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PubMed2025

Genome-wide DNA methylation regulation analysis provides novel insights on post-radiation breast cancer.

Breast cancer (BC) is the most common malignancy with a poor prognosis. Radiotherapy is one of the leading traditional treatments for BC. However, radiotherapy-associated secondary diseases are severe issues for the treatment of BC. The present study integrated multi-omics data to investigate the molecular and epigenetic mechanisms involved in post-radiation BC. The differences in the expression of radiation-associated genes between post-radiation and pre-radiation BC samples were determined. Enrichment analysis revealed that these radiation-associated genes involved diverse biological functions and pathways in BC. Combining epigenetic data, we identified radiation-associated genes whose transcriptional changes might be associated with aberrant methylation. Then, we identified potential therapeutic targets and chemical drugs for post-radiation BC patient treatment by constructing a drug-target association network. Specifically, four radiation-associated genes (CD248, CCDC80, GADD45B, and MMP2) whose increased expression might be regulated by hypomethylation of the corresponding enhancer region were found to have excellent diagnostic effects and clinical prognostic value. Finally, we further used independent samples to verify CD248 expression and established a simple epigenetic regulatory model. In summary, this study provides novel insights for understanding the regulation of target genes mediated by DNA methylation and developing potential biomarkers for radiation-associated secondary diseases in BC.

Humans↗

PubMed2026

GFPT1 as a cross-ancestry validated target for degenerative spinal disease: genetic association in a Chinese cohort and functional characterization in zebrafish.

Degenerative spinal disease (DSD), including spinal stenosis and spondylosis, lacks effective pharmacological treatment. To identify druggable targets and assess cross-ancestry applicability, we integrate multi-omics analyses using Summary-data-based Mendelian Randomization (SMR), colocalization, and two-sample Mendelian randomization with European whole-blood, peripheral-blood, and CSF eQTL/pQTL datasets, followed by whole-genome sequencing (WGS) validation in a Chinese cohort. We identify 7 genes/proteins associated with spinal stenosis and 5 with spondylosis, with GFPT1, GPX1, and SERPINA1 shared by both. Two-sample MR further supports the causal associations of these targets with DSD. Phenome-wide MR prioritization selects GFPT1 and GPX1 as favorable candidates with no predicted adverse effects and potential beneficial effects on hypertension. In the Chinese cohort (67 lumbar spinal stenosis patients and 100 controls), WGS identifies 4 GFPT1 cis-eQTL loci (rs13016371, rs35392088, rs12997521, and rs13019789) associated with lumbar spinal stenosis risk; all risk alleles are linked to increased GFPT1 expression, and all 24 variant carriers show L4/L5 stenosis on imaging. Druggability analysis identifies IOX1 as the sole preclinical-stage compound targeting GFPT1, and molecular docking supports robust binding to GFPT1 (- 6.39 kcal/mol). Functional assays show that IOX1 directly inhibits GFPT1 enzymatic activity and induces fructose-6-phosphate accumulation. In zebrafish, IOX1 significantly rescues GFPT1-induced degenerative phenotypes. These findings establish GFPT1 as a cross-ancestry validated therapeutic target for DSD and nominate IOX1 as a promising disease-modifying candidate.

Animals↗

PubMed2026

Selection favors cost-ordered adaptive mutational paths in a stress-magnitude-dependent manner.

Chronic exposure to stress requires adaptive strategies beyond canonical regulatory mechanisms. Stress varies, both qualitatively and quantitatively, across physiological niches and exerts distinct selection pressures on colonizing bacteria. Bacteria employ diverse defense strategies to withstand various stressful conditions, yet how they tailor their responses to different magnitudes of the same stressor remains poorly understood. We used multiple adaptive laboratory evolution experiments of Escherichia coli across varying paraquat concentrations and genetic backgrounds to dissect adaptive strategies at different levels of stress. Integrating multi-omic analyses with a tailored genome-scale metabolic model-based parametrized cost calculations, we identify two fundamentally distinct tolerance mechanisms. Under low-paraquat stress, blocking the polyamine transporter that is reported to be hijacked for paraquat influx suffices to maintain optimal growth. In contrast, higher stress levels activate an energetically demanding program involving enhanced detoxification and efflux. The transport flux regulation establishes a primary defense layer, upon which metabolic repair systems provide additional fitness advantages. The stress magnitude-dependent differential engagement of previously reported paraquat tolerance approaches offers insights into the principles governing dynamic bacterial adaptation.

Journal Article↗

PubMed2025

De novo pyrimidine synthesis is a collateral metabolic vulnerability in NF2-deficient mesothelioma.

Pleural mesothelioma (PM) is one of the deadliest cancers, with limited therapeutic options due to its therapeutically intractable genome, which is characterized by the functional inactivation of tumor suppressor genes (TSGs) and high tumor heterogeneity, including diverse metabolic adaptations. However, the molecular mechanisms underlying these metabolic alterations remain poorly understood, particularly how TSG inactivation rewires tumor metabolism to drive tumorigenesis and create metabolic dependencies. Through integrated multi-omics analysis, we identify for the first time that NF2 loss of function defines a distinct PM subtype characterized by enhanced de novo pyrimidine synthesis, which NF2-deficient PM cells are critically dependent on for sustained proliferation in vitro and in vivo. Mechanistically, NF2 loss activates YAP, a downstream proto-oncogenic transcriptional coactivator in the Hippo signalling pathway, which in turn upregulates CAD and DHODH, key enzymes in the de novo pyrimidine biosynthesis pathway. Our findings provide novel insights into metabolic reprogramming in PM, revealing de novo pyrimidine synthesis as a synthetic lethal vulnerability in NF2-deficient tumors. This work highlights a potential therapeutic strategy for targeting NF2-deficient mesothelioma through metabolic intervention.

Pyrimidines↗

PubMed2026

Clinical proteomics in inborn errors of metabolism: from biomarker discovery to implementation.

INTRODUCTION: Inborn errors of metabolism (IEMs) are rare, heterogeneous disorders traditionally diagnosed through genetic testing, enzyme assays, and metabolite measurements. However, these tools often do not fully explain phenotypic variability, organ involvement, disease progression, or treatment response. Clinical proteomics provides a complementary functional layer by capturing changes in protein abundance, proteoforms, post-translational modifications (PTM), and biological pathways, offering insights beyond genotype- and metabolite-based approaches. AREAS COVERED: This review examines the role of high-resolution mass spectrometry and computational proteomics in biomarker discovery and clinical decision-making for IEMs. It focuses on their contribution to diagnosis, variant interpretation, patient stratification, and treatment monitoring. Disease-specific applications are discussed, with the strongest evidence in lysosomal storage disorders, mitochondrial diseases, congenital disorders of glycosylation, and selected neurodegenerative or renal metabolic conditions. The literature search was performed in PubMed, Scopus, Web of Science, and Google Scholar, covering peer-reviewed articles available up to 2026, with emphasis on methodological advances and translational applications in clinical proteomics for IEMs. EXPERT OPINION: Proteomics will not replace established diagnostic tools, but it can help address clinically actionable questions in selected contexts. Translation into clinical practice will require standardized workflows, multicenter validation, clinically anchored endpoints, and integration with other omics approaches.

Humans↗

PubMed2026

scSNViz: visualization and analysis of cell-specific expressed SNVs.

MOTIVATION: Accurately characterizing expressed genetic variation at the single-cell level is essential for understanding transcriptional heterogeneity, allelic regulation, and mutational dynamics within complex tissues. However, few tools enable comprehensive visualization and quantitative analysis of expressed variants across individual cells. RESULTS: scSNViz is an R package for the exploration, quantification, and visualization of expressed single-nucleotide variants (SNVs) from cell-barcoded single-cell RNA sequencing (scRNA-seq) data. The software supports estimation of variant allele fractions, clustering of SNV expression profiles, and 2D and 3D visualization of individual SNVs or user-defined SNV groups. Beyond visualization, scSNViz facilitates investigation of cell-, cluster-, or lineage-specific variant expression patterns, as well as allelic dynamics including imprinting, random allele inactivation, and transcriptional bursting. It interoperates seamlessly with established single-cell frameworks-Seurat for clustering, Slingshot for trajectory inference, scType for cell-type annotation, and CopyKat for copy-number profiling-enabling integrative multi-omic analyses of expressed variation. AVAILABILITY AND IMPLEMENTATION: scSNViz is implemented in R and freely available at https://github.com/HorvathLab/scSNViz (DOI: 10.5281/zenodo.17307516). The package includes comprehensive documentation and example workflows designed for users with limited bioinformatics experience.

Software↗

PubMed2004

Metabolic profiles to define the genome: can we hear the phenotypes?

There is an increased reliance on genetically modified organisms as a functional genomic tool to elucidate the role of genes and their protein products. Despite this, many models do not express the expected phenotype thought to be associated with the gene or protein. There is thus an increased need to further define the phenotype resultant from a genetic modification to understand how the transcriptional or proteomic network may conspire to alter the expected phenotype. This is best typified by the description of the silent phenotype in genetic manipulations of yeast. High-resolution proton nuclear magnetic resonance ((1)H NMR) spectroscopy provides an ideal mechanism for the profiling of metabolites within biofluids, tissue extracts or, with recent advances, intact tissues. These metabolic datasets can be readily mined using a range of pattern recognition techniques, including hierarchical cluster analysis, principal components analysis, partial least squares and neural networks, with the combined approach being termed metabolomics. This review describes the application of NMR-based metabolomics or metabonomics to genetic and chemical interventions in a number of different species, demonstrating the versatility of such an approach, as well as suggesting how it may be integrated with other "omic" technologies.

Animals↗

PubMed2025

Integrative genomics elucidates the evolutionary, temporal, and developmental origins of a hydrocephalus risk gene.

INTRODUCTION: A prior integrative, multi-omics human genetics and functional genomics study identified maelstrom (MAEL), a gene involved in regulation of DNA transposon activity and genome structure, as a transcriptome-wide predictor of hydrocephalus (HC) in the brain cortex. Here we expand on this discovery and further characterize the evolutionary origin and expression of MAEL across developmental timescales and cell-lineages in the neonatal human brain towards a mechanistic understanding how variation in MAEL expression may cause HC. OBJECTIVE: To characterize the evolutionary, temporal, developmental, and lineages of MAEL expression in HC and the developing human brain. METHODS: Ensembl was used to delineate the evolution and taxonomy of MAEL across species. Analysis of single-cell RNA sequencing (scRNA-seq) of 49 brain regions across pre- and post-natal timescales from the Developing Human Brain Atlas (Allen Institute) identified temporal and spatial MAEL expression patterns. We quantified MAEL expression in primary cortical brain tissue obtained during the surgical treatment of HC. RESULTS: We performed taxonomic gene-mapping to define the evolutionary origin of MAEL to assess suitability for mechanistic characterization in vitro and in vivo across species. We find that MAEL is among the top 0.01% human-specific genes and < 50% sequence homology among commonly used model organisms with highly divergent functions, necessitating mechanistic validation in human tissue. scRNA-seq of the non-disease prenatal human brain identified MAEL expression enriched in cortical excitatory neurons, which was recapitulated in primary HC brain tissue obtained during surgery. Finally, using scRNA-seq of primary HC brain tissue, we functionally validated reduced MAEL expression, consistent with a prior human TWAS analysis. CONCLUSIONS: We identify the evolutionary, temporal, and developmental expression pattern of MAEL in the neonatal human brain. We also provide direct evidence for reduced MAEL expression in human HC brain tissue. These data, at least in part, implicate reduced MAEL expression underlying human HC across etiologies.

Journal Article↗

PubMed2025

Integrative metabolomic and proteomic analysis of diabetic kidney disease progression with younger-onset type 2 diabetes.

AIM: Younger-onset type 2 diabetes (YT2D) confers a disproportionately high risk of diabetic kidney disease (DKD), yet early biomarkers and underlying mechanisms remain poorly defined. We aimed to identify metabolites associated with DKD progression and integrate metabolomic and proteomic data to elucidate pathways involved in a multi-ethnic Asian cohort. MATERIALS AND METHODS: In this prospective study, 787 YT2D patients (diagnosed at ≤ age 40) were followed for a median of 5.7 years. DKD progression was defined as an annual decline in estimated glomerular filtration rate (eGFR) of ≥3 mL/min/1.73 m2 or ≥ 40% reduction in eGFR from baseline. Plasma metabolites were measured by nuclear magnetic resonance spectroscopy. Multivariable regression analysis was performed in a discovery (N = 550) and internal validation cohort (N = 237). Integrative metabolomic-proteomic analysis (N = 428) was performed using sparse partial least squares discriminant analysis (sPLS-DA). RESULTS: Ninety-eight metabolites were differentially expressed between DKD progressors and non-progressors, of which total branched-chain amino acids (BCAAs) (OR = 0.60, 95% CI 0.46-0.79), valine (OR = 0.62, 95% CI 0.48-0.81), and leucine (OR = 0.56, 95% CI 0.43-0.74) associated with DKD progression, independent of metabolic risk factors. Integrative analysis identified three components comprising 23 proteins and 30 metabolites, involved in the citrate cycle and apoptosis, which improved prediction of DKD progression beyond clinical risk factors (AUC 0.69-0.83). CONCLUSION: Lower plasma BCAA levels are independently associated with DKD progression in YT2D. Integrative multi-omics analysis highlights disruptions in metabolic and apoptotic pathways, providing insights into DKD pathophysiology and potential biomarkers for early risk stratification.

Humans↗

PubMed2026

Rhizosphere Dialogue: Microorganisms Mediated by Root Exudates Alleviate Drought Stress in Grasses.

Drought stress threatens the ecological functions and economic value of grasses, posing a major challenge to their sustainable production. Plants co-evolve with rhizosphere microbial communities, sometimes described as the plant's second genome, that can contribute to drought adaptation. Drought alters root architecture, hormonal and redox regulation and belowground carbon allocation, thereby modifying the quantity and composition of root exudation and reshaping the rhizosphere environment. This review uses the rhizosphere dialogue as an integrative framework to link these plant responses with microbial recruitment and subsequent feedback to the host. We summarise three linked stages of this dialogue: drought-induced changes in root exudation; microbial recruitment and colonisation through chemotaxis, attachment, biofilm formation, and root colonisation; and microbiome-mediated feedback that improves plant water relations, hormonal and redox homoeostasis, nutrient acquisition, and root function. We highlight microbial extracellular polymeric substances, 1-aminocyclopropane-1-carboxylate deaminase, and microbial volatile organic compounds as key mediators of drought alleviation. We then discuss how this framework may inform rational synthetic microbial community (SynCom) design, microbiome-informed breeding, artificial intelligence and machine-learning assisted strain prioritisation, rhizosphere legacy effects, and real-time monitoring. Future work should distinguish active exudate-mediated recruitment from drought-driven environmental filtering and integrate multi-omics, plant genetics, functional validation, and multi-location field trials to determine whether rhizosphere dialogue can become a predictive framework for climate-resilient grass production.

drought stress↗

PubMed2026

Cis-regulatory evolution of CsANS1 drives cultivar variation in anthocyanin accumulation in tea plants.

Anthocyanins, a ubiquitous class of water-soluble phytochemicals renowned for their chromatic diversity and potent bioactivity, are integral to the phenotypic and metabolic plasticity of higher plants. Using an integrative multi-omics approach that combines transcriptomic and metabolomic profiling, we identified anthocyanin synthase (CsANS1) as the key genetic determinant responsible for interspecific variation in anthocyanin accumulation among tea plants. Architectural comparison of promoter regions revealed a 192-bp variation insertion in the CsANS1 cis-regulatory region with potential functional significance. This insertion was strictly conserved in anthocyanin-rich (purple-leaf) cultivars, including both natural and hybrid genotypes, but entirely missing in anthocyanin-deficient (green-leaf) cultivars. Dual-luciferase assays confirmed that this insertion enhances promoter activity. Additionally, we delineated a tripartite regulatory axis comprising CsmiR156b, CsSPL9, and CsMYB75 which orchestrates the spatiotemporal modulation of CsANS1 expression and, consequently, anthocyanin biosynthesis. Collectively, these findings provide a mechanistic paradigm for anthocyanin polymorphism in tea plants, implicating both cis-regulatory evolution and transcriptional network synergy as pivotal drivers of phytochemical diversification.

Anthocyanins↗

PubMed2026

SpxA1 and SpxA2 function as a stoichiometry-dependent regulatory rheostat governing virulence gene expression in group A Streptococcus.

UNLABELLED: Group A Streptococcus (GAS) is a human-restricted pathogen whose global incidence has surged in the post-COVID era. The ability of GAS to shift from a colonizing to invasive phenotype depends on coordinated virulence gene regulation in response to host-derived signals. However, the mechanisms by which individual stress-sensing systems interact to reshape the virulence gene regulatory landscape remain incompletely understood. Here, we define the regulatory programs of two conserved transcriptional regulator paralogs, SpxA1 and SpxA2, using an integrated multi-omic approach combining RNA-seq, data-independent acquisition proteomics, NanoString-based transcriptional profiling across multiple host-relevant stress conditions, and chromatin immunoprecipitation with exonuclease treatment (ChIP-exo). RNA-seq revealed functionally distinct regulons with SpxA1 governing oxidative stress defense and SpxA2 coordinating virulence-associated gene expression linked to the CovRS two-component regulatory system. Proteomic analysis established SpxA2 as a ClpXP protease substrate in GAS and identified reciprocal paralog accumulation upon loss of either SpxA1 or SpxA2, consistent with compensatory transcriptional upregulation. NanoString profiling under bacitracin and human neutrophil peptide-1 challenge identified four gene modules with distinct stoichiometry-dependent and condition-dependent regulatory logic, revealing that the SpxA1/SpxA2 ratio rather than the activity of either paralog alone determines which transcriptional programs are engaged. ChIP-exo demonstrated that SpxA2 directly modulates CovR-DNA binding occupancy in a CovR-binding motif-dependent manner, simultaneously antagonizing CovR dimer binding at an extended (25 bp) CovR motif and facilitating CovR monomer binding at the canonical ATTARA motif. These findings establish the LiaFSR-SpxA2-CovRS axis as a cross-regulatory circuit through which GAS cell envelope stress sensing is directly transduced into coordinated virulence gene regulatory changes. IMPORTANCE: Group A Streptococcus (GAS) causes millions of infections annually, including a recent global surge in invasive disease. To survive in the human host, GAS must rapidly reprogram virulence gene expression in response to host-derived stresses. This study characterizes two conserved transcriptional regulators, SpxA1 and SpxA2, that govern this response through interaction with RNA polymerase to indirectly influence the DNA-binding activity of downstream transcription factors. We show that SpxA2, activated by a cell envelope stress-sensing system responding to human antimicrobial peptides, reshapes the binding of the master virulence regulator CovR in a promoter-specific manner, coupling cell envelope stress sensing to virulence gene regulation. The stoichiometric balance between SpxA1 and SpxA2 functions as a regulatory rheostat calibrating overall virulence gene regulatory tone, providing a framework for understanding how RNA polymerase-interacting regulators coordinate stress responses and virulence gene control across Gram-positive bacterial pathogens.

Streptococcus pyogenes↗

PubMed2026

Spatial habitat radiomics predicts tertiary lymphoid structure status and identifies an IDO1+ migratory dendritic cell axis in breast cancer.

BACKGROUND: Tertiary lymphoid structures (TLS) are spatially organized immune niches associated with therapeutic response and favorable outcomes in breast cancer (BC). However, TLS assessment currently relies on invasive tissue-based analyses, and the biological mechanisms underlying imaging-based TLS prediction remain poorly understood. METHODS: We developed and validated a spatial heterogeneity-based radiomic TLS signature (shTLS) using dynamic contrast-enhanced MRI to non-invasively predict TLS status across multicenter BC cohorts. Spatial habitat radiomics were used to capture intratumoral and peritumoral immune-related heterogeneity. Integrated multi-omics analyses, including transcriptomics, pathomics, genomics, single-cell RNA sequencing, immunohistochemistry, and multiplex immunofluorescence, were performed to biologically interpret shTLS-defined subgroups. Functional drug-sensitivity assays were conducted to assess therapeutic implications. RESULTS: The shTLS model achieved robust predictive performance across independent cohorts and molecular subtypes. High shTLS scores were associated with immune-inflamed tumors characterized by spatially clustered activated T cells and dendritic cells (DCs). In contrast, shTLS-low tumors exhibited an immunosuppressive spatial niche with peripheral accumulation of CD4+ PD-1+ T cells and plasma cells, increased immune-tumor separation, and enhanced inflammatory and immunoregulatory signaling. An indoleamine 2,3-dioxygenase 1 (IDO1)-associated immunoregulatory program was observed in the shTLS-low tumors, which appeared to be preferentially expressed by LAMP3+CCR7+ migratory DCs. Pharmacologic inhibition of IDO1 enhanced chemotherapy and CDK4/6 inhibitor sensitivity in vitro. CONCLUSION: This study establishes spatial radiomics as a non-invasive approach to decode TLS-associated immune ecosystems and supports the presence of an IDO1-associated immunosuppressive phenotype, providing biological insight and translational rationale for patient stratification and future combination strategies.

Humans↗

PubMed2026

Markers of microvascular instability predict severity and survival in idiopathic pulmonary fibrosis.

INTRODUCTION: Most research on idiopathic pulmonary fibrosis (IPF) has focused on the interplay among fibroblasts, the immune system and epithelial cells. There is growing evidence that microvascular dysfunction also plays a role in disease progression, but large human translational studies are lacking. In this research, we aim to identify a proteomic signature of microvascular instability and assess the impact of current therapeutics on the microvasculature. METHODS: Olink proteomic data from patients with IPF were obtained from the Pulmonary Fibrosis Foundation Patient Registry (PFF-PR) (n=914) and an independent validation cohort (n=366). Among the PFF-PR, 640 patients also have whole-blood RNA sequencing data available. A subset of 79 microvascular-associated proteins was curated, and their associations with disease severity and transplant-free survival were examined. An adaptive least absolute shrinkage and selection operator was used to generate a novel microvascular risk score. RESULTS: Higher plasma levels of five microvascular-associated proteins (SDC1, MMP10, THBS2, HGF and SERPINA5) were associated with lung function and survival in both cohorts. Whole-blood RNA sequencing of patients with microvascular risk revealed enrichment of immune-mediated processes. Patients with higher microvascular risk who were subsequently put on nintedanib in the following year had significantly better 3-year transplant-free survival compared with patients who did not receive antifibrotic intervention (HR 0.56, 95% CI 0.35 to 0.89, p=0.0142). DISCUSSION: Integrative multi-omics analyses suggest that perturbations to microvascular remodelling contribute to disease severity and progression in IPF. This analysis offers a framework for a precision medicine approach for IPF.

Idiopathic pulmonary fibrosis↗

PubMed2025

Consumption of traditional Sardinian fermented milk promotes changes in the rat gut microbiota composition and functions.

BACKGROUND: Fermented milk products are part of the staple diet for many Mediterranean populations. Most of these traditional foods are enriched with lactobacilli and other lactic acid bacteria, as well as with metabolites resulting from lactose fermentation. Currently, there is very little scientific knowledge on how dietary supplementation with fermented milk affects the composition of the gut microbiota and its metabolic activities. RESULTS: We integrated 16 S rRNA gene-based taxonomic profiling with metaproteomics-based functional analysis to investigate gut microbiota changes in rats exposed to an 8-week dietary supplementation with casu axedu, a traditional fermented milk produced within rural communities in Sardinia (Italy). Several microbial taxa showed a significantly increased abundance at the end of the dietary treatment, including Phascolarctobacterium, Prevotella, Blautia glucerasea, and Lactococcus lactis, while Bacteroides dorei and Helicobacter rodentium were decreased compared to the control rats. Metaproteomic analysis highlighted a striking reshaping of the Prevotella proteome in agreement with its blooming in casu axedu-fed animals, suggesting an increase of the glycolytic activity through the Embden-Meyerhof-Parnas pathway over the Entner-Doudoroff pathway. Moreover, an increased production of enzymes involved in succinate biosynthesis was observed, which in turn significantly boosted the abundance of Phascolarctobacterium and its production of propionate. Fermented milk consumption also promoted microbial synthesis of branched chain essential amino acids L-valine and L-leucine. Finally, metaproteomic data indicated a reduction of bacterial virulence factors and host inflammatory markers, suggesting that the consumption of casu axedu can have beneficial effects on the gut mucosa health. CONCLUSIONS: Our integrated multi-omics approach reveals that dietary supplementation with the traditional Sardinian fermented milk, casu axedu, induces significant shifts in the rat gut microbiota composition and function, characterized by the enrichment of beneficial taxa and metabolic pathways associated with improved gut health and reduced inflammation.

Animals↗

PubMed2026

Genome-wide identification and functional analysis of the BES1-like (VfBES1) gene family in Vernicia fordii reveals its role in floral development.

BACKGROUND: Vernicia fordii Hemsl (also known as Tung tree), an significant commercial oil-producing tree species, is a monoecious and diclinous species with male and female flowers on the same inflorescence; however, the molecular mechanisms governing its floral sex determination remain elusive, particularly the genetic basis underlying the skewed female-to-male flower ratio and the evolutionary dynamics of sex-related gene families, which severely restrict targeted breeding for yield enhancement. In the model plant Arabidopsis, the BRI1 EMS SUPPRESSOR 1 (BES1) transcription factor family plays a crucial role in Brassinosteroid (BR) signaling and reproductive development. However, its function remains largely unexplored in woody perennials. RESULTS: In this study, we introduce the genome-wide identification and functional characterization of the BES1-like (VfBES1) gene family in the Tung tree for the first time. Integrative multi-omics approaches reveal seven VfBES1 genes that are clustered into three phylogenetically distinct clades, each characterized by clade-specific motifs and structural simplicity. Segmental duplication events (VfBES1-1/VfBES1-5 and VfBES1-4/VfBES1-7) and promoter cis-element enrichment (hormone-responsive and abiotic stress-related motifs) highlight evolutionary innovation and functional diversification. Spatiotemporal expression profiling reveals VfBES1 genes' tissue- and stage-specific roles. VfBES1-1 predominantly expresses in female flowers and fruits, suggesting its possible roles in late-stage sex maintenance or ovule and fruit development. VfBES1-2 and VfBES1-6 exhibit male flower-specific and early floral developmental activation, respectively. Nuclear-localized VfBES1-6 displays co-expression with VfMYB35-1 gene, which is a regulator of male structure degeneration. CONCLUSIONS: Findings in this study shed light on the regulatory roles of VfBES1 genes in the floral development of the Tung tree, providing a reference for its precision breeding to enhance flowering synchrony and seed productivity. This study also provides a comparative framework for understanding the functional diversity of BES1-like genes in non-model woody plants.

Flowers↗

PubMed2026

Radiogenomics predicts immune microenvironment heterogeneity and response to combination immunotherapy in hepatocellular carcinoma.

BACKGROUND: The combination of immune checkpoint inhibitors (ICIs) with anti-angiogenic agents is the preferred first-line therapy option for patients with advanced hepatocellular carcinoma (HCC), yet only a subset of patients responds, urging the quest for prediction biomarkers. We aimed to integrate genomics with radiology to propose an immune-derived radiogenomics biomarker of response to such combination immunotherapy and evaluate its added value in clinical context. METHODS: We integrated bulk RNA sequencing (RNA-seq) and proteomics data of 994 HCC patients with single-cell RNA-seq data of 11 samples across multiple datasets to identify an immune-related signature (IRS) that may influence sensitivity or resistance to such combined immunotherapy strategy, followed by verification of selected marker genes using immunohistochemistry and cytological experiments. We then trained/validated a cross-modality radiogenomics biomarker using machine learning based on TCIA database that was further tested in multi-scale independent cohorts covering 754 HCC patients. RESULTS: Integrative multi-omics analysis identifed a parsimonious 2-gene prognostic signature including KPNA2 and SMG5 that was significantly associated with immune heterogeneity and response to combination immunotherapy. Machine-learning pipeline exported the optimal 4-feature radiogenomics biomarker using support vector machine that significantly discriminated prognosis (hazard ratio 1.415–1.890; p < 0.05 for all) and modestly predicted response to ICI plus anti-angiogenic therapy (area under the curve 0.720–0.829) in independent retrospective series across major imaging modalities (computed tomography/magnetic resonance imaging). In a prospective neoadjuvant cohort, this biomarker also showed favorable performance for predicting pathological response and tumor recurrence, accompanied by biological validation through single-cell RNA-seq analysis of pre-treatment biopsies. CONCLUSIONS: Our study provides a cross-device-cross-modal radiogenomics biomarker that can improve patient selection for emerging ICI plus anti-angiogenic therapy with novel potential therapeutic targets in HCC.

Humans↗

PubMed2026

Cell-type specific activation of the cGAS-STING pathway in tumor immunotherapy: mechanisms and therapeutic implications.

BACKGROUND: The cyclic GMP–AMP synthase–stimulator of interferon genes (cGAS–STING) pathway acts as a pivotal innate immune sensor that detects cytosolic DNA and links genomic instability to antitumor immune activation. Therapeutic activation of this pathway has garnered substantial interest as a strategy to enhance cancer immunotherapy by promoting dendritic cell maturation, augmenting antigen presentation, and facilitating cytotoxic lymphocyte infiltration. However, the functional outcomes of cGAS–STING signaling are highly context dependent and influenced by both cell type and tumor microenvironmental (TME) conditions. MAIN BODY: Recent advances in single-cell and spatial transcriptomic profiling have revealed profound heterogeneity in cGAS–STING activation across distinct cellular and regional compartments within tumors. Acute and spatially restricted activation of the pathway can elicit potent antitumor immune responses, whereas chronic or dysregulated signaling may promote immune tolerance and tumor progression. Moreover, metabolic stress, epigenetic silencing, and microenvironmental immunosuppressive factors such as TGF-β and IL-10 can further modulate STING activity, leading to resistance to immunotherapy. Current translational efforts focus on next-generation STING agonists, nanoparticle-based delivery systems, and rational combination strategies with immune checkpoint blockade and metabolic modulators to overcome tumor-intrinsic resistance and minimize systemic toxicity. CONCLUSIONS: Understanding the cell-type-specific and spatial dynamics of cGAS–STING signaling is crucial for the rational design of precision immunotherapies. Future research should emphasize context-dependent modulation of STING activity to maximize therapeutic benefit while limiting adverse effects. Integrating multi-omics technologies and spatially guided drug delivery may ultimately enable personalized modulation of the cGAS–STING axis, transforming it into a clinically effective and safe strategy for cancer immunotherapy.

Humans↗