Biology subjects

Danen, E.

Publications and source records attributed to Danen, E..

6 recordsLinked to original sources

bioRxiv2026

Informing agent-based models with spatial data using convolutional autoencoders

Spatial computational models such as agent-based models (ABMs) offer powerful in silico tools to study tumor dynamics, yet imaging data are still rarely used to inform these models directly. We present an ABM optimization framework that leverages convolutional encoders to compare spatial patterns between experimental imaging data and ABM-generated outputs within a shared latent space. This quantitative comparison was used to estimate ABM parameters across three datasets, ranging from synthetic data to 3D tumoroid-T cell co-culture microscopy and histopathology images from The Cancer Genome Atlas skin cutaneous melanoma samples. Estimated parameters were evaluated using data-derived features and experimental knowledge, including experimental conditions and gene expressions. Simulations using optimized parameters reproduced key spatial features of the training images, such as tumor boundary complexity and tumor-tumor neighborhood structure. Together, these results demonstrate a flexible framework for ABM parameter optimization using spatial data across modalities, enabling systematic investigation of how spatial architecture influences tumor progression and immune interactions.

systems biology↗

bioRxiv2026

Multi-omics characterization of breast cancer metabolism identifies new metabolic targets

Breast cancer cells undergo metabolic reprogramming to support proliferation and metastasis, but these alterations are heterogeneous. To systematically assess this heterogeneity under controlled conditions, we profiled 31 intracellular polar metabolites and 50 amines, together with exchange rates of 57 amines, in a panel of 51 breast cancer cell lines spanning diverse phenotypes. These data were integrated with lipidomics and transcriptomics. Multi-omics factor analysis identified metabolic signatures linked to proliferation and to differences between luminal, HER2-positive, basal A, and basal B cell lines, overlapping with an epithelial-to-mesenchymal transition phenotype. Fast-proliferating, aggressive cell lines showed increased uptake of essential amino acids and altered nucleotide levels, while heterogeneity in glutamine metabolism was mainly driven the subtype. This was partially associated with heterogeneous expression of metabolite transporters. To test the functional relevance, 67 metabolic genes were silenced in Hs578T using siRNA, and effects on proliferation and migration were measured by a sulforhodamine B assay, live-cell imaging, and a random cell migration assay. This resulted in 34 knockdowns that reduced proliferation and 20 reduced migration, with strong effects for the glycosyltransferases EXT1 and EXT2, nucleotide metabolism genes GART and HPRT1, and metabolite transporters SLC7A1, SLC7A11, and SLC16A3. These findings highlight phenotype-specific metabolic dependencies and identify candidate drug targets in aggressive breast cancer.

cancer biology↗

bioRxiv2025

Disentangling the interplay between cell-cell and cell-matrix interactions in cancer cell migration

Metastasis proceeds through the dissemination of cells from the primary tumor into the surrounding extracellular matrix (ECM), initiating further spread throughout the body. The invasion of cancer cells into the ECM is significantly influenced by cell-cell adhesion, cell-matrix adhesion, and the generation of traction forces. However, the complex interplay between these different aspects makes it difficult to disentangle their roles in the invasive process, hampering our mechanistic understanding of collective cell invasion. Here, we combine integrin knockout experiments in Hs578T and 4T1 breast cancer cell lines with a computational cellular Potts model to elucidate the biophysical mechanisms underlying invasive cell behavior. By tuning the cell-cell and cell-matrix adhesion parameters in our computational model, we establish a quantitative mapping with the experiments. Our work reveals that strong cell-matrix interactions promote invasion, while strong cell-cell adhesion promotes the formation and dissemination of multicellular clusters. Moreover, our model delineates a threshold for invasion and predicts that tumor morphology - particularly the number of branches from the primary tumor - correlates with its invasive potential, suggesting that morphological tumor features may serve as a proxy for metastasis. Our approach highlights the importance of combining biological experiments with computational and predictive modeling, offering new insights into the mechanisms driving cancer cell migration.

biophysics↗

bioRxiv2024

Novel high throughput 3D ECM remodeling assay identifies MEK as key driver of fibrotic fibroblast activity

In fibrotic tissues, activated fibroblasts remodel the collagen-rich extracellular matrix (ECM). Intervening with this process represents a candidate therapeutic strategy to attenuate disease progression. Models that generate quantitative data on 3D fibroblast-mediated ECM remodeling with the reproducibility and throughput needed for drug testing are lacking. Here, we develop a model that fits this purpose and produces combined quantitative information on drug efficacy and cytotoxicity. We use microinjection robotics to design patterns of fibrillar collagen-embedded fibroblast clusters and apply automated microscopy and image analysis to quantify ECM remodeling between-, and cell viability within clusters of TGF{beta}-activated primary human skin or lung fibroblasts. We apply this assay to compound screening and reveal actionable targets to suppress fibrotic ECM remodeling. Strikingly, we find that after an initial phase of fibroblast activation by TGF{beta}, canonical TGF{beta} signaling is dispensable and, instead, non-canonical activation of MEK-ERK signaling drives ECM remodeling. Moreover, we reveal that higher concentrations of two TGF{beta} receptor inhibitors while blocking canonical TGF{beta} signaling, in fact stimulate this MEK-mediated profibrotic ECM remodeling activity.

cell biology↗

bioRxiv2024

Single-Cell Stress Analysis in Tumoroids.

The reciprocal interplay between cancer cells and their local environment, mediated by mechanical forces, necessitates a deeper experimental understanding. This requires precise quantitative measurements of cellular forces within the intricate three-dimensional context of the extracellular matrix. While methods such as traction-force microscopy and micropillar-array technology have effectively reported on cellular forces in two-dimensional cell culture, extending these techniques to three dimensions has proven exceedingly challenging. In the current study, we introduced a novel approach utilizing soft, elastic hydrogel microparticles, resembling the size of cells, to serve as specific and sensitive traction probes in three-dimensional cell culture of collagen-embedded tumoroids. Our methodology relies on high-resolution detection of microparticle deformations. These deformations are translated into spatially resolved traction fields, reaching a spatial resolution down to 1 {micro}m and thereby detecting traction forces as low as 30 Pa. By integrating this high-resolution traction analysis with three-dimensional cell segmentation, we reconstructed the traction fields originating from individual cells. Our methodology enables us to explore the relationships between cellular characteristics, extracellular traction fields, and cellular responses. We observed that cellular stresses ranged from 10 to 100 Pa, integrating to cellular forces from 0.1 to 100 nN, which correlated with the localization of the cells actin skeleton, and the interaction area that cells developed towards the microparticles. Interestingly, the interaction of cells with inert microparticles appeared to be governed by contact mechanics resembling that of two soft spheres. The methodology presented here not only addresses the challenges of extending traditional stress-probe techniques to three dimensions, but also opens a strategy for the study of specific interactions between cells and the local tumoroid environment in a strive to further understand cell-matrix reciprocity in tissue. Here, we present a novel methodology that permits the measurement of quantitative surface stresses on small, inert, elastic, deformable microparticles. Our approach tackles the involved task of mapping local three-dimensional stress fields within tissue. Our methodology was successfully applied to analyze local stresses within a tumor spheroid. We foresee that our research represents a significant advancement toward comprehending the intricate dynamics of cell-matrix reciprocity within tissue.

biophysics↗

bioRxiv2021

Substrate rigidity modulates traction forces and stoichiometry of cell matrix adhesions.

In cell matrix adhesions, integrin receptors and associated proteins provide a dynamic coupling of the extracellular matrix (ECM) to the cytoskeleton. This allows bidirectional transmission of forces between the ECM and the cytoskeleton, which tunes intracellular signaling cascades that control survival, proliferation, differentiation, and motility. The quantitative relationships between recruitment of distinct cell matrix adhesion proteins and local cellular traction forces are not known. Here, we applied quantitative superresolution microscopy to cell matrix adhesions formed on fibronectin-stamped elastomeric pillars and developed an approach to relate the number of talin, vinculin, paxillin, and focal adhesion kinase (FAK) molecules to the local cellular traction force. We find that FAK recruitment does not show an association with traction-force application whereas a ~60 pN force increase is associated with the recruitment of one talin, two vinculin, and two paxillin molecules on a substrate of effective stiffness of 47 kPa. On a substrate with a four-fold lower effective stiffness the stoichiometry of talin:vinculin:paxillin changes to 2:12:6 for the same ~60 pN traction force. The relative change in force-related vinculin recruitment indicates a stiffness-dependent switch in vinculin function in cell matrix adhesions. Our results reveal a substrate-stiffness-dependent modulation of the relation between cellular traction-force and the molecular stoichiometry of cell-matrix adhesions.

biophysics↗