Experimental & Molecular Medicine

The innate immune system controls bacterial growth and modulates inflammation during wound healing. TCP-25 is a synthetic thrombin-derived host-defense peptide that combines direct antibacterial activity with neutralization of microbial products and modulation of CD14-dependent inflammatory signaling. We investigated whether this dual mechanism translates to human wounds using longitudinal samples from 24 healthy volunteers enrolled in a randomized, double-blind, within-participant, placebo-controlled phase I dose-escalation study of topical TCP-25 gel in matched epidermal suction blister wounds. We assessed inflammatory cytokines, neutrophil-derived proteins, wound exudation, cultivable bacterial burden, spatial bacterial distribution, and microbiome composition. TCP-25 reduced multiple cytokines, myeloperoxidase, and heparin-binding protein, with the strongest effects observed during the peak inflammatory phase. These changes were accompanied by reduced wound exudation and significant reductions in cultivable bacterial burden. Despite this antibacterial effect, microbiome composition and diversity remained largely unchanged, and participant-specific microbial profiles were preserved. TCP-25 therefore coordinated bacterial control, modulation of the physiological inflammatory response, and reduced wound leakage without major disruption of the resident microbiota composition. These findings provide clinical support for translating nature's endogenous host-defense principles into new therapies for complex wounds.

Dermatomyositis is driven by overactivation of type I and II interferons and other proinflammatory cytokines that signal via the JAK-STAT pathway. We conducted a 12-week, open-label study of brepocitinib, an oral TYK2/JAK1 inhibitor, in five adults with severe cutaneous dermatomyositis. Treatment was associated with rapid, clinically meaningful improvement in cutaneous disease activity. Single-cell and spatial transcriptomic profiling of lesional skin showed marked suppression of interferon-responsive pathways and inflammatory cell states by week 4. Together with findings from a Phase 3 randomized trial in DM patients with skin and muscle involvement (VALOR, NCT05437263), these data support TYK2/JAK1 inhibition as a promising therapeutic strategy for DM.

Type II diabetes mellitus (T2DM) is one of the most prevalent diseases in the United States and is associated with diabetic foot ulcers (DFU) and their impaired, often chronic, wound healing. The T2DM mouse model with dysfunctional leptin receptor (db/db) has been used in basic and translational studies of wound healing due to its systemic phenotypes (hyperphagia, hypometabolism, obesity, T2DM) and its notable delayed skin wound healing. However, a characterization of the temporal cellular dynamics of the db/db wound healing model has not been performed, nor has the model been systematically compared to human DFUs. We performed the first comprehensive single-cell, multi-omic analysis of dermal cells in diabetic (db/db) compared to non-diabetic (ND) mice across three time points ranging from the inflammatory to the delayed proliferative and resolution phases of healing. Single-cell transcriptomics were uniquely linked to their corresponding cells surface protein expressions of cell-specific receptors, including immune cells (CD45) such as neutrophils (CD11b, Ly6G), monocytes/macrophages (CD11b, F4/80, CD11c, Ly6C) and T lymphocytes (CD3, CD4), and dermal cells such as endothelial cells (CD31) and fibroblasts (CD26, CD140a), and showed high concordance between protein cell markers and their gene expressions in major cell types. Differential multi-omic analyses characterized two neutrophil (Tnfaip3+Sod2+Ly6G+, Csf3r+Fos+Ly6G+), three monocyte/macrophage (F4/80highCD11bhigh, Ly6chighCD11bhigh, CD11chighCD11blow) and three fibroblast (Pi16+Dpp4+CD26high, Lrrc15+Tnc+CD140ahigh, Cilp+Mgp+CD26low) subtypes showing dysregulated dynamics across the time course of healing in db/db vs ND mice. Notably, NETotic Tnfaip3+Sod2+Ly6G+ neutrophils and phagocytic F4/80highCD11bhigh macrophage subtypes were drastically up-regulated in diabetic wounds. Differential cell-cell communication analyses revealed striking differences in crosstalk dynamics between fibroblast, macrophage and neutrophil subtypes in the early phase of healing, and ligand-receptor interactome analyses identified CD44 as the hub of dysregulated immune cell interactions in diabetic wounds, implicating cell adhesion, migration and inflammatory pathways, especially those mediated by ICAM1. Inhibition of CD44 using blocking antibodies in primary macrophages from db/db mice and via intradermal injections in db/db mice significantly normalized the early wound immune dysfunction, in part by inhibiting ICAM1 and reversing the excessive neutrophil influx into diabetic wounds. A new integrated dataset of single-cell human chronic wound studies revealed similar CD44-mediated immune cell dysfunctions in diabetic vs non-diabetic foot ulcers, pointing to CD44 as a promising therapeutic target for T2DM-associated chronic wounds.

Advances in tissue biology have revealed remarkable transcriptomic heterogeneity of endothelial cells between and within organ systems. This necessitates more precise models of organ-specific endothelium to understand the pathogenesis of genetic vascular disorders, such as pulmonary hypertension (PH), where gene-disease associations have implicated endothelial cell dysfunction as a key driver of disease pathogenesis. Towards this end, human induced pluripotent stem cells (hiPSCs) hold immense promise for PH disease modeling where hiPSCs are generated from an affected individual and undergo gene correction to generate syngeneic controls that can be differentiated to endothelial cells (hiEndos), providing a limitless source of material for downstream studies; however, the ability to generate lung-specific hiEndos to model pulmonary vascular disease has been limited. To overcome this challenge, we developed a chimeric human-mouse lung vascular model wherein hiEndos are first patterned via BMP9-induced signaling towards a lung-like molecular phenotype in vitro and are then intravenously transplanted into the mouse lung vasculature in vivo to generate orthotopic lung-specific endothelium for downstream studies. Transplanted pre-patterned hiEndos form functional connections to the native mouse lung vasculature and upregulate differentiated lung-specific molecular cell subtype profiles that include capillary- and arterial-like cell populations. To apply this approach for disease modeling, we generated new hiPSC lines by reprogramming fibroblasts from individuals of the 2001 landmark cohort of BMPR2 gene variant-associated PH and developed a novel in vivo competitive lung endothelial reconstitution assay to quantify functional and molecular differences between human BMPR2-variant vs syngeneic gene-corrected/edited hiEndos. Our approach revealed novel insights into PH disease pathogenesis, not previously evident with prior models, including BMPR2 variant-induced in vivo defects in human lung capillary gene expression, elevated lncRNA H19 expression, increased AHR signaling, and diminished functional capacity to repopulate the pulmonary vascular endothelium.

Fibroblasts are traditionally considered structural cells that maintain tissue homeostasis and facilitate repair. However, accumulating evidence suggests they also participate in innate immunity, although their pattern recognition capabilities remain incompletely characterized. Here, we systematically assessed the innate immune responses of commercially available primary human dermal fibroblasts from a male and a female donor. Fibroblasts were stimulated with a panel of microbe-associated molecular patterns (MAMPs) targeting various pattern recognition receptors (PRRs), including Toll-like receptors (TLRs), NOD-like receptors (NODs), Alpha kinase 1 (ALPK1) and STING. Innate immune activation was quantified by measuring the nuclear translocation of NF-{kappa}B via high content microscopy and cytokines and chemokines secretion by ELISA; baseline PRRs expression was determined by quantitative PCR. Only a restricted subset of agonists, specifically E. coli LPS (TLR4), Poly I:C (TLR3 / RIG-I) and unexpectedly ADP heptose (ALPK1) induced robust NF-{kappa}B activation and secretion of the chemokines IL-8 and MCP-1. Apart from IL-6 and RANTES, which were produced exclusively following Poly I:C stimulation, pro-inflammatory cytokines (IL-1{beta}, TNF, IFN-{beta}) and the anti-inflammatory cytokine IL-10 remained undetectable. Consistent with this limited reactivity, qPCR of PRRs revealed basal expression of TLR4 and ALPK1, whereas most other receptors were expressed at very low or undetectable levels. Notably, NOD1 was highly expressed although no cell activation was observed with several NOD1 agonists. Dose-response analysis revealed surprisingly high sensitivity to LPS. In conclusion, primary human dermal fibroblasts exhibit a highly selective but sensitive innate immune response, largely restricted to chemokine production upon PRR activation. This unexpected dissociation between chemokine and cytokine responses suggests that fibroblasts function as sentinel cells in early skin defense, capable of detecting key microbial patterns at low concentrations, to orchestrate local immune surveillance. Further investigation into interindividual variability and context-dependent activation is needed.

An autocrine pro-adhesive/pro-contractile signaling loop, through the mechanosensitive transcriptional cofactor YAP, promotes fibrosis. The CCN family of matricellular proteins modify adhesive signaling. Of these, CCN3 is antifibrotic. We show that BLR-200, a CCN3-derived peptide, has anti-fibrotic properties in the bleomycin-induced model of scleroderma skin fibrosis. In vitro, BLR-200 delayed, but did not abolish, fibroblast adhesion to collagen and nuclear YAP localization. In vivo, BLR-200 prevented/treated bleomycin-induced skin fibrosis, and reduced bleomycin-induced expression of profibrotic genes including alpha-smooth muscle actin, CCN1 and CCN2. Lineage tracing and scRNA-seq analyses revealed that the myofibroblasts in this model were quantitatively derived from collagen-lineage Pi16+/Col15+ve fibroblasts. BLR-200 prevented myofibroblast differentiation in this model and trajectory of fibroblasts toward a Sfrp2-positive subset, a cell type associated with poor clinical outcome. BLR-200 impairs YAP activation in vitro and appearance of translationally-relevant fibroblast subtypes in vivo and is a novel anti-fibrotic agent for SSc skin fibrosis.

Hidradenitis suppurativa (HS) is a chronic, debilitating, inflammatory skin disorder. Medications have been reported in association with cases of new-onset HS or exacerbation of existing disease; however, the extent of this risk is unclear. We queried the FDA adverse event reporting system (FAERS) from 2003-2023 to identify drug-specific reporting signals for HS. We stratified reports by whether HS was listed as an indication (Drug-Worsened, DW) or not (Drug-Induced, DI) to distinguish disease flares from de novo disease. Primary suspect drugs with > 3 HS reports were included. Disproportionality was quantified using reporting odds ratio (ROR) with Wald 95% confidence intervals (CI). Time-to-onset was also evaluated. We identified 5,529 HS reports: 3,725 DW and 1,804 DI. Females comprised 63% (mean age 41) and the US was the top reporting country (81.8% DW; 53.66% DI). In the DI group, statistically significant signals were observed for immunomodulators also used to treat HS including adalimumab (n=506, ROR= 12.6 [11.3-14.0]) infliximab (n=108, ROR=8.2 [6.7-10.0]), and secukinumab (n=79, ROR=6.6 [5.2-8.2]), consistent with paradoxical reactions. Median time-to-onset was 22 days for secukinumab, compared to 312 and 319 days for adalimumab and infliximab. Signals were also identified for isotretinoin (n=28, ROR= 6.2 [4.2-8.9]), and for antineoplastic agents including cytarabine (n=25, ROR= 24.7 [16.6-36.6]) and omacetaxine (n=8; ROR= 7416 [CI 2923-18816]), which may reflect reported eccrine hidradenitis. In the DW group, adalimumab (n=2967), secukinumab (n=67), and infliximab (n=57) predominated but displayed lower RORs (0.72-1.4), likely reflecting indication bias. While mechanisms of drug-associated HS require further clarification, our findings demonstrate significant associations and highlight the importance of dermatologic monitoring when initiating certain agents.

Most patients with cancer of unknown primary (CUP) still receive platinum-based chemotherapy and have a poor prognosis, with overall survival of less than one year. Recent studies suggest improved outcomes with molecularly guided or site-specific therapies informed by molecular tissue profiling. Here, we analyzed ctDNA from 190 CUP patients using an integrated genomic and epigenomic assay to identify actionable alterations and predict tissue-of-origin (ToO). Integration of actionable biomarkers, ToO prediction and clinical data yielded diagnostic, prognostic or therapeutic information in 90% of unfavorable CUP cases and 88% of patients analyzed at first diagnosis. High ctDNA tumor fraction was associated with poorer prognosis in both favorable and unfavorable CUP. These findings highlight the clinical utility of ctDNA analysis for therapeutic decision-making in CUP and support its incorporation into the diagnostic work-up, particularly when tissue samples are unavailable or insufficient for molecular testing.

The skin microbiome shapes local immunity, but the mechanisms of microbiome-immune crosstalk remain poorly understood. A major barrier to discovery is the lack of approaches that enable simultaneous, longitudinal measurement of microbes and immune cells from the same tissue without disrupting barrier integrity. Here we present a hydrogel-coated microneedle (MN) patch that enables minimally invasive co-sampling of viable microbes, immune cells, and interstitial fluid from skin. In humans, the patches were well tolerated and preserved inter-individual microbial signatures. Murine models colonized with commensal Staphylococcus epidermidis and the opportunistic pathogen Staphylococcus aureus, revealed distinct immune trajectories during commensal colonization, pathogen challenge, and commensal-pathogen co-colonization. Pathogen colonization drives progressive inflammatory amplification, whereas commensal exposure induces controlled immune activation that stabilizes over time. Notably, S. epidermidis reshapes pathogen-induced responses, producing a transient immune activation followed by attenuation of inflammation. These results establish MN sampling as a strategy to resolve immune-microbiome dynamics in barrier tissues and provide a framework for mechanistic studies of host-microbe interactions in health and disease.

Cancer treatment has shifted toward personalized therapy based on molecular profiling, particularly in advanced disease. Existing circulating tumor DNA panels are often broad, generating many non-actionable variants and incurring costs that limit routine use in molecular tumor boards. We developed and validated a manufacturer-independent, 109-gene liquid biopsy-centered pan-cancer open next generation sequencing panel (LION panel), combined with an in-house bioinformatic pipeline to support clinical decision-making. A total of 87 samples were analyzed, including 17 reference samples, 21 healthy blood donor controls, and 49 patient samples including nine tumor entities. The LION panel achieved 92% sensitivity and 99% specificity in reference samples, with high concordance to digital droplet PCR (r = 0.99). It detected variant allele frequencies as low as 0.05% (tumor-informed) and 0.5% (tumor-uninformed). Clinical concordance reached 82% with blood-based digital droplet PCR and 75% with whole exome tissue sequencing. In representative cases, variant dynamics correlated with disease progression and revealed additional targetable variants. Overall, the LION panel supports clinical decision-making by enabling identification of targetable variants, disease monitoring, and detection of treatment resistance, particularly when tumor tissue is unavailable.

Background: Cutaneous melanoma is the most aggressive malignant skin tumor, and metastasis represents the primary cause of patient mortality. Bisphenol S (BPS) has an unclear influence on melanoma metastasis and its underlying molecular mechanisms. Methods: Potential BPS targets were predicted using the SEA, SwissTargetPrediction, and SuperPred databases. Based on TCGA-SKCM transcriptomic data, differential expression analysis was performed, and Weighted Gene Co-expression Network Analysis (WGCNA) was employed to construct a gene co-expression network. Candidate genes were obtained by integrating BPS-related targets, differentially expressed genes (DEGs), module genes, and univariate Cox regression genes, followed by Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and protein-protein interaction (PPI) network construction. Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression was applied to screen core prognostic genes and construct a risk prediction model. Further analyses included network construction, molecular docking, and 100 ns molecular dynamics (MD) simulation. Results: Integration of BPS-related targets, DEGs, WGCNA module genes, and Cox regression results yielded 13 candidate genes enriched in kinase activity regulation and melanoma-related pathways. LASSO-Cox regression ultimately identified three core prognostic genes--ABCB1, PIM2, and TSHR--all significantly upregulated in metastatic tissues, with area under the curve (AUC) values of approximately 0.7. High-expression patients exhibited significantly better overall survival than low-expression patients (P < 0.05). A nomogram incorporating the three genes and clinical parameters demonstrated good calibration performance. Within the ceRNA network, MALAT1 and hsa-miR-155-5p were identified as key regulatory molecules, and 37 potential transcription factors were predicted, including CEBPA, JUN, and STAT3. Molecular docking revealed strong binding affinities of BPS toward ABCB1 , PIM2, and TSHR, and MD simulations confirmed the structural stability of all three complexes. Conclusion: ABCB1, PIM2, and TSHR are the core target genes through which BPS influences melanoma metastasis via multidrug resistance, kinase signaling, and receptor-mediated signal transduction. The prognostic model based on these three genes demonstrates good clinical applicability, and the ceRNA and transcription factor regulatory networks provide a systematic molecular basis for understanding the association between BPS exposure and melanoma metastasis.

Background: Cases requiring 13 or more tissue sections in Mohs micrographic surgery (MMS) demand extended operative time, additional resources, and often specialised closure techniques. Pre-operative identification of such cases would improve surgical scheduling, resource allocation, and patient counselling. We aimed to develop and validate a machine learning prediction tool using pre-operative clinical features to identify cases likely to require13 sections. Objectives: To develop and validate machine learning models for predicting which Mohs procedures will require 13 sections, using pre-operative clinical features, and to identify key predictive factors. Methods: We analysed 408 consecutive Mohs procedures with 16 pre-operative clinical variables. Thirty machine learning algorithms were evaluated, including ensemble methods (Stacking, Voting), gradient boosting (XGBoost, LightGBM, CatBoost), neural networks (3-7 layers), support vector machines, and traditional classifiers. Model performance was assessed using 5-fold stratified cross-validation and independent test set evaluation. Feature importance was determined using SHAP (SHapley Additive exPlanations) analysis. Results: The stacking ensemble achieved the highest cross-validation AUC of 0.891 (95% CI: 0.849-0.934) and test AUC of 0.884. Tumour area (cm2), calculated using the ellipse formula to approximate clinical tumour morphology, emerged as the strongest predictor (SHAP importance: 0.141), followed by tumour size dimensions (0.086 and 0.068), aggressive histopathology (0.046), and recurrence status (0.035). Wide neural network architectures (5-layer) outperformed deeper configurations (7-layer). The model demonstrated 70.7% high-confidence predictions with uncertainty <15%. Conclusions: Machine learning models using pre-operative clinical features can accurately predict which Mohs procedures will require 13 or more sections. The stacking ensemble approach provides robust predictions suitable for clinical decision support. External validation in multi-centre cohorts with diverse patient populations and practice patterns is warranted to assess model generalisability.

BACKGROUNDMyocardial fibrosis, a pathological hallmark of adverse cardiac remodeling and heart failure, has been conventionally attributed to the activation of resident fibroblasts. Although recent studies suggest contributions from non-fibroblast lineages, direct in vivo genetic evidence that cardiomyocytes can undergo a mesenchymal-like fate transition during myocardial fibrosis remains absent. This study aims to investigate whether such a transition occurs and to elucidate the underlying regulatory mechanisms. METHODSHuman myocardial infarction (MI) tissues were analyzed by immunohistochemistry and integrated with public single-nucleus RNA sequencing (snRNA-seq) data to detect mesenchymal-like signatures in cardiomyocytes. Genetic lineage-tracing was performed in MI mice, and in cardiomyocyte-specific Hgs (hepatocyte growth factor-regulated tyrosine kinase substrate) gene knockout mice, to map the fate of cardiomyocyte-derived cells. Mechanistic insights were obtained through proteomic and snRNA-seq analysis of Hgs knockout hearts and validated through gain- and loss-of-function experiments targeting Aldh1a2 (aldehyde dehydrogenase 1 family member A2). RESULTSIn human MI samples, a subset of cardiomyocytes showed reduced expression of cardiomyocyte markers concurrent with acquisition of mesenchymal-associated markers. Genetic lineage tracing demonstrated that adult cardiomyocytes can adopt a mesenchymal-like cell fate during post-MI remodeling. We identify HGS as a factor constraining this transition. Hgs knockout in adult cardiomyocytes upregulated Aldh1a2, triggered the mesenchymal-like fate transition, and gave rise to cells expressing markers of activated fibroblasts or osteoblasts, accompanied by pronounced myocardial fibrosis and calcification. Forced Aldh1a2 overexpression in cardiomyocytes drove the mesenchymal-like fate transition in vitro and in vivo, whereas Aldh1a2 deletion in cardiomyocytes mitigated MI-induced myocardial fibrosis. CONCLUSIONSThis study provides in vivo genetic evidence that adult cardiomyocytes possess the capacity to undergo a mesenchymal-like fate transition under pathological conditions. Our data suggest that HGS and ALDH1A2 serve as regulators of the transition, offering a new basis for understanding cellular and molecular mechanisms of myocardial fibrosis. Novelty and SignificanceO_ST_ABSWhat Is Known?C_ST_ABSO_LIMyocardial fibrosis is primarily driven by resident fibroblast activation, with additional contributions from cardiac CD34+ cells, pericytes, and macrophages. C_LIO_LIAdult cardiomyocytes exhibit phenotypic plasticity and transdifferentiate into epicardial-like or pacemaker cells under specific conditions. C_LI What New Information Does This Article Contribute?O_LIA subset of cardiomyocytes adopts a mesenchymal-like cell fate during myocardial fibrosis, marked by downregulation of cardiomyocyte identity markers and loss of aligned cell-cell contacts. C_LIO_LIThese cells acquire mesenchymal morphology and markers, ECM components, migratory gene signatures, and proliferative capacity. C_LIO_LIHGS and ALDH1A2 act as regulators of this mesenchymal-like fate transition. C_LI Myocardial fibrosis drives heart failure progression, yet the cellular sources of pathological fibroblasts remain incompletely defined. Here, we demonstrate that a subset of cardiomyocytes adopts a mesenchymal-like cell fate during myocardial fibrosis by using an integrated approach combining human MI samples, murine genetic lineage tracing, and snRNA-seq. Mechanistically, we identify HGS and ALDH1A2 as regulators of this transition. Cardiomyocyte-specific Hgs deletion upregulates Aldh1a2, triggering the mesenchymal-like fate transition. Furthermore, Aldh1a2 overexpression drives this transition, while its deletion attenuates MI-induced fibrosis. These findings reveal a previously unrecognized plasticity of adult cardiomyocytes and identify potential therapeutic targets for fibrotic heart disease.

Conventional short-read sequencing cannot determine whether co-occurring variants within a cancer gene reside on the same allele (cis) or on opposing alleles (trans), a distinction with direct biological and therapeutic consequences. Trans configurations confirm biallelic tumor suppressor inactivation and inform therapy selection, while cis configurations generate compound oncogenic alleles with enhanced activity. We analyzed 768 patients with prostate, breast, or ovarian cancers in the PROBLEM cohort, using mutational signatures to nominate cryptic genomic instability cases where the causative biallelic event was not apparent from short-read sequencing. Long-read nanopore sequencing resolved 32 of 46 cryptic cases (69.6%), leveraging its unique advantages in direct methylation detection, long insertion resolution, and complex structural variant characterization, confirming trans biallelic inactivation in all resolved tumor suppressor cases. Systematic analysis of 4,496 MiOncoSeq samples identified 17,519 multi-hit gene pairs, of which 78.7% exceeded the 500 bp short-read phasing limit. Long-read phasing further revealed recurrent compound cis oncogenic alleles in NOTCH1, PIK3CA, PDGFRB, and KIT with functionally synergistic activity. Haplotype phasing resolves a systematically overlooked gap in cancer variant interpretation and warrants broader integration into precision oncology workflows. Statement of SignificanceShort-read sequencing cannot resolve whether co-occurring variants within a cancer gene are cis or trans, a distinction critical for clinical interpretation. Long-read nanopore sequencing addresses this gap through direct haplotype phasing, methylation detection, and complex structural variant resolution, confirming biallelic tumor suppressor inactivation and revealing compound cis oncogenic alleles with enhanced activity.

Primary genetic mitochondrial diseases (GMDs) are a clinically and genetically diverse group of diseases estimated to impact over 1 in 4,000 individuals. Leigh syndrome (LS) is the most common pediatric presentation of GMD. LS typically presents within the first years of life and is a severe progressive multi-system disorder. Symmetric progressive inflammatory brain lesions are a defining feature of the disease. Patients can also present with seizures, metabolic dysfunction, muscle weakness, and other symptoms. No effective clinical treatments currently exist. Recent data from the Ndufs4(-/-) mouse model shows that peripheral macrophages contribute to brain lesions in LS, that disease is causally driven by innate immune populations, and that depletion of innate immune cells prevents LS disease. However, the precise mechanisms underlying immune activation remain unknown. Certain mitochondrial macromolecules retain bacterial signatures and can act as potent agonists for innate immune pathways. For example, cytoplasmic mitochondrial RNA and mitochondrial DNA are detected by Toll-like receptors (TLRs) 7 and 9, respectively, at the endosome. Accordingly, these are considered strong candidates for mediating innate immune activation in LS. Here, we generated TLR signaling deficient Ndufs4(-/-)/MyD88(-/-) animals to assess whether TLR signaling plays a role in disease onset or progression in LS. Loss of MyD88 in Ndufs4(-/-) animals statistically significantly increased survival and delayed the onset of some symptoms, but the benefits were modest compared to CSF1R inhibition from prior work. We conclude that Myd88-mediated immune signaling is not a primary driver of LS. Notably, prophylactic enrofloxacin treatment, which was necessary for production of innate immune deficient MyD88(-/-) animals, modestly decreased survival and accelerated disease. The impact of enrofloxacin and similar drugs in the context of mitochondrial disease warrants further investigation.

Myocardial development requires precise modulation of its growth and maturation by the mechanical loads within cardiac cycle, including preload and afterload. However, the mechanisms by which these natural cardiac loads interact to simultaneously govern growth and maturation of the developing myocardium in both cellular and mesoscale levels remain poorly understood. Here, we developed a naturally engineered fetal ventricular tissue (NFVT) platform that enables the application of afterload under dynamic preload using cyclic stretching with an asymmetrical duty cycle (asymmetrically cycled preload) to better replicate the natural cardiac loading in chick NFVT. Our results showed that low afterload (LA) enhanced NFVT contractile function with sustained tissue growth and improved cardiomyocyte maturation while suppressing fibrosis phenotypes. These effects were associated with reduced YAP1 and NOTCH activation in cardiomyocytes and enhanced tissue architecture. In contrast, high afterload (HA) induced contractile impairment with fibrotic remodeling through activation of cardiomyocyte PIEZO1/YAP1 signaling and sustained fibroblast entanglement. TeaserLow afterload under asymmetrically cycled preload promotes NFVTs contractile function with sustained tissue growth and cardiomyocyte maturation while suppressing fibrosis phenotypes through regulation of cellular mechanotransduction, including minimal PIEZO1 expression and inhibited YAP1 and NOTCH activation in cardiomyocytes, and improvement of collective cellular organization.

Keloids are fibroproliferative skin disorders arising following dermal injury that extend beyond the original wound margins. Their pathogenesis remains poorly understood, and current treatments are associated with high recurrence rates. Identifying transcriptomic biomarkers that distinguish keloids from other skin and scar phenotypes may provide insight into disease mechanisms and facilitate the development of targeted therapeutic approaches. However, previous transcriptomic studies have often been limited by small sample sizes, pairwise comparisons between tissue classes, heterogeneous data-integration strategies, and a reliance on conventional differential gene expression (DGE) analysis. Here, we employed a multi-stage machine learning (ML) workflow for robust keloid biomarker discovery using transcriptomic datasets derived from both bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq). We assembled and harmonized, to the best of our knowledge, the largest curated cross-study keloid transcriptomic cohort currently available, comprising 81 samples from 13 independent studies spanning four clinically relevant tissue classes: normal skin, normotrophic scar, hypertrophic scar, and keloid scar. Through study-aware cross-validation, feature selection, partition-stability analysis, and bootstrap validation across multiple ML classifiers, we identified a panel of eight highly consistent biomarkers capable of distinguishing keloid from non-keloid samples. These biomarkers were associated with dysregulation of extracellular matrix homeostasis, fibrosis-resolution pathways, vascular remodelling, and metabolic reprogramming. Comparison with conventional DGE analysis demonstrated substantial agreement while also highlighting important differences between the two approaches. In particular, FASN was consistently identified by the ML workflow as an upregulated discriminatory biomarker despite exhibiting weak, non-significant differential expression in the DGE analysis. Cell-type-specific analysis further supported this finding, revealing significant FASN upregulation in fibroblast and vascular endothelial populations. These results demonstrate that ML and DGE capture complementary aspects of transcriptomic variation. This study provides a robust strategy for cross-study transcriptomic biomarker discovery and identifies candidate genes and pathways for future mechanistic and therapeutic investigation in keloids. 1 Author SummaryKeloids are abnormal scars that continue to grow beyond the original wound and can be difficult to treat because they frequently recur after therapy. Although many studies have investigated the biology of keloids, the molecular mechanisms that distinguish them from other scar types remain incompletely understood. Identifying biomarkers involved in keloid formation may help inform improved treatment strategies. Previous transcriptomic studies have often been limited by small sample sizes and inconsistent analytical approaches. In this study, we combined gene-expression data from multiple independent studies to create, to the best of our knowledge, the largest cross-study transcriptomic collection available for keloid analysis. We then applied several machine learning approaches to identify genes that consistently distinguished keloids from other skin and scar phenotypes. The identified biomarkers were associated with extracellular matrix remodeling, fibrosis, vascular function, and cellular metabolism. One gene involved in fatty-acid synthesis, FASN, was repeatedly identified by the machine learning analyses despite being overlooked by conventional gene-expression methods. Additional single-cell analyses confirmed elevated FASN expression in specific cell populations within keloid tissue. More broadly, this work provides a strategy for discovering robust biomarkers from heterogeneous biological datasets and identifies molecular targets for future studies of keloid disease.

Kindlin-1, encoded by FERMT1, is an essential integrin co-activator that regulates cell-extracellular matrix (ECM) adhesion, tissue architecture, and microenvironment signalling. Loss-of-function mutations in FERMT1 cause Kindler epidermolysis bullosa, which is strongly associated with aggressive cutaneous squamous cell carcinoma (cSCC). Although Kindlin-1 deficiency promotes hypoxia and invasion, the impacts on ECM-vascular organisation and oxygen homeostasis are not known. Here, using genetic deletion of Kindlin-1 in a murine model of cSCC across 2D cultures, 3D spheroids, and in vivo tumours, combined with collagen and vascular imaging and spatial mixed-effects modelling, we show that Kindlin-1 loss uncouples ECM-vascular regulation, driving hypoxia and tumour progression. Tumours in which Kindlin-1 was deleted displayed a dense but dysfunctional vascular network, with reduced tissue-to-vessel and inter-bifurcation distances, increased vessel alignment, and persistent hypoxia despite increased vascular density. Collagen deposition was reduced and fibres were straighter, indicating a simplified, invasion-permissive matrix. Hypoxia increased Vegfa and Angpt1 expression while reducing Col1a1, and hypoxia-responsive spheroids confirmed greater hypoxia and invasiveness in Kindlin-1-deficient cells. Transcriptomic analysis revealed enrichment of ECM degradation and vascular dysfunction pathways, including upregulation of matrix-remodelling and vascular permeability genes such as Mmp13, Mmp3, and Ptgs2, alongside reduced collagen-associated and vascular homeostasis genes. Spatial modelling further showed disrupted collagen-vascular coupling and an association between hypoxia and reduced vessel diameter, consistent with dysfunctional angiogenesis rather than improved perfusion. These changes arose early and independently of tumour size, establishing impaired integrin activation as a central mechanism linking ECM degradation, vascular dysfunction, and sustained hypoxia in aggressive cSCC.

Colorectal cancer (CRC) remains a major cause of cancer mortality, with limited options for poor-prognosis subtypes such as CMS4. Antigen-targeted therapies show promise but tend to fail due to inadequate target selection and insufficient patient stratification. Effective prioritization requires large harmonized data capturing CRC heterogeneity - a resource that is currently lacking. To address this need, we built a harmonized multi-omic CRC knowledge base and applied a scalable discovery pipeline to identify antigen targets specifically associated with CMS4 biology and with strong translational potential. We constructed a harmonized CRC atlas by integrating 79 transcriptomics datasets (5,033 tumors, 161 normal samples) using proprietary AI-powered data scouting, integration, and curation technologies. Consensus Molecular Subtypes (CMS) were inferred to capture CMS4-specific expression patterns and this atlas was then combined with 3 bulk RNA-seq reference datasets, 2 single-cell atlases, and 8 protein annotation databases to form a unified multi-omic CRC knowledge base of unmatched scale. From this integrated system, we identified genes differentially expressed in CMS4 patients encoding druggable cell-surface proteins, which we then prioritized using a weighted efficacy- and safety-based scoring model. We identified 236 CMS4-enriched candidates, including 124 not detectable at the CRC-wide level, demonstrating the added resolution gained through subtype stratification. Recovery of known investigational CRC (LGR5, MET, TACSTD2) and CMS4-associated targets of clinical emerging interest (PDGFRB, ALK5/TGFBR1, FAP) support the biological and methodological validity of our approach. Benchmarking against thresholds from FDA-approved pan-cancer targets and terminated trials identified 32 candidates with comparable or superior therapeutic profiles. Among these, 11 were enriched for CMS4-defining pathways, including epithelial-mesenchymal transition, angiogenesis, and stromal invasion, and 5 showed strong profile similarity to established CRC and CMS4 benchmarks. After extensive data exploration, particularly promising candidates were shortlisted for further validation. This work shows that CMS4-focused molecular stratification, when combined with an unprecedentedly large harmonized multi-omic knowledge base, yields a refined set of antigen candidates with enhanced specificity, safety, and biological relevance. The prioritized targets illustrate the power of subtype-resolved discovery to uncover clinically actionable insights. Our pipelines modular design can extend to other tumor contexts, offering a robust foundation for accelerating targeted therapy development.

Skeletal muscle possesses remarkable regenerative capacity. However, in limb-girdle muscular dystrophy-2F (LGMD2F), this capacity is compromised by persistent innate immune activation, whose transcriptional landscape remains unexplored. In parallel, (-)-Epicatechin has emerged as a promising compound with beneficial effects on muscle and notable anti-inflammatory properties. We therefore used (-)-Epicatechin treatment to test whether it can alleviate LGMD2F-associated transcriptional and immune dysregulation. Here we provide the first transcriptomic characterization of LGMD2F using the Sgcd-/- mouse model, along with the first RNA-sequencing-based evaluation of (-)-Epicatechin treatment. We profiled two functionally distinct muscles -- the soleus and EDL -- through bulk RNA-sequencing coupled with immune cell-deconvolution. Sgcd-/- muscles exhibited marked transcriptional dysregulation, more pronounced in the soleus and associated with enhanced innate immune signaling. (-)-Epicatechin induced a muscle- and genotype-dependent transcriptional response: in wild-type animals, the EDL displayed the highest number of differentially expressed transcripts, whereas in Sgcd-/- mice, the soleus showed the most prominent response. This shift was accompanied by downregulation of Toll-like receptor and RIG-I-like receptor pathways, along with suppression of NF-{kappa}B2 and interferon-stimulated genes. Together, these findings identify innate immune overactivation as a central feature of LGMD2F and reveal (-)-Epicatechin as a context-dependent modulator of muscle-specific transcriptional responses.