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PubMed2026

Spatial proteomics reveals four-stage molecular evolution in cancer immunotherapy-related gastritis.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have transformed cancer treatment, yet immune-related adverse events (irAEs) including immunotherapy-related gastritis (IRAEG) pose significant clinical challenges-often necessitating treatment interruption that may compromise antitumor efficacy. IRAEG presents with atypical symptoms, lacks specific biomarkers, and shows histopathological overlap with other forms of gastritis, complicating diagnosis and management. Despite increasing clinical recognition, a systematic understanding of spatial molecular alterations across the full disease course remains limited. Here, we used spatial proteomics to map the molecular landscape of IRAEG during disease progression and to define stage-specific patterns of molecular evolution relevant to cancer immunotherapy management. METHODS: We analyzed tissue samples from seven patients, including four non-immunotherapy-related gastritis controls and three cancer patients who developed IRAEG following ICI therapy for solid tumors, sampled longitudinally across four disease stages: baseline (G1), acute severe inflammation (G2), early recovery (G3), and complete recovery (G4). Using laser capture microdissection coupled with data-independent acquisition mass spectrometry, we profiled 177 spatially resolved gastric tissue regions. Multiplex immunohistochemistry and immunofluorescence characterized features of the immune microenvironment, while Gene Ontology, KEGG pathway analysis, Gene Set Variation Analysis, and xCell inference enabled functional, metabolic, and immune profiling. Key immune and NET-related findings were further validated by multiplex immunofluorescence in an independent, expanded cohort of IRAEG and non-immunotherapy-related gastritis samples. RESULTS: IRAEG was characterized by widespread HLA molecule activation and enhanced antigen processing, resembling the immune phenotype observed in organ transplant rejection. The acute G2 stage exhibited excessive neutrophil extracellular trap formation, profound metabolic suppression, and collapse of immune homeostasis-features that may inform early intervention strategies to preserve ICI treatment continuity. During early recovery (G3), inflammatory injury transitioned toward repair, marked by activation of fatty acid metabolism and PPAR signaling. Notably, even at complete clinical recovery (G4), more than 1,000 proteins remained differentially expressed, reflecting sustained enhancement of metabolic and immune functions and establishing a distinct molecular "memory" state with implications for ICI rechallenge decisions. CONCLUSIONS: These findings define four molecularly distinct stages of IRAEG progression and recovery. The stage-specific signatures identified here serve as candidate biomarkers for diagnosis, disease staging, and therapeutic response assessment, and may guide clinical decisions regarding irAE management, treatment modification, and safe ICI rechallenge to support continued antitumor therapy.

Humans↗

PubMed2026

Integrated landscape of salivary metagenome and multi-biofluid metabolome characterizes a microbial-metabolic axis in upper gastrointestinal cancer progression.

BACKGROUND: Upper gastrointestinal cancer (UGIC) imposes a major global health burden, yet the stage-specific molecular changes along the microbial-metabolic axis remain limited understood. We aimed to delineate this molecular landscape across UGIC progression and evaluate its potential as non-invasive methods for precision screening. RESULTS: Derived from a multi-center population-based UGIC screening program, we enrolled 420 individuals, stratified into normal, low-grade intraepithelial neoplasia (LGIN), high-grade intraepithelial neoplasia (HGIN), and UGIC (n = 105 per group). Integrated salivary metagenomics and paired salivary/plasma metabolomics were performed to capture local and systemic dysregulation. We uncovered distinct stage-specific divergence during UGIC progression: profound remodeling of the salivary microbiota (104 differential species) and salivary metabolomics (80 differential metabolites) initiated early at the LGIN stage, whereas plasma metabolic dysregulation (40 differential metabolites) peaked significantly later at the HGIN stage. Integrative analysis revealed salivary microbiota related more closely with salivary metabolome than plasma metabolome. Moreover, statistical evidence suggested that dysbiotic salivary microbiota was associated with altered lysine- and tryptophan-related catabolic pathways converging on Acetyl-CoA-related metabolic nodes, supporting a potential metabolic mechanism in precancerous lesions. Finally, the discriminative model integrating metagenomic and metabolomic markers demonstrated promising diagnostic performance in distinguishing these precancerous lesions (LGIN: area under the curve [AUC] = 0.83; HGIN: AUC = 0.77) and UGIC (AUC = 0.76) from normal. CONCLUSION: This study characterizes a stage-specific microbial-metabolic axis that facilitates the comprehensive understanding of UGIC pathogenesis. These multi-biofluid signatures offer a promising non-invasive triage strategy for detecting precancerous lesions and optimizing endoscopic resource allocation. Video Abstract.

Female↗

PubMed2026

Early Cardiomyopathy in Prediabetic NDPK-B-Deficient Mice Is Associated with Remodeling of the Mitochondrial O-GlcNAc Proteome.

Diabetic cardiomyopathy (DCM) is characterized by myocardial remodeling that may already be evident during prediabetes, yet the molecular alterations accompanying these early changes remain poorly understood. The present study examined mouse models of Nucleoside diphosphate kinase B (NDPK-B)-deficient prediabetes and streptozotocin-induced diabetes using O-GlcNAc-associated proteomic profiling to define stage-specific molecular alterations during the progression from prediabetic to diabetic cardiomyopathy. Both models exhibited increased left ventricular extracellular matrix deposition and impaired diastolic function, together with activation of the hexosamine biosynthesis pathway. Profiling of O-GlcNAc-associated proteins uncovered extensive remodeling of the mitochondrial proteome already at the prediabetic stage, with respiratory complex I among the most prominently altered targets, alongside changes in substrate metabolism and inflammatory signaling. In overt DCM, the putative O-GlcNAc proteomic profile was associated with a shift toward wider lipid-dependent metabolic reprogramming and remodeling of mitochondrial proteins. These findings identify early remodeling of the mitochondrial O-GlcNAc-associated proteome as a molecular signature of prediabetic cardiomyopathy and highlight respiratory complex I proteins as candidate targets for future mechanistic investigations.

Animals↗

PubMed2026

Proteo-metabolomic integration identifies stage-specific candidate biomarkers for Parkinson's disease.

Parkinson's disease (PD) is a progressive neurodegenerative disorder with a prolonged prodromal phase and complex motor symptoms. Despite improved clinical criteria, early diagnosis and longitudinal monitoring remain challenging. While cerebrospinal fluid (CSF) and plasma metabolites and proteins show biomarker potential, their utility in predictive models is insufficiently characterized. We employed a secondary computational approach to integrate proteometabolomic profiles from CSF and plasma samples of >1100 Parkinson's Progression Markers Initiative (PPMI) participants. Using multi-omics machine learning, we identified biofluid-specific signatures and evaluated predictive performance. Twenty-one biomarker candidates were validated across three models (SVM, GLMNET, RF); SVM and GLMNET achieved the highest recall (83-86%) and AUCs of 0.84-0.89. Longitudinal mixed-effects modeling revealed eight candidates associated with progression across diagnostic stages. We identified a three-part molecular framework characterizing neurodegeneration: a diagnostic subpanel reflecting early microbiome dysregulation (secretory granins and metabolites) and synaptic breakdown; a second subpanel monitoring phenoconversion via neurogenesis precursors and extracellular matrix proteins; and a third subpanel tracking progression through chronic neuroinflammation and immune activation. This integrated multi-omics approach provides a robust framework for stage-specific PD monitoring and potential clinical deployment.

Journal Article↗

PubMed2026

Gut microbiota dynamics and metabolic pathways associated with bleomycin-induced pulmonary fibrosis progression.

BACKGROUND: Pulmonary fibrosis (PF) is a progressive respiratory disease characterized by epithelial injury, aberrant repair and excessive extracellular matrix deposition. Although the gut-lung axis is increasingly implicated in respiratory disorders, stage-resolved characterization of gut microbiota taxonomic and functional potential during PF development is limited. METHODS: We established a bleomycin-induced murine PF model and performed cross-sectional shotgun metagenomic sequencing of fecal samples from separate cohorts at three defined stages: baseline (control), day 7 (early fibrosis; M7), and day 14 (established fibrosis; M14). Microbial taxonomy, alpha/beta diversity, and predicted functional capacity were inferred using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Carbohydrate-Active enZymes (CAZy) annotations; associations were assessed using Procrustes and Spearman correlation analyses. RESULTS: Histopathology and immunohistochemistry confirmed progressive fibrogenesis with increased TGF-β1 and α-SMA expression. Compared with baseline, bleomycin-treated groups exhibited stage-specific shifts in gut microbial composition, including depletion of mucin-associated taxa (e.g., Prevotella, Akkermansia muciniphila) and expansion of Muribaculaceae- and Clostridiaceae-affiliated taxa. Alpha and beta diversity metrics differed across groups. KEGG/CAZy-based annotations revealed predicted, stage-dependent changes in microbial metabolic potential, including early reductions in pathways related to amino acid and glycan metabolism (M7) and later increases in predicted starch/sucrose catabolism, phosphotransferase system (PTS) representation, and secondary bile acid biosynthesis (M14). Correlation analyses linked compositional shifts to these predicted functional changes. CONCLUSION: In a stage-resolved, cross-sectional study, bleomycin-associated pulmonary fibrosis was accompanied by compositional and predicted functional alterations in the gut microbiota. These data identify candidate taxa and predicted pathways for follow-up mechanistic testing, but functional (metabolomic) and causality experiments are required to confirm whether and how microbial changes contribute to PF pathogenesis.

Animals↗

PubMed2026

mRNA therapy: A novel approach for retinal neurodegenerative diseases.

Retinal neurodegeneration remains a major cause of irreversible vision loss, yet current therapeutic options are limited in effectiveness. Although gene therapies have shown clinical potential, the overexpression platforms they rely on, such as adeno-associated virus DNA, are constrained by safety concerns, limited efficacy, and cargo size restrictions. In contrast, mRNA therapy has gained recognition as a compelling alternative, enabling rapid and efficient protein expression without the risk of genomic integration. This review synthesizes recent advances in mRNA engineering, delivery systems, and administration routes for retinal applications, and highlight strategies to enhance targeting, penetration, and controlled release through interdisciplinary collaboration between ophthalmology and bioengineering. In recent years, engineered mRNA formats, including chemically modified linear, circular, and self-amplifying RNA, can achieve higher translation efficiency within a tunable expression window. The transient nature and relatively low immunogenicity of in vitro transcribed mRNA support repeat dosing without insertional mutagenesis. Advances in nanocarriers, particularly lipid nanoparticles, have enabled preferential delivery to retinal neurons, Müller glia, and pigment epithelium via intraocular administration, while improving mRNA stability and transfection efficiency. In preclinical studies, mRNA has been widely used to deliver gene-editing tools, transcription factors, and supplementary functional proteins. In disease models such as optic nerve crush and laser-induced choroidal neovascularization, mRNA-based therapies enhance neuroprotection and suppress pathological angiogenesis in the injured retina, with favorable ocular safety profiles. However, it remains largely unexplored how the intrinsic advantages of mRNA therapy can be leveraged to develop tailored strategies for complex retinal disorders. Consistent with this gap, mRNA platforms have not yet been widely incorporated into retinal research or clinical practice. In parallel, clinical translation also lags: despite encouraging outcomes of lipid nanoparticle-mRNA formulations in preclinical models, no candidates have progressed into retinal clinical trials. This review draws on the complex pathology and therapeutic logic of retinal neurodegeneration. It proposes that mRNA therapy enables multitarget, repeatable, stage-specific interventions that align with the dynamic evolution of diseases and the requirements of combination therapy in retinal diseases. It may be used to support neuroprotection, axon regeneration, and neurovascular regulation. By integrating data across experimental models and modalities, this review outlines representative cases and experimental paradigms to guide rational trial design and carrier selection. Taken together, technical progress and evolving application strategies position mRNA therapy as a compelling therapeutic avenue for retinal neurodegeneration.

administration↗

PubMed2026

Exploring the impact of syndecans in prostate cancer: Stage-specific roles and therapeutic implications.

Syndecans (SDCs) 1-4 are a family of transmembrane heparan sulfate proteoglycans (HSPGs) that regulate cell-cell communication, adhesion, extracellular matrix organization, and signaling pathways involved in tumor biology. In prostate cancer (PCa), accumulating evidence suggests that SDCs contribute to tumor progression, therapeutic resistance, and interactions within the tumor microenvironment. However, their specific, stage-dependent roles remain incompletely understood. This review provides an integrated synthesis of current experimental and clinical evidence on SDC1-SDC4 in PCa, complemented by exploratory analyses of publicly available transcriptomic, genomic, and proteomic datasets. In contrast, copy-number alteration (CNA) strata dichotomized by the mean for SDC1, SDC2, and SDC4 showed differences in progression-free interval. Specific CNA subclasses and relationships between CNA values and SDC mRNA or protein abundance could not be determined. Proteomic pseudotime analysis further suggested that SDC4 expression increases during PCa progression, supporting its potential involvement in advanced disease. We discuss the regulation and modulation of SDCs by androgen deprivation therapy (ADT), enzymatic shedding, integrin-mediated signaling, extracellular matrix interactions, lipid signaling pathways, and microRNA networks. In particular, SDC1-microRNA interactions may influence PCa cell proliferation, cellular senescence, epithelial-mesenchymal transition (EMT), and intracellular signaling pathways. Overall, this review highlights SDCs as context-dependent regulators of PCa biology with potential relevance as biomarkers or therapeutic targets. However, clinical translation will require independent validation, standardized assays, compartment-resolved analyses, and mechanistic confirmation.

Prognosis↗

PubMed2026

Research progress and application prospects of multi-omics integration strategies in precision risk stratification of type 1 diabetes mellitus.

Type 1 diabetes (T1D) is a chronic metabolic disease mediated by autoimmunity. Its pathogenesis involves complex interactions between genetic susceptibility and environmental factors. Conventional T1D risk stratification primarily relies on genetic markers, islet autoantibodies, and glycemic indicators. Although these biomarkers remain indispensable in current clinical practice, they are often insufficient when used alone to accurately identify ultra-early high-risk individuals, predict disease progression rates, or support individualized preventive strategies. Consequently, more comprehensive molecular approaches are needed to improve precision risk stratification. In recent years, the rapid development of multi-omics technologies has provided new strategies for precise risk stratification of T1D. This narrative review critically evaluates how multi-omics integration strategies can improve precision risk stratification throughout the T1D disease continuum by integrating complementary molecular information from genomics, transcriptomics, proteomics, metabolomics, epigenomics, and the microbiome. Particular emphasis is placed on stage-specific biomarker discovery, multi-omics data integration frameworks, artificial intelligence-assisted prediction models, biomarker validation, and the opportunities and challenges associated with clinical translation. Current evidence suggests that integrated multi-omics approaches have the potential to improve risk prediction accuracy, distinguish heterogeneous disease trajectories, identify individuals at imminent risk of progression, and provide biologically informed targets for precision intervention. However, important challenges remain, including data harmonization, external validation, model interpretability, cost-effectiveness, and integration into routine clinical screening programs. Future research should prioritize prospective multicenter cohorts, standardized analytical pipelines, externally validated prediction models, and clinically interpretable multi-omics frameworks to facilitate the translation of precision risk stratification into routine T1D prevention and management.

Humans↗

PubMed2026

Integration of methylome and transcriptome reveals age-associated signatures of stage-specific dynamics and regulatory remodeling in dogs.

Aging in mammals is characterized by widespread yet coordinated epigenetic alterations. However, integrative analyses of DNA methylation and gene expression in dogs remain largely unexplored, particularly within genetically homogeneous single-breed populations. To elucidate the molecular signatures of canine aging, we profiled the genome-wide methylome and transcriptome of clinically healthy beagle dogs representing three distinct age groups. Global methylation levels were highly conserved across individuals, yet both methylation and gene expression variability increased progressively with aging. This epigenetic drift was not stochastic but structured by genomic context, as reduced CpG-gene associations indicated a gradual loss of epigenetic control over transcription. We further observed stage-related methylation change patterns across the three age groups, including early-shift, late-shift, and progressive patterns. These groups showed partially overlapping but distinct hallmark associations, suggesting links to different age-related biological processes. Together, these findings indicate that canine epigenetic aging involves multifaceted molecular changes across adulthood and support dogs as a useful model for investigating conserved molecular signatures of aging.

Beagle dog↗

PubMed2026

Beyond the "cold" barrier: Redefining the clinical paradigm of immune checkpoint inhibitor therapy in ovarian cancer.

Ovarian cancer remains an immunologically "cold" tumor, with early all-comer immune checkpoint inhibitor (ICI) trials largely negative despite underlying immunogenicity. This review takes a clinician-centric, stage-specific view linking regimen choice, treatment line, and tumor-immune context to observed outcomes. In the neoadjuvant and first-line settings, unselected ICI combinations with chemotherapy and anti-angiogenic agents failed to improve progression-free survival, whereas adding a poly (ADP-ribose) polymerase (PARP) inhibitor to ICI maintenance yielded modest gains in biomarker-enriched cohorts. In recurrent disease, single-agent ICIs produced objective response rates of 8-15%, and most randomized combinations were negative. The phase III KEYNOTE-B96 trial in platinum-resistant disease demonstrated a progression-free survival benefit in the intention-to-treat population and an overall survival benefit in tumors with programmed death ligand 1 (PD-L1) combined positive score ≥ 1 when pembrolizumab was paired with weekly paclitaxel with or without bevacizumab, underscoring the value of an immunomodulatory chemotherapy backbone in earlier lines. Ovarian clear cell carcinoma emerges as an immunotherapy-sensitive, chemo-resistant subtype that warrants dedicated stratification. We explain why single-analyte biomarkers-PD-L1, tumor mutational burden, homologous recombination deficiency/BRCA1/2-have not reliably enriched benefit and outline a multidimensional approach integrating genomic scars (e.g., mutational signature 3), immune functional state (Immunoscore, CD8⁺ tumor-infiltrating lymphocyte density and CD8⁺: regulatory T-cell ratio), and spatial architecture (inflamed, excluded, desert phenotypes). This framework aims to move beyond the all-comer era toward context-informed precision immunotherapy in ovarian cancer.

Humans↗

PubMed2026

Comparative Multiomics Analysis of Cerebral Organoid-Derived Exosomes during Organoid Maturation.

Cerebral organoids derived from human pluripotent stem cells recapitulate key features of early brain development and provide a physiologically relevant model for neurogenesis. Exosomes secreted by these organoids carry bioactive cargo and offer a noninvasive means to monitor maturation and intercellular communication. We performed comprehensive multiomics profiling of exosomes collected from cerebral organoids at defined developmental stages to evaluate their utility as biomarkers of neuronal differentiation. Metabolomic analysis revealed a progressive decline in amino acids, including glutamic acid, consistent with increased metabolic demand during neurogenesis. Lipidomic and neurosteroid profiling showed dynamic increases in phosphatidylethanolamine and pregnenolone, reflecting synaptic membrane formation and signaling. Transcriptomic and proteomic analyses identified stage-specific neurodevelopmental signatures, with key markers mirroring those of parent organoids. Collectively, cerebral organoid-derived exosomes faithfully reflect organoid maturation and provide a robust platform for tracking in vitro brain development.

Humans↗

PubMed2026

Integrative multi-omics analysis reveals lipid/metabolite dysregulation and temporal decoupling in disease progression.

Our study presents and applies a metabolomics-driven multi-omics integration strategy to elucidate dynamic pathway interactions during disease progression. We analyzed longitudinal metabolomics datasets from a Duchenne muscular dystrophy (DMD) mouse model (6-30 weeks) and an acute Bothrops asper envenomation model (1-24 h) to contrast chronic versus acute inflammation. In the DMD model, we predicted phased cross-talk between sphingolipid metabolism and neurotrophin signaling: an early proteomic surge followed by lipid-mediated amplification and a late convergence at the protein level. Arginine and proline metabolism exhibited early metabolite accumulation preceding delayed inferred protein changes, consistent with impaired nitric oxide synthesis and argininemia-like effect. We also predicted late-stage activation of the AGE-RAGE pathway in DMD, likely triggered by ceramide buildup, and an autophagy-related lipid metabolic shift at mid-stage. In the envenomation model, tryptophan-kynurenine and nicotinamide pathways for NAD⁺ biosynthesis were rapidly perturbed at the metabolite level (1-3 h) but induced corresponding predicted enzymes only by 24 h. Thyroid hormone signaling showed an early coupling of substrate availability (tyrosine surge at 1 h) with predicted stress-response proteins and a second, delayed wave of inferred transcriptional regulators at 24 h. Acute envenomation also triggered immediate glycine/serine utilization possibly for antioxidant defense and glycerophospholipid breakdown (via phospholipase A₂), whereas chronic DMD showed sustained glycine/serine engagement and inferred, unresolved phospholipid perturbation without protein-level compensation, which may result from chronic oxidative stress. Overall, our integrative analysis revealed time-specific, multi-layer molecular perturbations distinguishing acute toxin injury from chronic muscle degeneration. Key metabolic control points (ceramide accumulation, arginine flux diversion, autophagy-lipid cross-talk, NAD⁺ salvage timing) were identified, highlighting potential targets for stage-specific therapeutic or nutritional interventions.

Animals↗

PubMed2026

A chromosome-level genome assembly and developmental transcriptome profiling reveal stage-specific remodeling of the molecular chaperone system in Helicoverpa armigera.

Helicoverpa armigera is one of the most destructive lepidopteran pests worldwide owing to its remarkable polyphagy, long-distance migration, and rapid adaptation to insecticides. Here, we present a chromosome-level genome assembly of H. armigera generated from a field-collected individual in southwestern China, providing a valuable resource for future population genomic and pangenome studies. Developmental transcriptome analyses of first-instar larvae, fifth-instar larvae, and adults identified 6817, 3519, and 5518 differentially expressed genes, respectively, including 797 shared among all developmental transitions. Functional enrichment and co-expression network analyses revealed extensive transcriptional reprogramming, characterized by coordinated regulation of glycolysis, the tricarboxylic acid (TCA) cycle, and fatty acid β-oxidation, indicating dynamic metabolic remodeling during development. Genome-wide analysis identified 77 heat shock protein (HSP) genes belonging to six subfamilies. These genes were unevenly distributed across chromosomes, with HSP20 members exhibiting extensive tandem duplication. Expression profiling revealed pronounced stage specificity, suggesting progressive remodeling of molecular chaperone networks during development. Early larvae primarily relied on HSP40/HSP60/HSP70 and HSP10/HSP60 chaperone systems; fifth-instar larvae exhibited HSP20-centered proteostasis; and adults predominantly expressed HSP40 together with multiple HSP70 members, accompanied by enrichment of stress response and metamorphosis-related functions. This study provides new insights into developmental transcriptional regulation, metabolic remodeling, and stage-specific specialization of molecular chaperone networks in H. armigera, establishing a foundation for future studies of stress adaptation, population genomic variation, and developmental mechanisms.

Cotton bollworm↗

PubMed2025

Single-cell RNA-seq of small-intestinal neuroendocrine tumors reveals the cell of origin and gene expression of early tumor development.

Patients with a hereditary form of small-intestinal neuroendocrine tumors (SI-NETs) present with multiple synchronous tumors and precursors at various stages. Using this germline trait, single-cell RNA sequencing is performed to define the cell-of-origin and gene-expression trajectory in early tumor development. A subset of CES1(+), LCN15(-) enterochromaffin (EC) cells, residing at +4 position and below in the crypts, distinct from EC cells migrating up the villi, emerges as the putative SI-NET origin. PRODH2 is identified as a key biomarker for precursor cells, revealing stage-specific gene expression linked to early tumor development. From precursor to fully developed tumors, notable changes include the up-regulation of UCHL1 and MBD3L2, as well as the significant down-regulation of cell-cycle inhibitory genes, CDKN1A, CDKN1C, and CDKN2B, which play roles in cell survival and tumorigenesis. The current study provides insight into SI-NET initiation and progression, offering potential advancements in diagnosis, prevention, and treatment.

Neuroendocrine Tumors↗

PubMed2026

Incidence of Cirrhosis in Fibrotic Metabolic Dysfunction-Associated Steatohepatitis: A Meta-Analysis of Placebo Arms from Randomized Clinical Trials.

BACKGROUNDS AND AIMS: Metabolic dysfunction-associated steatohepatitis (MASH) with stage F2-F3 fibrosis represents the main target population for emerging pharmacotherapies. However, data on short-term progression to cirrhosis (F4) in this group remain limited. We aimed to evaluate the incidence of cirrhosis in placebo-treated patients with fibrotic MASH in randomized controlled trials (RCTs). METHODS: In this single-arm meta-analysis, we systematically searched PubMed and Cochrane Library from inception to December 13, 2024, for pharmacological Phase ≥ 2 RCTs reporting cirrhosis events (detected in liver biopsy or clinical signs) among patients with fibrotic MASH receiving placebo. Incidence rates were pooled using generalized linear mixed models with Clopper-Pearson confidence intervals (CIs). RESULTS: We identified a total of 11 RCTs, including 586 patients with fibrotic MASH. Total follow-up was 657.23 person-years (PYs), with 83 cirrhosis events reported. The pooled incidence rate was 13.09 per 100 PYs (95% CI 7.81 to 21.12, I2 = 75.6%, τ2 = 0.682). In subgroup analysis, the incidence of cirrhosis was 3.40 per 100 PYs in MASH F2 (95% CI 1.10 to 10.02, I2 = 0%, τ2 = 0) and 17.90 per 100 PYs (95% CI 10.63 to 28.55, I2 = 70.2%, τ2 = 0.561) in MASH F3, with significant differences between stages (p = 0.006). Sensitivity analyses showed consistent estimates. Most RCTs were judged to have a low risk of bias. CONCLUSIONS: This study provides stage-specific data on cirrhosis incidence in fibrotic MASH, highlighting the high short-term risk associated with MASH F3 in trial settings. These data may inform benchmarks to guide event expectations, enrichment strategies, sample size assumptions, and the interpretation of future MASH clinical trials.

Humans↗

PubMed2026

Integrative dual-track transcriptomics reveals stage-specific coordination, regulatory divergence, and HSP90AA1-associated remodeling in human folliculogenesis.

Human folliculogenesis depends on coordinated yet non-identical developmental remodeling in the oocyte and its surrounding granulosa cells. When these two compartments remain synchronized and when they diverge into lineage-specific regulatory states, however, remains incompletely resolved. Here we performed an integrative dual-track re-analysis of the human RNA-seq dataset GSE107746, modeling oocytes and granulosa cells as distinct but developmentally linked compartments across follicular progression. Analysis of 148 sequencing libraries showed that compartment identity was the dominant source of transcriptomic variation, supporting compartment-aware downstream interpretation. Within this framework, oocytes followed a relatively continuous developmental trajectory, with substantial transcriptional remodeling already evident across adjacent stages, whereas granulosa cells showed weaker early-stage contrasts but markedly stronger late-stage reorganization, particularly around the antral and preovulatory transitions. Functional enrichment indicated that oocyte maturation was associated with RNA-processing and broader genome-regulatory remodeling, whereas granulosa maturation was dominated by progressive mitochondrial and bioenergetic activation. Co-expression analysis showed that both compartments contained strong late-stage programmes together with inverse early-state modules, indicating a shared systems-level architecture of maturation, although the hub-gene composition and biological content of these programmes were largely compartment-specific. Machine-learning validation reinforced this asymmetry: oocyte stage classification was best recovered from a compact eigengene-based representation, whereas granulosa stage discrimination was better resolved by a broader differential-expression-derived feature set. At the gene level, HSP90AA1 emerged as a stage-associated marker with compartment-specific behavior, showing progressive attenuation across oocyte development, assignment to the selected oocyte blue module, and sharper transitional dynamics in granulosa cells. Together, these findings support a model in which human folliculogenesis proceeds through coordinated but non-equivalent transcriptomic remodeling, with shared developmental logic at the systems level but distinct molecular execution in germline and somatic compartments.

Co-expression networks↗

PubMed2026

Stage-specific ROMO1 in rheumatoid arthritis: predictive immune insights into the MIF pathway and HLA-DR/IL2RA axis via integrated GWAS, transcriptomic, single-cell, and spatial profiling.

Emerging evidence links reactive oxygen species modulator 1 (ROMO1), a key mitochondrial ROS regulator, to rheumatoid arthritis (RA) pathogenesis. However, its exact mechanism remains elusive given the conflicting evidence about its specific function. We used a four-level integrative framework combining multi-omics data and literature‑supported mechanistic inference. At the genetic level, Mendelian randomization (MR) was performed to explore potential causal relationships between ROMO1, IL2RA, HLA-DR, MIF, and RA risk, followed by differential expression analysis and machine learning-based feature selection to identify key mROS genes. The temporal expression dynamics of ROMO1 were assessed in RA progression. At the cellular and tissue levels, we integrated single-cell RNA sequencing and spatial transcriptomics to map cell-type-specific expression and synovial localization of ROMO1-related immune cells and pathways. Finally, our multi-omics findings were contextualized with literature-supported mechanistic inference. (1) MR results were consistent with a potential protective effect of ROMO1 on RA (OR = 0.52) and its potential regulation of risk factors IL2RA (OR = 0.46) and HLA-DR (OR = 0.40). Conversely, IL2RA (OR = 1.42), HLA-DR (OR = 1.88), and MIF (OR = 1.17) were positively associated with RA risk. Additionally, ROMO1 was identified as a top candidate diagnostic predictor with stage-specific dynamics: downregulated in the early but upregulated in the late/remission stages. (2) Single-cell RNA sequencing showed ROMO1's cell-specific expression in CD14+ HLA-DR+ CD74+ monocytes and CD4+ IL2RA+ T cells. Cell communication analysis further suggested that these cells may participate in MIF pathway regulation. Spatial transcriptomics subsequently identified that ROMO1-related cells localized to synovial pathological regions, with MIF pathway changes correlated with RA progression. (3) Finally, literature-supported mechanistic inference suggests that ROMO1 may modulate mROS levels to promote anti-inflammatory M2 macrophage polarization, which could theoretically contribute to reduced systemic inflammation and the alleviation of multi-organ decline in RA. This integrated multi-omics investigation, supported by literature-based mechanistic inference, suggests ROMO1 as a stage-dependent biomarker candidate and potential immune regulator in RA.

Humans↗

PubMed2026

Matrix Mechanics Governs Mechano-Metabolic Adaptation across Cancer Grades in Bladder Spheroids.

Extracellular matrix (ECM) mechanics is pivotal regulators of tumor progression, yet how viscoelasticity and matrix architecture converge to shape metabolic and invasive adaptation remains insufficiently defined. We postulate that mechanical stimuli from the ECM induce coordinated changes in adhesive and metabolic pathways, and that the nature of this independent mechano-metabolic pathway is conserved across benign, low-invasive, and high-invasive bladder cancer phenotypes. Therefore, we engineered collagen-hyaluronan hydrogels with tunable stiffness to recapitulate soft and rigid tumor microenvironments and profiled bladder cancer spheroids representing benign, low-invasive, and highly invasive states. Integrating hydraulic force spectroscopy, rheology, and molecular phenotyping, we show that matrix stiffening differentially reprograms spheroid architecture, motility, and adhesion- and metabolism-related gene expression. Spheroid behavior emerged from the interplay between intrinsic mechanical properties, matrix rheology, and molecular adaptation. HCV29 spheroids formed rigid, compact structures, relying on cell-matrix adhesion rather than metabolic or proteolytic remodeling. HT1376 spheroids activated glycolysis (HK2) and MMP-2-dependent ECM remodeling in soft matrices, but remained largely nonmigratory, indicating decoupling of invasive priming from motility. T24 spheroids were soft, deformable, and highly migratory in compliant matrices, integrating metabolic reprogramming, adhesion remodeling (E-/N-cadherin, SDC4), and radial collagen fiber alignment to drive invasion. Notably, canonical FAK/AKT/mTOR signaling was absent across all spheroids, while pS6 ribosomal protein and ILK indicated noncanonical, SDC4/integrin-ILK-dependent mechanotransduction supporting cytoskeletal dynamics, metabolism, and ECM remodeling. Collagen organization further differed across spheroid types, with dense, radially aligned fibers in HT1376, intermediate architecture in HCV29, and loose, disorganized networks in T24, closely matching their distinct migratory behaviors and cell-ECM interactions. These findings reveal stage-specific mechanometabolic strategies in bladder cancer, demonstrating how ECM mechanics and architecture jointly guide invasion, metabolic adaptation, and local immune modulation, including the regulation of immune cell infiltration and tumor immune evasion.

Humans↗