Search bioRxiv⌕ Search

bioRxiv · 10.64898/2026.01.08.698349

Lung-mimicking click alginate-dECM model of breast cancer lung metastasis reveals the role of ECM mechanics in tumor growth dynamics and genomic instability

Abstract

Metastatic breast cancer (BC) is the main cause of cancer-related death in women. Accumulating evidence highlights the prominent changes within the lung metastatic niche, resulting in stiffening of the extracellular matrix (ECM). The prevailing concept of cancer evolution encompasses the acquisition of beneficial traits as a consequence of genomic instability, yet it remains elusive to what extend altered lung ECM mechanics feed into this. To investigate this, a tunable 3D bioengineered model, capturing the biophysical and biochemical characteristics of the BC metastatic lung niche is developed. Porcine derived lung decellularized ECM (dECM), combined with norbornene and tetrazine modified click-crosslinkable alginate, recapitulates composition and mechanics of healthy soft (3 kPa) and metastatic stiff (13 kPa) lung niches. Label-free optical microscopy further validates the microarchitectural resemblance between resulting matrices and human lung metastasis samples. Encapsulation of MDA-MB-231 and MCF7 cells reveals that stiffer matrices promote BC cluster growth and DNA damage, indicated by yH2AX, independent of BC subtype. Moreover, this platform is compatible with patient derived cells, which remain viable for 14 days. These findings underscore the critical role of tissue mechanics in regulating BC metastasis progression and demonstrate the utility of the herein developed tunable, physiologically relevant platform for patient-based models. Table of Content O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=180 SRC="FIGDIR/small/698349v1_ufig1.gif" ALT="Figure 1"> View larger version (59K): org.highwire.dtl.DTLVardef@19a164dorg.highwire.dtl.DTLVardef@12e1c1aorg.highwire.dtl.DTLVardef@371378org.highwire.dtl.DTLVardef@1df3ddb_HPS_FORMAT_FIGEXP M_FIG C_FIG Fabrication of 3D bioengineered breast cancer (BC) lung metastasis niche to investigate how tissue mechanics modulate cancer evolution. Tunable hybrid biomaterials recapitulate the mechanical and biochemical characteristics of healthy soft and diseased stiff lung. Within these niches, stiffness promotes enhanced BC cluster growth and genomic instability. Biocompatibility with patient-derived BC cells, opens opportunities for drug testing platforms for personalized medicine.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Fallert, L., Urigoitia-Asua, A., Pardo-Sanchez, J. M., Jimenez de Aberasturi, D., Cipitria, A.. 2026-01-08. Lung-mimicking click alginate-dECM model of breast cancer lung metastasis reveals the role of ECM mechanics in tumor growth dynamics and genomic instability. https://doi.org/10.64898/2026.01.08.698349

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

SpiraMed: A Stereotactic Helix-based Therapy Delivery system for the Human Brain

Stereotactic needle-based delivery remains the standard for local administration of Advanced Therapy Medicinal Products (ATMPs) to the human brain. ATMP administration typically involves multiple trajectories, presenting cumulative risks and prolonging surgery. Reflux-prone, patchy therapy coverage compromises clinical results. We demonstrate a novel approach, deploying a helical delivery catheter via a single access trajectory per target, referred to as SpiraMed. Helix retraction is synchronised with therapy delivery, enabling comprehensive target coverage in seconds. Helix pitch and diameter can be precisely tailored to patient-specific target volume and vascular anatomy, as part of the preoperative stereotactic surgical planning process. Testing in agarose phantoms, live sheep and cadaveric human brain confirms enhanced therapy delivery volume, delivery speed and target coverage, with reductions in reflux and predicted risk of bleeding complication. SpiraMed represents a new paradigm, promising to help deliver on the transformative potential of cell and gene therapies across the spectrum of human CNS disease.

bioengineering↗

Normative Modeling of Molecular-Enriched Functional Connectivity for Detecting Deviations from Healthy Brain Aging

Inter-individual variability in adult brain aging can obscure early pathological alterations and is only partly represented by population-average or scalar brain-aging measures. We combined Receptor-Enriched Analysis of functional Connectivity by Targets (REACT) with normative modeling (NM) to derive spatially resolved, molecularly informed deviation scores for dopamine transporter (DAT)-, norepinephrine transporter (NET)-, and serotonin transporter (SERT)-enriched resting-state functional connectivity (FC). We first evaluated whether these normative models could be transferred to independently processed external data through local calibration and then explored whether the resulting deviation profiles differed with cerebral amyloid burden in cognitively unimpaired older adults. Hierarchical Bayesian regression (HBR) models with a SHASHb likelihood were estimated separately for 204 cortical molecular-enriched FC features in 4,152 healthy adults (18.0--89.8 years) from seven publicly available neuroimaging datasets and evaluated in a held-out healthy test set. Pretrained models were locally adapted to three AMYPAD-PNHS acquisition batches using cognitively unimpaired, amyloid-negative participants (global Clinical Dementia Rating [CDR] = 0; Centiloid [CL] [lt] 10). The independent primary comparison contrasted participants with intermediate amyloid burden (10 [≤] CL [lt] 30; n = 111) and amyloid-positive participants (CL [≥] 30; n = 66); secondary analyses tested linear associations with continuous CL within participants with CL [≥] 10. Of 204 normative reference models, 199 (97.5%) met the predefined diagnostic criteria; median held-out explained variance (EXPV) was 0.174. Of 612 feature-by-batch transfers, 541 (88.4%) met the strict transfer-diagnostic criteria. In the primary false discovery rate (FDR)-controlled regional analysis, DAT-enriched right caudal middle frontal cortex showed lower locally standardized deviation scores in the intermediate-amyloid-burden group than in the amyloid-positive group (adjusted difference = -0.582, q = 0.016). DAT extreme-deviation burden was also greater in the intermediate-amyloid-burden group (difference = 0.032, q = 0.044). The right frontal effect was reproduced with model-native scores across the three acquisition batches (pooled standardized effect = -0.698, q = 0.010). No NET- or SERT-enriched regional difference between these two groups survived FDR correction, and no regional or subject-level linear association with continuous CL values survived FDR correction in the CL [≥] 10 group. Normative modeling can provide spatially resolved reference distributions of molecular-enriched FC that are deployable in independently processed external data when local adaptation, calibration, and feature-level transfer diagnostics are incorporated. The AMYPAD-PNHS application identified modest, spatially selective, and molecular-system-specific categorical differences during a cognitively unimpaired stage of amyloid accumulation, while continuous analyses within CL [≥] 10 did not support a linear association. These findings support a methodological basis for distributed application of molecular-enriched normative models and motivate independent and longitudinal evaluation of their biological relevance.

bioengineering↗

AC-Diff: Anatomy-Contrast Disentangled Diffusion for Multi-Vendor Liver MRI Harmonization

Magnetic resonance imaging (MRI) exhibits substantial scanner and protocol dependent appearance variations, making harmonization challenging without distorting patient specific anatomy, particularly in abdominal imaging. We propose AC-Diff, an anatomy--contrast disentangled diffusion framework that formulates MRI harmonization as a factor-specific generative intervention. Using aligned multi-contrast supervision and cross-patient factor swapping, AC-Diff learns to separate anatomical structure from acquisition-dependent contrast. Unlike conventional image or latent diffusion, AC-Diff restricts stochastic generation to the contrast subspace while the source anatomy bypasses diffusion and is directly reused during reconstruction. Experiments on an in-house multi-vendor cohort and the external Duke Liver MRI dataset demonstrate improved target-domain alignment with strong structural preservation. In downstream liver segmentation, AC-Diff improves Dice from 0.942 for the original inputs to 0.954 for the harmonized images. These results support contrast-specific latent generation as a promising approach to anatomy-preserving MRI harmonization.

bioengineering↗