Biology subjects

Schroeder, B.

Publications and source records attributed to Schroeder, B..

7 recordsLinked to original sources

bioRxiv2026

Tumor-hepatocyte crosstalk drives a hepatic lactate-TGF-β axis of CD8⁺ T cell exhaustion and immunotherapy resistance in small-cell lung cancer liver metastases

PurposeLiver metastases confer poor outcomes and attenuate the benefit of immunotherapy across solid tumors. This study investigated how the hepatic metastatic niche promotes CD8 T cell dysfunction and immunotherapy resistance in small-cell lung cancer (SCLC). Experimental DesignClinical outcomes and tumor gene expression were integrated with multi-region single-cell RNA sequencing of T cells from rapid-autopsy SCLC metastases, together with spatial transcriptomics. SCLC-hepatocyte conditioned-media models were combined with stable-isotope tracing, mass spectrometry, functional and metabolic assays, and ChIP-qPCR to define mechanisms of CD8 T cell suppression. ResultsLiver metastases were associated with inferior survival and reduced benefit from immune checkpoint blockade. Multi-region single-cell analysis showed that CD8 T cells from liver metastases exhibited an exhaustion-associated state enriched for hypoxia, lactate, and TGF-{beta} programs. SCLC-hepatocyte crosstalk generated a lactate- and TGF-{beta}-rich microenvironment that reduced CD8 T cell effector function, proximal T cell receptor signaling, glycolytic fitness, viability, and proliferation. Stable-isotope tracing demonstrated transfer and accumulation of co-culture-derived lactate in recipient CD8 T cells, with limited entry into downstream pyruvate-linked pathways. Lactate accumulation was accompanied by increased H3K18 lactylation at the PDCD1, LAG3, and TGFB1 regulatory loci. In parallel, SCLC-hepatocyte crosstalk increased paracrine TGF-{beta} and activated canonical SMAD2 signaling in CD8 T cells. TGF-{beta} receptor inhibition restored CD8 T cell proliferation. In the phase III IMpower133 cohort, a combined lactate-TGF-{beta} transcriptional program was associated with inferior survival, most strongly in patients with liver metastases. ConclusionsTumor-hepatocyte crosstalk generates convergent lactate and TGF-{beta} signals that drive CD8 T cell dysfunction in liver metastases. This hepatic immune-metabolic circuit provides a potential mechanism for immunotherapy resistance and supports therapeutic strategies targeting TGF-{beta} signaling in liver-metastatic SCLC. Translational RelevancePatients with SCLC liver metastases have poor outcomes and derive limited benefit from immune checkpoint blockade, but actionable mechanisms of hepatic immune resistance remain undefined. We identify an immune-metabolic circuit in which SCLC-hepatocyte crosstalk generate lactate and TGF-{beta} signals that converge on CD8 T cells. Stable-isotope tracing demonstrates the transfer and accumulation of tumor-hepatocyte-derived lactate in recipient T cells, which causes H3K18 lactylation at exhaustion- and TGFB1-associated loci. In parallel, paracrine TGF-{beta} activates canonical SMAD signaling and reinforces proliferative dysfunction. TGF-{beta} receptor inhibition restores CD8 T cell proliferation. In the phase III IMpower133 cohort, a combined lactate-TGF-{beta} program is associated with inferior survival, particularly among patients with liver metastases. These findings provide a mechanistic and biomarker framework for testing TGF-{beta}-directed strategies in liver-metastatic SCLC, a population with substantial unmet clinical need.

cancer biology↗

bioRxiv2025

Different dispersal rates and declining climate suitability shape future vegetation compositions across the Arctic: implications for the boreal forest - tundra boundary

AimWe investigate how species-specific dispersal abilities might influence future Arctic plant distributions and large-scale dynamics at the boreal forest - tundra boundary until 2100 Locationcircumpolar terrestrial Arctic (boreal forest, taiga and tundra) Taxon1,550 plant species MethodsWe developed climate-driven species distribution models (SDM) to predict species-specific emerging climate niches under different climate scenarios. The model was parameterized using occurrence data from the Global Biodiversity Information Facility database (GBIF) and temperature and bioclimatic variables from the CHELSA data set. Dispersal rates were assigned to each species using a trait-based approach and were used to predict future habitat with a distance-based probability over time. ResultsPlant species are predicted to occupy on average only 12.3% (1.5 - 53.9 95% CI) of their emerging climate niches, with half of the species unable to colonize new habitat by 2100 due to limited dispersal distances. In dispersal limited predictions migration to higher altitudes played a greater role than northward shifts. Decolonization by species (extirpation) due to decreasing climate suitability had a larger effect on species composition change compared to dispersal limitations. Boreal tree species were predicted to expand into the tundra shrinking the treeless areas. Main conclusionsFuture plant species distributions and resulting large-scale compositions are affected by species-specific dispersal rates. Even though new suitable niches emerge prominently towards the north, higher altitudes might be more relevant given their accessibility by dispersal over the next century. Although climate niche dynamics could support higher plant species richness across the Arctic, overall richness is expected to decline with climate warming due to dispersal limitations. The colonization of new habitats via dispersal in combination with the decolonization of former habitats due to declining climatic suitability on species level are predicted to cause large-scale changes in species composition, especially at the boundary between the boreal forest and the tundra biome.

ecology↗

bioRxiv2024

Metastatic organotropism in small cell lung cancer

Metastasis is the leading cause of cancer-related deaths, yet its regulatory mechanisms are not fully understood. Small-cell lung cancer (SCLC) is the most metastatic form of lung cancer, with most patients presenting with widespread disease, making it an ideal model for studying metastasis. However, the lack of suitable preclinical models has limited such studies. We utilized rapid autopsy-derived tumors to develop xenograft models that mimic key features of SCLC, including histopathology, rapid and widespread development of metastasis to the liver, brain, adrenal, bone marrow, and kidneys within weeks, and response to chemotherapy. By integrating in vivo lineage selection with comprehensive bulk and single cell multiomic profiling of transcriptomes and chromatin accessibility, we identified critical cellular programs driving metastatic organotropism to the liver and brain, the most common sites of SCLC metastasis. Our findings reveal the key role of nuclear-cytoskeletal interactions in SCLC liver metastasis. Specifically, the loss of the nuclear envelope protein lamin A/C, encoded by the LMNA gene, increased nuclear deformability and significantly increased the incidence of liver metastasis. Human liver metastases exhibited reduced LMNA expression compared to other metastatic sites, correlating with poorer patient outcomes and increased mortality. This study introduces novel preclinical models for SCLC metastasis and highlights pathways critical for organ-specific metastasis, offering new avenues for the development of targeted therapies to prevent or treat metastatic disease.

cancer biology↗

bioRxiv2024

Microenvironment Shapes Cell State, Plasticity, and Heterogeneity of Small Cell Lung Cancer

Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intra-tumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the drivers of SCLC plasticity are poorly understood. To map the landscape of SCLC tumor microenvironment (TME), we apply spatially resolved transcriptomics and quantitative mass spectrometry-based proteomics to metastatic SCLC tumors obtained via rapid autopsy. The phenotype and overall composition of non-malignant cells in the tumor microenvironment (TME) exhibits substantial variability, closely mirroring the tumor phenotype, suggesting TME-driven reprogramming of NE cell states. We identify cancer-associated fibroblasts (CAF) as a crucial element of SCLC TME heterogeneity, contributing to immune exclusion, and predicting exceptionally poor prognosis. Together, our work provides a comprehensive map of SCLC tumor and TME ecosystems, emphasizing their pivotal role in SCLCs adaptable nature, opening possibilities for re-programming the intercellular communications that shape SCLC tumor states.

cancer biology↗

bioRxiv2022

Autophagy controls mucus secretion from intestinal goblet cells by alleviating ER stress

Colonic goblet cells are specialized epithelial cells that secrete mucus to form a barrier between the host and its microbiota, thus preventing bacterial invasion and inflammation. How goblet cells control the amount of mucus they secrete is unclear. We found that constitutive activation of autophagy in mice via Beclin 1 led to production of a thicker and less penetrable mucus layer by reducing endoplasmic reticulum (ER) stress. Accordingly, inhibiting Beclin 1-induced autophagy via Bcl-2 impaired mucus secretion. Furthermore, alleviating intestinal ER stress with a bile acid, or activating the unfolded protein response (UPR) pharmacologically via eIF2 phosphorylation, led to excessive mucus production. Over-production of mucus altered the gut microbiome, with expansion of mucus-utilizing bacteria, and protected from intestinal inflammation. Thus, ER stress is a cell-intrinsic switch that limits mucus secretion, while autophagy maintains proper mucus secretion and intestinal homeostasis by relieving ER stress.

immunology↗

bioRxiv2020

Automated Segmentation of Fractured Distal Radii by 3D Geodesic Active Contouring of in vivo HR-pQCT Images

Radius fractures are among the most common fracture types; however, there is limited consensus on the standard of care. A better understanding of the fracture healing process could help to shape future treatment protocols and thus improve functional outcomes of patients. High-resolution peripheral quantitative computed tomography (HR-pQCT) allows monitoring and evaluation of the radius on the micro-structural level, which is crucial to our understanding of fracture healing. However, current radius fracture studies using HR-pQCT are limited by the lack of automated contouring routines, hence only including small number of patients due to the prohibitively time-consuming task of manually contouring HR-pQCT images. In the present study, a new method to automatically contour images of distal radius fractures based on 3D morphological geodesic active contours (3D-GAC) is presented. Contours of 60 HR-pQCT images of fractured and conservatively treated radii spanning the healing process up to one year post-fracture are compared to the current gold standard, hand-drawn 2D contours, to assess the accuracy of the algorithm. Furthermore, robustness was established by applying the algorithm to HR-pQCT images of intact radii of 73 patients and comparing the resulting morphometric indices to the gold standard patient evaluation including a threshold- and dilation-based contouring approach. Reproducibility was evaluated using repeat scans of intact radii of 19 patients. The new 3D-GAC approach offers contours within inter-operator variability for images of fractured distal radii (mean Dice score of 0.992 {+/-} 0.004 versus median operator Dice score of 0.993 {+/-} 0.006). The generated contours for images of intact radii yielded morphometric indices within the in vivo reproducibility limits compared to the current gold standard. Additionally, the 3D-GAC approach shows an improved robustness against failure (n = 4) when dealing with cortical interruptions, fracture fragments, etc. compared with the automatic, default manufacturer pipeline (n = 40). Using the 3D-GAC approach assures consistent results, while reducing the need for time-consuming hand-contouring.

bioengineering↗

bioRxiv2018

Fast, volumetric live-cell imaging using high-resolution light-field microscopy

Visualizing diverse anatomical and functional traits that span many spatial scales with high spatio-temporal resolution provides insights into the fundamentals of living organisms. Light-field microscopy (LFM) has recently emerged as a scanning-free, scalable method that allows for high-speed, volumetric functional brain imaging. Given those promising applications at the tissue level, at its other extreme, this highly-scalable approach holds great potential for observing structures and dynamics in single-cell specimens. However, the challenge remains for current LFM to achieve subcellular level, near-diffraction-limited 3D spatial resolution. Here, we report high-resolution LFM (HR-LFM) for live-cell imaging with a resolution of 300-700 nm in all three dimensions, an imaging depth of several micrometers, and a volume acquisition time of milliseconds. We demonstrate the technique by imaging various cellular dynamics and structures and tracking single particles. The method may advance LFM as a particularly useful tool for understanding biological systems at multiple spatio-temporal levels.

bioengineering↗