectively. To take full analytical advantage of such multi-omics data, the individual measurements need to be integrated into one dataset. We present MIIT (Multi-Omics Imaging Integration Toolset), a Python framework for integrating spatially resolved multi-omics data. MIITs integration workflow consists of performing a grid projection of spatial omics data, registration of stained serial sections, and mapping of MSI-pixels to the spot resolution of Visium 10x ST data. For the registration of serial sections, we designed GreedyFHist, a registration algorithm based on the Greedy registration tool. We validated GreedyFHist on a dataset of 245 pairs of serial sections and reported an improved registration performance compared to a similar registration algorithm. As a proof of concept, we used MIIT to integrate ST and MSI data on cancer-free tissue from 7 prostate cancer patients and assessed the spot-wise correlation of a gene signature activity for citrate-spermine secretion derived from ST with citrate, spermine, and zinc levels obtained by MSI. We confirmed a significant correlation between gene signature activity and all three metabolites. To conclude, we developed a highly accurate, customizable, computational framework for integrating spatial omics technologies and for registration of serial tissue sections.

bioinformatics↗

bioRxiv2024

Versatile roles of Annexin A4 in ccRCC: impact on membrane repair, transcriptional signatures, and composition of the tumor microenvironment

Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal malignant disease and is characterized by dismal prognosis in the metastasized setting. Invasive growth of cancer cells relates to high levels of compressive forces translating to relevant damage of the plasma membrane. However, functional implications of protein machineries required for plasma membrane repair in ccRCC are not yet completely elucidated. Given the membrane-associated localization of the large family of annexin proteins, we aimed for a global annotation of annexin proteins, which led to the identification of ANXA4 selectively expressed in cancer cells of ccRCC. Interestingly, ANXA4 showed context-dependent distinct localization patterns including the plasma membrane as well as the nuclear compartment/nuclear membrane. We investigated the functional role of ANXA4 in ccRCC employing genetic titration studies (knockdown, CRISPR/Cas9 knockout and overexpression) and identified impaired acute plasma membrane repair as well as invasive capability in conditions of reduced ANXA4 expression. Utilizing computational segmentation of the tumor microenvironment (TME) of ccRCC samples revealed that ANXA4 low tumors exhibited a distinct TME composition compared to ANXA4 high cases. ANXA4 low tumors showed higher levels of tumor infiltrating lymphocytes accompanied by increased deposition of acellular extracellular matrix. Further transcriptomic analysis demonstrated major alterations in transcriptional signatures related to epithelial-mesenchymal transition (EMT) and immune signaling. Transcription factor enrichment analysis and further functional validation identified ELF3 as one central regulator of invasive properties. Our integrative approach including molecular analyses with advanced histopathological segmentation uncovered novel roles for ANXA4 in modulating acute membrane repair, transcriptional regulation, and shaping cellular composition of the ccRCC tumor microenvironment.

cancer biology↗

bioRxiv2024

Deep phenotyping of the prostate tumor microenvironment reveals molecular stratifiers of relapse and links inflammatory chemokine expression to aberrant metabolism

Understanding the molecular characteristics and changes of the tumor microenvironment (TME) associated with aggressive prostate cancer (PCa) is essential for precise diagnosis and treatment. We interrogated spatially resolved integrated transcriptomics and metabolomics data to build molecular strafiers discriminating patients with aggressive, potentially relapsing, and metastasizing PCa. We report a relapse associated (RA) gene expression signature characterized by upregulated immune response related gene expression scoring high in cancer, stroma, and glandular tissue of relapsing patients. Further, we identified a signature specific to a distinct sub-group of morphologically non-cancerous glands in prostate tissue from patients with relapsing cancer. This signature, named chemokine-enriched-gland (CEG) signature, was characterized by upregulated gene expression of pro-inflammatory chemokines. Glands with a high CEG score were enriched for club-like cells and surrounding stroma was infiltrated by immune cells. Tissue regions scoring high for both CEG and RA signatures were associated with reduced levels of citrate and zinc and loss of normal prostate secretory gland functions via reduced expression of genes necessary for citrate secretion. In summary we report that aggressive PCa is associated with an increased inflammatory status linked to chemokine production and club-like cell enrichment in potentially pre-cancerous prostate glands displaying an aberrant metabolism.

cancer biology↗

bioRxiv2024

Androgen deprivation therapy-resistant club cells are linked to myeloid cell-driven immunosuppression in the prostate tumor microenvironment

Prostate cancer treatment resistance is a significant challenge facing the field. Genomic and transcriptomic profiling have partially elucidated the mechanisms through which cancer cells escape treatment, but their relation toward the tumor microenvironment (TME) remains elusive. Here we present a comprehensive transcriptomic landscape of the prostate TME at multiple points in the standard treatment timeline employing single-cell RNA-sequencing and spatial transcriptomics data from 110 patients. We identify club-like cells as a key epithelial cell subtype that acts as an interface between the prostate and the immune system. Tissue areas enriched with club-like cells have depleted androgen signaling and upregulated expression of luminal progenitor cell markers. Club-like cells display a senescence-associated secretory phenotype and their presence is linked to increased polymorphonuclear myeloid-derived suppressor cell (PMN-MDSC) activity. Our results indicate that club-like cells partake in inducing myeloid inflammation previously associated with androgen deprivation therapy resistance, providing a rationale for their therapeutic targeting.

cancer biology↗

bioRxiv2018

Optogenetic control shows that kinetic proofreading regulates the activity of the T cell receptor

The pivotal task of the immune system is to distinguish between self and foreign antigens. The kinetic proofreading model (KPR) proposes that T cells discriminate self from foreign ligands by the different ligand binding half-lives to the T cell receptor (TCR). It is challenging to test KPR as the available experimental systems fall short of only altering the binding half-lives and keeping other parameters of the ligand-TCR interaction unchanged. We engineered an optogenetic system using the plant photoreceptor phytochrome B to selectively control the dynamics of ligand binding to the TCR by light. Combining experiments with mathematical modeling we find that the ligand-TCR interaction half-life is the decisive factor for activating downstream TCR signaling, substantiating the KPR hypothesis.\n\nOne Sentence SummaryThe half-life of the ligand-T cell receptor complex determines T cell activation.

immunology↗