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An alignment-last approach enables rapid transcriptomic biomarker discovery in large cohorts

Canonical transcriptomic analysis requires committing from the outset to a reference genome or transcriptome, which imposes a predefined feature set, usually annotated genes or isoforms. Alignment and annotation dilute the signal through feature-level aggregation, discard any sequence absent from the reference, and require reprocessing the entire dataset for each new question (mutations, fusions, transposable elements). Here, we introduce the alignment-last paradigm, in which the read becomes the unit of comparison across samples, and alignment is deferred to annotate only the relevant sequences. Querying the merome, a reference-free cohort k-mer index, with just a handful of reads (about 0.01% of a sample's) reveals the cohort's transcriptomic structure in bulk and single-cell data. At single-cell resolution, these reads outperform genes for cell classification and rediscover, without supervision, a transposable-element signature (VL30) of exhausted T cells. Finally, unsupervised read-level differential analysis recovers established lncRNA biomarkers; uncovers new prognostic transposable-element reads in adrenocortical carcinoma and sarcomas; and extracts signals even from reads that fail to align.

bioinformatics

Harnessing Escherichia coli motility to engineer bacterial Voronoi patterns

Cell motility drives spatial pattern formation across diverse biological systems. Here, we engineer Escherichia coli motility in semi-solid agar to control Voronoi patterns in two and three dimensions, partitioning space into regions closest to their respective inoculation seeds. Consistent with our reaction-diffusion model, we observed that collisions between expansion fronts generate either biomass depletion (''gaps'') or accumulation (''anti-gaps''), governed by the relative diffusion rates of bacteria and nutrients. By engineering strains with distinct expansion rates and tuneable motility, and by integrating these experimental data into a dynamic Voronoi model, we achieved precise control over pattern geometry. This enabled the generation of gaps with varying widths, curved boundaries, asymmetric structures, seedless regions, and complex composite patterns. Together, these findings establish bacterial Voronoi patterns as a programmable platform for engineering multicellular spatial organization, with potential applications in synthetic biology and materials science.

synthetic biology

Modelling human haematopoietic stem cell commitment ex vivo identifies IL-33 as a regulator of megakaryopoiesis

Commitment events to specific blood lineages arise from single hematopoietic stem cells (HSCs) and are influenced by stress, inflammation and disease. However, the understanding of how such events are regulated in human haematopoiesis is limited by the lack of tractable in vitro models. In this study, we introduce a novel Early Progenitor Differentiation (EPD) assay to study the initial lineage commitment of human 49+ HSCs, in a system faithfully recapitulating cell states observed in vivo. Combining single cell -omics approaches and single cell functional assays, we show that IL-33 acts directly on human 49f+ HSCs activating the MAPK pathway to enhance their commitment towards Megakaryocytic-Erythroid-Mast cell Progenitors and subsequently megakaryopoiesis. This occurs without affecting HSC self-renewal via accelerated establishment of chromatin programmes associated with Erythroid and Megakaryocyte and mast cells lineages. Our findings demonstrate the utility of the EPD model to identify molecular regulators of human HSC differentiation and uncover a new role of IL-33 in haematopoiesis.

cell biology

Intelligent differential ion mobility spectrometry (iDMS): A deep neural network that predicts optimal space-resolved ion mobility parameters for isomeric monoglycosphingolipids

Simultaneous quantification of monoglycosphingolipid stereoisomers is required to monitor changes in defective enzymatic pathways linked to diseases such as Gaucher Disease, Parkinson's Disease, and Krabbe Disease. Resolution of beta-glucosyl and beta-galactosyl epimers cannot be achieved by standard liquid chromatography, electrospray ionization, tandem mass spectrometry (LC-ESI-MS/MS). Separation becomes possible when field asymmetric ion mobility spectrometry (FAIMS), also known as differential mobility mass spectrometry (DMS), is added as an orthogonal separation technique to LC. FAIMS/DMS separates epimeric ion clusters in a high versus low electric field (separation voltage, SV) then redirects the target epimeric ions to the mass spectrometer through the application of a direct current (compensation voltage, CoV). Resolving SVs and CoVs must be manually determined for each lipid. Manual derivation is a labour-intensive process that requires pure synthetic standards, limiting the number of stereoisomers a user can include in an assay. To address this problem, we introduce here intelligent DMS (iDMS). iDMS is an in silico supervised neural network model that learns the ion mobility relationships between SV and CoV and the monoglycosphingolipid structural features of sugar headgroup, N-acyl chain length, and N-acyl degree of unsaturation. iDMS predicts the SV and CoV combinations capable of resolving any stereoisomer pair from a training dataset of composed of measured signal intensities across a range of SVs and CoVs of 12 lipids. This machine learning alternative to manual DMS optimization promises to accelerate the deployment of multiple-reaction-monitoring mode (MRM) RPLC-ESI-DMS-MS/MS assays for the routine and rapid quantification of biologically relevant monoglycosphingolipid stereoisomers.

bioinformatics

Non-Covalent Poly(ADP-ribose) Signaling Organizes a Circadian E3 Ligase Network in the Brain

Although PAR biology has traditionally been studied through covalent PARylation, non-covalent PAR-binding proteins provide an additional mechanism for interpreting transient PAR signals and converting them into downstream regulatory programs. Among these effectors, E3 ubiquitin ligases are uniquely positioned to couple PAR sensing to selective ubiquitination, thereby integrating stress signaling with proteostatic control. Because circadian systems depend heavily on temporally coordinated protein turnover, we hypothesized that PAR-binding E3 ligases may form a circadian-structured regulatory layer within the brain. To test this, we integrated GTEx v10 brain transcriptomics, GWAS Catalog gene-mapped associations, CIRCA circadian phase annotations, and Human Protein Atlas single-cell transcriptomic resources to characterize the organization of PAR-binding E3 ubiquitin ligases across neural tissues. Across the brain, the E3 ligase repertoire was broadly deployed yet regionally structured, with cerebellar and cortical enrichment patterns preserved within the PAR-binding subset. Representative ligases spanning circadian regulation, DNA repair, and neurodegeneration-relevant pathways displayed distinct abundance and regional-variability archetypes across GTEx brain regions. Human genetic analyses demonstrated that E3 ligases associated with cognition-, neurodegeneration-, and sleep/circadian-related phenotypes were disproportionately PAR-binding, supporting convergence between PAR-responsive ubiquitin regulation and disease-relevant biology. Circadian phase analyses further revealed that PAR-binding ligases occupy structured, non-random circadian windows within the broader E3 background, including distinct co-phasing relationships with BMAL1 and CRY1. Finally, cell-type enrichment analyses identified microglia as the dominant compartment for circadian-linked and PAR-binding circadian E3 weighting within the brain E3 program. Together, these findings support a systems-level framework in which non-covalent PAR-binding E3 ubiquitin ligases constitute a brain-deployed, circadian-organized regulatory layer that couples PAR signaling to time-dependent ubiquitin control in neural systems.

bioinformatics

Dehydration triggers anomalous subdiffusion in biomimetic cell membranes

Lipid diffusion plays a central role in shaping the structural organization of cell membranes, maintaining lipid homeostasis, and facilitating cellular transport and signaling. The lateral mobility of phospholipids in membranes depends heavily on their hydration state. Furthermore, the activation energy of diffusion increases in conditions of reduced membrane hydration, suggesting that the underlying diffusion mechanism changes upon dehydration. Using two variants of fluorescence correlation spectroscopy (point FCS and scanning FCS) and two membrane reporters, we demonstrate that mild dehydration of phase-separated biomimetic cell membranes alters the lipid diffusion mechanism, resulting in anomalous subdiffusion rather than free Brownian motion. Importantly, the anomalous diffusion parameter, , decreases significantly upon the initial reduction of the membrane hydration layer, and the effect is fully reversible upon rehydration. These observations strongly indicate the reversible shift in lipid diffusion mode rather than irreversible membrane damage. We propose that this anomalous subdiffusion is caused by the formation of temporarily immobile lipid pockets in the membrane upon dehydration. These results therefore provide important insights into the mechanism of lipid diffusion in membranes undergoing local and transient dehydration, which is an important intermediate step in various biological processes associated with membrane fusion, such as neurotransmission, fertilization, and viral entry.

biophysics

Basophilic Erythroblast Emerges as the Key Turning Point in Polycythemia Vera

Abstract Polycythemia vera (PV) is a rare, chronic myeloproliferative neoplasm driven by the JAK2V617F mutation and characterized by uncontrolled erythroid proliferation. Although the mutation arises in hematopoietic stem cells, the differentiation stage at which its transcriptional consequences first become biologically meaningful has remained undefined. Using a multi-layer transcriptomics integration approach that combined differential gene expression, NicheNet ligand-receptor analysis, pseudotime trajectory inference, and CNV profiling on scRNA seq data, alongside bulk transcriptome validation, we identified basophilic erythroblasts as the critical transition point at which JAK2V617F shifts from a genomically present but transcriptionally silent state to an actively trajectory-altering and treatment-responsive disease driver. Differential expression revealed a qualitatively distinct disease signature at this stage, including ERFE-mediated iron dysregulation, MAP2K2-driven RAS/MAPK co-activation, and epigenetic reprogramming. NicheNet showed the establishment of a TGF{beta} superfamily and chemokine-driven niche-remodeling axis, and pseudotime analysis demonstrated that basophilic erythroblasts are the first erythroid population to exhibit condition-dependent trajectory divergence, whereas earlier progenitors showed none despite carrying the mutation. Interferon- treatment showed its broadest counterresponse at this stage but declined sharply thereafter, identifying basophilic erythroblasts as both the principal therapeutic target and the point of maximum vulnerability in PV.

bioinformatics

Mechanism-based prediction of insertion-driven high pathogenicity avian influenza virus emergence

High pathogenicity avian influenza viruses (HPAIVs) emerge from H5 and H7 low-pathogenicity avian influenza virus progenitors through mutations that introduce a multibasic cleavage site in haemagglutinin. Although nucleotide insertions recurrently generate this motif, the molecular determinants of insertion and whether particular HA sequences are genetically predisposed to evolve toward HPAIV remain unknown. Combining experimental virology and thermodynamic modelling, we show that insertions arise through polymerase slippage controlled by local product-template duplex thermodynamics within the viral polymerase catalytic site. Predicted RNA secondary structures outside the polymerase are not required for high-frequency insertions and only modestly modulate insertion rates. We formalize this mechanism in HPAIVpredict, which predicts insertion profiles, recapitulates intermediates associated with documented HPAIV emergence events and identifies H5 and H7 sequence backgrounds predisposed to acquire functional multibasic cleavage sites.

microbiology

THE ROLE OF LIQUID CRYSTAL ORDERING IN THE STRUCTURAL ORGANIZATION OF DNA IN BACTERIA.

This paper presents and critically reviews the results of original and some literature based experimental studies conducted by the authors last years on the structural organization of DNA in dormant (starvation stress), anabiotic dormant (4 HR treatment) E. coli cells, as well as the K12 {Delta}dps strain, which lacks the Dps protein (Dps null E. coli). The experimental data includes small-angle synchrotron radiation diffraction (SAXS) and transmission electron microscopy (TEM) data. Synchrotron radiation diffraction experiments on K12{Delta}dps cells allowed us to conclude that peaks at 44.3, 22.1, and 14.8 angstrom resolutions are associated exclusively with ordered DNA organization. Peaks at 44.3, 22.1, and 14.8 angstrom resolutions are also observed for samples of dormant (starvation stress) cells and anabiotically dormant cells. Therefore, this ordered DNA organization also applies to samples of dormant and anabiotically dormant cells. A model is proposed that considers the ordered DNA organization in the cell as a cholesteric liquid crystal. The powder diffraction pattern calculated based on this model is compared with experimental small angle X ray scattering (SAXS) data obtained on Dps-null cell samples. The model completely reproduces the key features of the experimental diffraction pattern from Dps-null cell samples. Accordingly, the cholesteric liquid crystal model corresponds to DNA packaging in dormant and anabiotically dormant cells. Cholesteric liquid crystal ordering should be further considered in all models of cellular DNA packaging. To address the question of which structural organization of DNA predominates in the cell: the cholesteric liquid crystal or nanocrystalline or whether they coexist and fully manifest themselves under different external conditions, it is necessary to utilize the latest methodological advances in structural analysis.

biophysics

Predictability failure in glucose-insulin system for ICU patients

Modern medicine implicitly assumes that physiological responses to intervention are predictably determined by administered treatments. However, physiological systems containing intrinsic delays between the detection of a stimulus and the biological response may violate this assumption. We investigate the human glucose-insulin system as described by the Ultradian model and mathematically demonstrate that clinically relevant forcing protocols-such as pulsatile insulin delivery and step-wise glucose infusion, both commonly used in intensive care units (ICUs)-can induce sustained temporal chaos that may hamper accurate prediction of the physiological response. If not accounted for, these chaotic dynamics could create difficulties in achieving optimal dosing and timing when administering glucose and insulin in clinical or home care settings. This phenomenon, termed delay-induced uncertainty (DIU), arises from the interaction between physiological delay, intrinsic shear near a limit cycle, and external forcing. Using the Ultradian glucose-insulin model, we compute top Lyapunov exponents to quantify predictability. Across a range of pulsatile and step-wise forcing regimes, including stochastic amplitudes drawn from Markov processes, we observe positive Lyapunov exponents, indicating sustained chaos. Our results suggest that delayed endocrine regulation may fundamentally limit the predictive value of the models used to develop glycemic management strategies, with implications for clinical protocols in the ICU.

systems biology

AnnFlux: object-conditioned neural stochastic differential equations for single-cell perturbation dynamics

Single-cell perturbation profiling measures responses to genetic and chemical interventions, yet most models learn a static map, ignoring how populations move over time and how perturbations combine. AnnFlux, an object-conditioned stochastic differential equation, learns a drift field in latent cell-state space. Conditioning on the perturbing object makes the field queryable one object at a time, yielding per-object drifts comparable across genes and drugs. By learning a drift field tailored to each perturbation context, it interpolates a held-out timepoint in an epithelial-mesenchymal transition time course and predicts unseen perturbations. Beyond point estimates, AnnFlux improves distributional fidelity and predicts responses to held-out perturbation combinations. An IFN-response signature predicted by AnnFlux was associated with TLS proximity in an independent pan-cancer spatial atlas. This framework maps perturbation-driven cell-state evolution as continuous trajectories and represents unseen perturbations using prior-knowledge embeddings.

bioinformatics

A replicated patient-specific component of tumour telomere length across two pan-cancer cohorts

Bulk telomere length measured from tumour sequencing is routinely interpreted as a property of the cancer cells. However, a tumour specimen is a mixture, and the patient who supplies it has a telomere length of their own. Here I re-analyse published pan-cancer telomere estimates and ask how much of a tumour's telomere length is patient-specific. A calibration step comes first. Whole-genome and low-pass estimates recover the known cross-sectional attrition of leukocyte telomeres with age, at 26.6 bp per year in blood normals, whereas whole-exome estimates do not. After adjustment for cancer type, sequencing centre and sex, the exome slope is minus 0.6 bp per year. In 684 blood-normal aliquots sequenced by both assays, the whole-genome estimate declines at 38.9 bp per year, whereas the exome estimate from the same DNA shows no detectable decline. The difference between assays is 41.5 bp per year, with P = 3 x 10^-10. Because exome data constitute 78.6% of the original resource, downstream analyses use only whole-genome and low-pass libraries. Within those data, tumour telomere length tracks the patient's matched-normal telomere length. The Spearman correlation is 0.395 in TCGA, with positive associations in 22 of 23 cancer types. This finding replicates in PCAWG using a different telomere estimator, with a correlation of 0.472 and positive associations in all 24 histologies examined. Adjustment for cancer type, sequencing centre and library type leaves a regression coefficient of 0.385. The association is also stable after adjustment for age, sex, tumour purity, leukocyte fraction, ploidy, sequencing coverage and continental ancestry, with coefficients ranging from 0.406 to 0.429. Pure normal-cell admixture is rejected as the sole explanation. Under a two-compartment mixture model, the coefficient for host telomere length is expected to equal 1 and the host-by-purity interaction to equal minus 1. These restrictions are jointly rejected with P = 0.001. Tumour purity, leukocyte fraction and age each explain only about 1 to 3% of within-cohort variance and do not alter the cross-cancer ranking. By contrast, the between-cohort coefficient is not directly interpretable. Its apparent near one-to-one relationship with tissue-associated telomere length depends strongly on which tissue supplies the matched-normal reference and on the statistical spread of that predictor, falling to 0.44 when organ-matched solid tissue is used. Bulk tumour telomere length is therefore a composite phenotype containing a replicated patient-specific component. Telomere biomarker studies should include matched-normal telomere length as a covariate rather than treating tumour telomere length as exclusively tumour-intrinsic.

cancer biology

β4-integrins safeguard nuclear mechanics to suppress prostate cancer progression

Prostate cancer (PCa) progression is accompanied by profound alterations in cell-extracellular matrix (ECM) adhesion, nuclear architecture and mechanical adaptability, yet the molecular mechanisms linking these processes remain poorly understood. Hemidesmosomes (HDs), formed by 6{beta}4-integrins, anchor epithelial cells to the basement membrane and couple extracellular forces to the intermediate filament (IF) cytoskeleton. Here, we identify a previously unrecognized tumor-suppressive function of {beta}4-integrins in preserving nuclear integrity in prostate epithelial cells. Loss of {beta}4-integrins disrupted the cytokeratin-5 network and its coupling to the nucleus, leading to nuclear softening, lamin remodeling, reduced heterochromatin content and enhanced confined migration. Unexpectedly, proximity-labeling proteomics revealed that {beta}4-integrins engage nuclear pore complex (NPC) components in an 6-independent manner, particularly upon HD disassembly. Selected interactions were validated using proximity ligation and co-immunoprecipitation assays. {beta}4-integrin loss was associated with enlarged nuclear pores and aberrant nucleocytoplasmic transport, including nuclear accumulation of YAP1. Consistent with these findings, reduced {beta}4-integrin expression in a large PCa tissue cohort correlated with altered nuclear morphology, adverse clinicopathological features, metastatic progression, and poor patient survival. Collectively, our study establishes {beta}4-integrins as a critical molecular link between cell-ECM adhesion, nuclear mechanics and genome integrity.

cancer biology

Local mechanical heterogeneity drives epidermal cell delamination

Delamination within stratified epithelia like the skin epidermis describes the detachment and upward motion of cells originating from the basal layer. Despite its fundamental importance for tissue development, homeostatic regeneration and repair, the mechanisms that drive delamination remain a longstanding open question. Upward motion follows cell shape changes, which are inherently driven by physical forces, but their role is elusive. Here, we investigate delamination in stratifying keratinocytes by combining imaging, force measurements and theoretical modeling. We identify a local change in force balance between differentiating cells and their environment as the key step initiating delamination. Within a homogeneous cell layer with apically polarized contractility, differentiation leads to actomyosin remodeling, redistributing cellular force exertion to the basal side. Such mechanical heterogeneity then results in differentiating cells experiencing and inward basal and outward apical forces that manifest in the formation of a +1 force defect and promote shape changes culminating in upward motion. Simultaneously, delaminating cells actively pull on their underlying neighbors, generating convergent tissue flows which close the basal layer below. Together, we propose a general physical description of delamination initiation, which may act across various multilayered epithelia.

biophysics

Nuclear Cathepsin L Remodels the Replication Machinery to Create a Therapeutic Vulnerability in Ovarian Cancer

Abstract Therapeutic resistance in ovarian cancer is frequently driven by persistent replication stress, yet the molecular mechanisms that convert replication stress into a therapeutically exploitable vulnerability remain incompletely understood. Here, we identify drug-induced nuclear cathepsin L (nCTSL) as a previously unrecognized regulator of replication stress and DNA repair. Clofarabine (CLF) combined with the ATR inhibitor AZD6738, or the CHK1 inhibitor prexasertib promoted nuclear accumulation of CTSL, where it remodeled the replication machinery through degradation of CCNE1, MCM3, MCM6, and geminin, accompanied by loss of RAD51 and 53BP1 and increased {gamma}H2AX and phospho-RPA2. DNA fiber analysis demonstrated marked inhibition of replication fork progression following CLF-based combinations, whereas CTSL depletion accelerated fork progression and abolished therapy-induced replication stress. Reconstitution with the nuclear M1F CTSL isoform restored replication restraint, confirming a direct role for nuclear CTSL in regulating replication dynamics. GFP-based DNA repair reporter assays further revealed that CLF-based combinations suppress DNA repair competence in a CTSL-dependent manner, indicating that nuclear CTSL couples replication stress amplification with functional inhibition of repair pathways. Functionally, CLF-based combinations selectively targeted transformed fallopian tube secretory epithelial cells while sparing non-transformed counterparts, demonstrated broad activity in patient-derived ovarian cancer ascites spheroids, and significantly inhibited tumor growth and prolonged survival in vivo. Collectively, our findings identify nuclear CTSL as a mechanistic driver of replication stress that remodels the replication machinery, impairs DNA repair, and creates a therapeutically exploitable vulnerability in ovarian cancer. We propose that nuclear CTSL promotes a transition from replication competence to replication catastrophe, thereby establishing a conceptual framework for biomarker-guided therapeutic strategies targeting CTSL-dependent replication stress.

cancer biology

SARAF represses the mild hypothermia response through the regulation of JUN

The mild hypothermia response (MHR) is a conserved mammalian cytoprotective program activated upon exposure to mild hypothermia (32 degrees C) that contributes to the neuroprotective effects of therapeutic hypothermia following hypoxic injury. Although rapid changes in intracellular calcium occur upon cooling, the mechanisms linking calcium dynamics to the activation of core MHR factors such as SP1 and RBM3 remain incompletely defined. In this study, we used siRNA-mediated knockdown (KD) of candidate regulators in conjunction with novel mild hypothermia indicator (MHI) reporters to identify upstream modulators of MHR-associated transcription. We identify SARAF, a negative regulator of store-operated calcium entry (SOCE), as a repressor of both SP1 and RBM3 under normothermic conditions. SARAF depletion is associated with increased intracellular calcium release and enhanced SP1- and RBM3-linked transcriptional outputs. We identify JUN as an important downstream factor mediating SARAF depletion-dependent de-repression of the MHR and demonstrate that it undergoes activation rapidly upon cooling. Finally, SARAF depletion conferred significant cytoprotection against hypoxia-induced early apoptosis. Collectively, these findings establish SARAF as an upstream regulator of MHR-associated transcription and provide a functional link between cold-induced intracellular calcium dynamics and the induction of core MHR effectors.

molecular biology

AVOCODO: An open-source multimodal annotation platform for developmental EEG

Behavioral annotation of synchronized video recordings is an essential step in developmental electroencephalography (EEG) research, supporting both the identification of behavior-related artifacts and the investigation of brain-behavior relationships. Existing annotation workflows, however, are often fragmented: proprietary EEG software provides limited flexibility for behavioral coding, whereas dedicated behavioral annotation platforms typically lack native integration with EEG data. We developed AVOCODO (Audio/VideO CODing Optimization), an open-source MATLAB-based software platform that integrates synchronized behavioral annotation directly into the EEG workflow. AVOCODO reads native EGI MFF recordings, synchronizes embedded video with EEG, visualizes the audio spectrogram to facilitate precise annotation of vocalizations, and writes user-defined behavioral events directly back into the original MFF recording as native EEG event markers while simultaneously exporting annotations as CSV files. The software supports fully customizable behavioral coding schemes, optional EEG visualization for quality control, and reloading of previously annotated recordings for review and inter-rater verification. Since its initial development in 2024, AVOCODO has been applied internally across five developmental EEG studies involving approximately 500 pediatric participants and more than 3,000 EEG recordings. By bridging behavioral annotation and EEG preprocessing within a unified open-source workflow, AVOCODO has the potential to improve the efficiency, reproducibility, and scalability of behavioral annotation in developmental EEG research.

bioinformatics

Single-cell informed metabolic modeling reveals organ-specific metabolic adaptations in breast cancer organotropism

Breast cancer organotropism is driven by interactions between tumor cells and organ-specific microenvironments that support metastatic growth. To better understand the metabolic basis of organ-specific metastasis, we integrated single-cell transcriptomics with constraint-based systems biology to generate context-specific metabolic models of breast cancer metastasis to the liver, bone, and brain. Our analysis identified both common and organ-specific metabolic changes, suggesting that metastatic cells share a core metabolic program while also adapting to the metabolic environment of each target organ. Primary tumors with metastatic potential showed early alterations in nucleotide metabolism, transport reactions, and energy-related pathways, indicating metabolic changes before metastatic spread. Metabolic transformation analysis identified key metabolic regulators involved in the tricarboxylic acid (TCA) cycle, oxidative phosphorylation, redox balance, and metabolite transport. Integration with CRISPR gene essentiality data further highlighted metabolically important genes as potential therapeutic targets. In addition, analysis of organ-specific secreted metabolites revealed distinct metabolic signatures associated with metastatic colonization of the liver, bone, and brain. Overall, our single-cell-informed metabolic modeling approach shows that breast cancer organotropism is associated with both shared and organ-specific metabolic adaptations. The study provides a framework for identifying potential metabolic vulnerabilities that could be targeted to treat metastatic breast cancer.

systems biology