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PubMed2026

Microglial GRB2 is essential for brain ventriculogenesis and CSF homeostasis.

Microglia play essential yet poorly understood roles in brain development, including axon guidance, regulation of neurogenesis, and pruning of neuronal projections. Congenital hydrocephalus (CH), characterized by enlarged cerebrospinal fluid (CSF)-filled ventricles, is a leading cause of pediatric brain surgery, but its molecular mechanisms remain unclear. We have identified what we believe to be novel, recurrent, damaging missense variants in the SH3-binding domain of the adaptor protein Growth Factor Receptor-Bound Protein 2 (GRB2) in unrelated patients with CH. GRB2 is significantly co-expressed with one of its known upstream receptor tyrosine kinase partners, CSF1R, in the developing human brain, particularly in a microglial subtype associated with regulation of neural stem cells. Immunoprecipitation validated GRB2-CSF1R binding in mouse microglial cells and human monocyte cell line. Cx3cr1-Grb2fl/fl mice engineered with conditional deletion of Grb2 in microglia exhibit congenital absence of microglia and early postnatal severe communicating (non-obstructive) hydrocephalus, mimicking GRB2-mutant patients. The severe ventriculomegaly of Cx3cr1-Grb2fl/fl mice is associated with both depletion of cerebral cortical neurons and impairment of glia-lymphatic-mediated CSF flow. Together, these findings implicate a role of GRB2 in microglia that could be essential for brain development and CSF homeostasis.

Genetics↗

PubMed2026

Multi-omics causal inference of childhood asthma triggered by ambient particulate matter.

BACKGROUND: The causal impact of fine particulate matter (PM2.5), an established environmental risk factor, on childhood asthma and its biological mechanisms remain to be elucidated. The objective of the present study was to evaluate the causal association between PM2.5 and childhood asthma and to dissect the mediating role of plasma proteins through a multi-omics integrated Mendelian randomisation (MR) framework. METHODS: Two-sample MR was performed on large-scale genome-wide association data to estimate the causal effect of PM2.5 on childhood asthma. Genes commonly associated with PM2.5 and childhood asthma were screened by transcriptome-wide association study (TWAS) and subjected to enrichment analyses and MR. Mediator proteins were identified by two-step MR. Potential adverse effects were scanned by phenome-wide MR (Phe-MR). RESULTS: MR revealed a significant positive causal effect of PM2.5 on childhood asthma (OR=1.897, 95% CI: 1.063-3.388, p=0.030). TWAS highlighted 70 genes co-expressed in PM2.5 and childhood asthma that were enriched in inflammatory pathways such as lysosome- and leukocyte-mediated immunity. MEAF6 was validated as a protective gene and RNF40 as a risk gene for childhood asthma. Two-step MR identified FUT10 as a positive mediator mediating 19.3% of the causal effect, and CD200 and MANBA as negative mediator proteins. Phe-MR indicated the association of these genes and proteins with multiple other diseases, implying possible adverse effects from therapeutic intervention. CONCLUSION: Long-term PM2.5 exposure is causally linked to childhood asthma with MEAF6, RNF40, CD200, MANBA and FUT10 identified as key molecules. The study provides new evidence for the biological mechanisms linking PM2.5 to childhood asthma.

Journal Article↗

PubMed2026

Comparative transcriptome analysis of Qinchuan and Wagyu cattle reveals lnc11599 as a negative regulator of intramuscular fat deposition.

BACKGROUND: Intramuscular fat (IMF) content is a critical factor determining beef quality, influenced by various factors including breed and age. However, the regulatory role of long non-coding RNAs (lncRNAs) in IMF deposition remains unclear. METHODS: This study investigated IMF deposition in the longissimus dorsi muscle of one- and two-year-old Qinchuan and Wagyu cattle through histological examination and fat content measurement. Based on transcriptome sequencing data of intramuscular fat tissue, differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed to identify lncRNAs associated with IMF deposition. The effects of a key candidate lncRNA on the adipogenic differentiation of cattle intramuscular preadipocytes were further examined. RESULTS: Results showed that Wagyu cattle exhibited stronger IMF deposition capacity than Qinchuan cattle across all age groups, with IMF content increasing with age in both breeds. We identified 7,910 lncRNAs from intramuscular fat tissue transcriptome data, including 6,455 novel lncRNAs. Through integrated differential expression analysis and WGCNA, 88 lncRNAs closely associated with IMF deposition were screened from two-year-old Qinchuan and Wagyu cattle. Notably, lnc11599 was significantly upregulated in Qinchuan cattle intramuscular fat tissue, but its expression decreased during intramuscular preadipocyte differentiation. Functional experiments demonstrated that lnc11599 knockdown enhanced adipogenic differentiation capacity, manifested as a highly significant increase in lipid accumulation, upregulation of key adipogenic genes at the mRNA level, together with increases in total fatty acid content and unsaturated fatty acid proportion. CONCLUSIONS: This study established the lncRNA expression profiles in intramuscular fat tissue of Qinchuan and Wagyu cattle across different developmental stages, and demonstrated that lnc11599 acts as a negative regulator of intramuscular fat deposition. These findings provide new directions for elucidating the mechanisms of cattle IMF deposition and offer potential targets for genetic improvement of beef quality.

Animals↗

PubMed2026

Genes associated with translation and oxidative phosphorylation as components of the translational response in nodulated and water-restricted soybean.

BACKGROUND: Soybean primarily acquires nitrogen through symbiosis with nitrogen-fixing bacteria. Water deficit (WD) is a major stress limiting crop yield. Nodulation may enhance drought tolerance in legumes by modulating nitrogen and hormone metabolism, osmotic adjustment, and antioxidant defenses; however, the molecular basis underlying the differential WD responses between N-fix and N-fed plants remain unclear. Translational control of gene expression is a key regulatory mechanism during stress. RESULTS: We compared the transcriptome and translatome of soybean roots from N-fix and N-fed plants exposed to WD across four combined treatments. N-fix plants under WD exhibited more complex responses in terms of total differentially expressed genes (DEGs) compared to N-fed plants. This increased complexity was also evident among translationally regulated DEGs and differentially expressed transcription factors, whose involvement in WD responses of N-fix plants is novel. Co-expression network analysis identified modules associated with core biological processes encompassing nodulation, WD, and notably, their interplay was particularly prominent in Module 1, which was enriched in genes related to ribosomal protein synthesis and oxidative phosphorylation (OXPHOS). Guilt-by-Association analysis enabled the prediction of novel functions for differentially expressed, uncharacterized hub genes related to stress and/or nodulation responses. CONCLUSIONS: Translational regulation of genes involved in OXPHOS and translation initiation emerged as a central response in N-fix plants under WD. These findings reveal distinct molecular adaptations in N-fix soybean roots facing WD and highlight translational control as a key regulatory layer. We also identified promising candidate genes-including transcription factors and uncharacterized hub genes under translational regulation-that represent potential targets for improving drought tolerance in legumes once validated functionally.

Glycine max↗

PubMed2026

Evidence for dual pathways of Tc1/mariner domestication in Drosophila.

BACKGROUND: The domestication of transposable elements is a key source of evolutionary innovation, yet the pathways by which their functional modules are repurposed by the host remain poorly understood. The Tc1/mariner superfamily is a widespread group of DNA transposons, but the prevalence and patterns of their domestication are underexplored. RESULTS: We performed a systematic genomic screen across 43 drosophilid species using stringent criteria for molecular domestication. This analysis identified five high-confidence, evolutionarily conserved genes derived from Tc1/mariner transposases. Phylogenetic and structural analyses suggest domestication via two distinct molecular pathways: co-option of the DNA-binding module and co-option of the catalytic domain. The DNA-binding module pathway includes CG4570, the previously known genes cag and toy (the latter fused with a homeodomain), and a lineage-restricted gene in the Drosophila obscura group that exhibits signatures of recent domestication. In contrast, the catalytic domain pathway is represented solely by CG14478. Structural modeling reveals that CG14478 protein preserves a canonical DDE endonuclease fold. Co-expression network analysis suggests potential cellular roles of these genes: CG14478 is linked to RNA/chromatin-related processes, CG4570 to cell cycle/chromosome functions, cag to ciliary and nuclear functions, and toy to neuronal development. CONCLUSIONS: This study establishes a stringent framework for identifying domesticated TEs, demonstrating that Tc1/mariner elements are co-opted via two distinct pathways: retention of either catalytic or DNA-binding modules. Our findings suggest that domestication is a dynamic continuum, ranging from recent, lineage-specific events to ancient, conserved genes, and underscore how genomic conflict with TEs can drive eukaryotic evolution and regulatory complexity.

Animals↗

PubMed2026

Hepatic metabolic adaptation to endurance exercise: temporal and sex differences by multiomics integration and validation.

BACKGROUND: Although endurance exercise benefits liver health, sex-specific adaptive trajectories remain unclear. This study mapped dynamic liver adaptation in males and females during prolonged training and identified underlying molecular programs. METHODS: Using publicly available time-resolved liver multi-omics data generated by the Molecular Transducers of Physical Activity Consortium (MoTrPAC), we established a computational pipeline for differential analysis of transcriptomic, proteomic, phosphoproteomic, and metabolomic data with FDR correction, followed by FGSEA pathway enrichment. Kinase activities were inferred through ortholog mapping and PhosphoSitePlus. Cross-omics co-expression networks were constructed using WGCNA and topological overlap to link omics features with physiological phenotypes. For experimental validation, liver tissues were collected from endurance-trained Sprague-Dawley rats, and key nodes were confirmed by Western blotting, qRT-PCR, and immunofluorescence/immunohistochemical staining. Public scRNA-seq data were further integrated to map multi-omics signals to single-cell resolution and assess functional changes in specific cell types. RESULTS: The hepatic response to exercise stress was stage-specific, shifting from early transcriptional activation to later proteomic and metabolic remodeling. Multi-omics integration revealed distinct sex-associated adaptive trajectories: males were more strongly associated with energy metabolism, redox-related programs, and amino acid/organic acid catabolism, whereas females showed prominent membrane lipid remodeling, proteostasis -related programs, and mitochondrial/ribosomal translational features. Single-cell analysis showed that tissue remodeling occurred without major lineage turnover, instead involving altered communication among pre-existing cell communities. Validation of PPP1R3G identified a protein-dominant exercise-responsive marker, supporting the contribution of post-transcriptional or protein-level regulation. CONCLUSIONS: Hepatic adaptation to endurance stress follows a cross-omics evolutionary pattern with sex-specific reprogramming of energy supply and homeostatic maintenance. This time-resolved framework clarifies how exercise improves liver function and supports sex-oriented metabolic interventions and therapeutic target discovery.

Animals↗

PubMed2026

Identification and evaluation of glutamine-related gene characteristics based on multi-omics to predict the prognosis of patients with colorectal cancer.

BACKGROUND: Colorectal cancer (CRC), a prevalent malignancy of the gastrointestinal tract, ranks among the leading causes of cancer-related morbidity and mortality. Its clinical course is marked by high fatality and poor prognosis. Elucidating the mechanisms underlying CRC initiation and recurrence is therefore critical for identifying novel therapeutic targets. METHODS: This study incorporated two datasets, TCGA-CRC and GSE17537. A total of 84 glutamine metabolism-related genes (GMRGs) were identified, and differential expression analysis was conducted using the TCGA-CRC dataset. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to determine gene modules most strongly associated with GMRG scores. Single-cell RNA sequencing (scRNA-seq) was utilized to characterize key cellular clusters and to identify differentially expressed genes (DEGs) between high and low glutamine metabolism (GM) groups. Overlapping GMRGs were visualized using the ggVennDiagram package in R. A CRC risk prediction model was developed through Cox proportional hazards and LASSO regression analyses, with performance evaluated by ROC curves. Cell type enrichment across 64 immune and stromal populations was assessed via xCell, and intergroup differences were tested using the Wilcoxon rank-sum test. TIDE scores were used to estimate immunotherapy responsiveness, while oncoPredict facilitated drug sensitivity profiling. PCOLCE2 expression in CRC was validated by RT-qPCR and Western blotting. Its functional role was examined through CCK-8 assays, invasion and migration tests, flow cytometry, and glutamate quantification. RESULTS: ScRNA-seq analysis identified two key cell populations and 437 DEGs associated with GM status. WGCNA pinpointed the MEgreen module as most significantly correlated with GMRG scores, encompassing 1075 genes. Integration of DEGs, module genes, and GM-related DEGs yielded 60 candidate genes for downstream analysis. A GMRG-based prognostic model comprising six genes (SRPX, CXCL1, GPX3, PCOLCE2, CLU, SEMA3E) demonstrated strong predictive performance. Prognostic gene expression correlated with immune and stromal infiltration patterns, as indicated by Spearman correlation analysis. The high-risk group exhibited diminished predicted response to immunotherapy (TIDE scores). Drug sensitivity analysis identified four compounds—Dasatinib-51, WH-4-023-56, TWS-119-366, and LDN-193189-478—with elevated efficacy in high-risk CRC cases. PCOLCE2 expression was significantly reduced in CRC tissues. Functional assays revealed that PCOLCE2 knockdown did not substantially affect cell proliferation but significantly impaired invasion and migration in CRC cells, increased apoptosis, and suppressed both glutamine uptake and glutamate production—highlighting its oncogenic role. CONCLUSION: Six GMRGs—SRPX, CXCL1, GPX3, PCOLCE2, CLU, and SEMA3E—were identified as key components of a robust prognostic model for CRC. These findings offer valuable insights into CRC pathogenesis and potential therapeutic strategies. Notably, this study provides the first evidence implicating PCOLCE2 as a tumor-promoting factor in CRC.

Glutamine↗

PubMed2026

A modular γδ TCR-T platform combining KRAS pMHC targeting with re-dosable mRNA engager redirection.

Solid tumors often evade TCR-engineered αβ T cells when antigen expression varies or when the restricting Human Leukocyte Antigen (HLA) allele is lost. γδ T cells, in contrast, detect cellular dysregulation through non-peptide/Major Histocompatibility Complex (MHC) cues, including phosphoantigens and stress ligands, and can be developed as allogeneic therapies. Although intratumoral γδ T cell signatures are associated with improved outcome across cancers, γδ recognition itself is broad and still selected within the thymus just as αβ T cell receptors (TCRs) are. It does not, however, anchor specificity to a defined driver-mutation pMHC epitope. We therefore asked whether a high-affinity, co-receptor-independent αβ TCR could graft oncogenic-driver specificity onto γδ T cells while leaving the endogenous γδ TCR intact. We knocked the KRASG12V/HLA-A*11:01 TCR A11v into primary human γδ T cells. Engineered cells co-expressed the transgenic αβ TCR and the endogenous γδ TCR and lysed KRASG12V/HLA-A*11:01+ tumor cells in vitro and in vivo. To cover potential resistance through loss of HLA-A*11:01, we delivered an mRNA lipid nanoparticle (LNP) encoding a secreted mesothelin×CD3 (M5) bispecific T cell engager (TCE). LNP-M5 produced circulating TCE that redirected γδ A11v T cells and polyclonal bystander T cells to kill mesothelin+ targets, accompanied by development of higher γδ A11v T cell counts in vivo. In humanized mice bearing mixed HLA-A*11:01+ and HLA-A*11:01 - KRASG12V tumors, γδ A11v T cells produced transient control, whereas adding LNP-M5 yielded complete responses and prolonged survival. Thus, this two-part therapy couples invariant driver targeting to tunable redirection and addresses loss of the restricting HLA allele, a central escape route for TCR-based therapy. It provides an off-the-shelf reagent to enable KRAS-anchored treatment with the ability to redeliver the reagent.

Humans↗

PubMed2026

Metabolic-cell-death gene trio predicts survival and cuproptosis sensitivity in colorectal cancer.

BACKGROUND: Metabolic cell death (MCD) modulates colorectal cancer (CRC) progression, yet its prognostic value remains unexplored. We aimed to build an MCD-centred gene signature for outcome prediction and precision therapy. METHODS: Transcriptomes of 1,174 CRC patients were integrated. Weighted gene co-expression network analysis, differential expressions and least absolute shrinkage and selection operator (LASSO) + random survival forest were successively applied to derive a three-gene (CDKN2A/MPC1/AHCY) risk model. Functional, immune-infiltration, drug-sensitivity and genomic analyses were performed, followed by validation in fresh clinical specimens and cell lines. RESULTS: Integrative metabolic-death transcriptomics identified CDKN2A, MPC1 and AHCY as the hub drivers of CRC. Their three-gene signature robustly stratified patients into high- and low-risk subsets [3-year area under the curve (AUC) 0.83-0.85, P<0.001]. High-risk tumors were enriched for extracellular matrix (ECM)-receptor-interaction pathways, displayed abundant myeloid-derived suppressor cell (MDSC) infiltration and were more vulnerable to AZD8186, AZ960 and JAK inhibitors. Guided by these in-silico findings, we functionally confirmed that CDKN2A silencing markedly repressed proliferation, invasion and migration of SW480/HCT116 cells and potentiated cuproptosis via up-regulation of lipoylated DLAT/DLST and CTR1. CONCLUSIONS: We report the first MCD-derived prognostic platform for CRC that simultaneously predicts survival and therapeutic response. Targeting CDKN2A-enhanced cuproptosis represents a promising metabolic-precision strategy for high-risk patients.

Colorectal cancer (CRC)↗

PubMed2026

Enterocutaneous Fistula-Associated Sepsis and Mortality: Development and Validation of a Multimodal Artificial Intelligence Prediction Model.

BACKGROUND: Predicting enterocutaneous fistula (ECF)-associated sepsis and mortality poses significant challenges in digital health care due to the disease's complexity and heterogeneous clinical manifestations. Current approaches that rely on single-modal data or traditional scoring systems often fail to capture the intricate immune-inflammatory dynamics and multisystem involvement in patients with ECF. OBJECTIVE: This study aims to develop an artificial intelligence (AI)-driven multimodal fusion model integrating clinical, imaging, and transcriptomic data for early prediction of ECF-associated sepsis and 28-day mortality, addressing the limitations of conventional single-dimensional models. METHODS: This study leveraged publicly available datasets (Medical Information Mart for Intensive Care III [MIMIC-III], electronic Intensive Care Unit [eICU], and The Cancer Genome Atlas) to construct a multimodal framework. Clinical parameters were processed using Extreme Gradient Boosting, abdominal imaging features were extracted via convolutional neural networks, and transcriptomic profiles were analyzed with variational autoencoders. A Transformer-based fusion network was employed for joint prediction and validated through cross-validation and external testing. Key features were identified using Shapley Additive Explanations and Local Interpretable Model-Agnostic Explanations interpretability algorithms, while immune regulatory mechanisms were explored via weighted gene co-expression network analysis. RESULTS: The multimodal model achieved an area under the curve (AUC) of 0.89 for predicting sepsis and 28-day mortality, outperforming unimodal models (clinical-only model, AUC 0.72, and imaging-only model, AUC 0.78). Critical predictors included Sequential Organ Failure Assessment score, lactate levels, intra-abdominal free fluid on imaging, and immunoregulatory genes (programmed death-ligand 1 [PD-L1] and indoleamine 2,3-dioxygenase 1 [IDO1]). Mechanistic analysis revealed distinct immune reprogramming in patients with sepsis, characterized by increased regulatory T cells and M2 macrophages, along with downregulated cluster of differentiation 8+ (CD8+) T cells. CONCLUSIONS: This multimodal AI model offers an innovative digital solution in medical informatics, enabling precise early risk stratification for ECF-associated sepsis. By integrating multisource data and providing interpretable insights into immune-inflammatory pathways, the model enhances health care quality for patients with ECF and paves the way for personalized intervention strategies.

Humans↗

PubMed2026

Gut microbiota-derived metabolites target C5AR1/KDM2A/HCAR3 axis in inflammatory bowel disease: a multi-machine learning algorithms and molecular docking study.

BACKGROUND: Inflammatory bowel disease (IBD) is a chronic recurrent disorder. Gut microbiota-derived metabolites regulate intestinal homeostasis, but their molecular mechanisms in IBD remain unclear. Current studies lack systematic "microbiota-metabolite-target" network mining with multi-method validation. This study integrates network pharmacology, three machine learning algorithms, and molecular docking to construct this regulatory network in IBD. METHODS: Transcriptome data were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using limma (p < 0.05, |log2FC| > 0.5). Weighted gene co-expression network analysis (WGCNA) with an optimal soft threshold of β = 7 was performed to identify key module genes. Candidate genes were obtained by intersecting DEGs, gut microbiota-associated genes from the gutMGene database, and WGCNA module genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to explore the functional roles of candidate genes. Core genes were identified using three machine learning algorithms (LASSO, Boruta, and SVM-RFE), followed by protein-protein interaction (PPI) network analysis. Molecular docking was performed to assess the binding affinities between hub proteins and gut microbiota-derived metabolites. RESULTS: A total of 885 DEGs were identified between the IBD and control groups, including 463 upregulated and 422 downregulated genes. WGCNA identified 280 key module genes from the purple and yellow modules. The intersection of DEGs, gut microbiota-associated genes, and WGCNA module genes yielded 19 core candidate genes. PPI network analysis combined with three machine learning algorithms jointly identified C5AR1, KDM2A, and HCAR3 as core hub genes. ROC curve analysis demonstrated that all three hub genes achieved AUC values greater than 0.7 in both the training and validation sets, indicating excellent diagnostic performance for IBD. Enrichment analysis revealed significant associations with the TNF, NF-κB, and IL-17 signaling pathways. Molecular docking confirmed stable binding of C5AR1 with 1,3-Diphenylpropan-2-Ol (-7.87 ± 0.83 kcal·mol-¹) and HCAR3 with 3-Indolepropionic Acid (-6.35 ± 0.70 kcal·mol-¹), both below -5.0 kcal·mol-¹. CONCLUSION: This study first constructs a "gut microbiota-metabolite-hub gene" axis in IBD, providing a computational framework for microbiota-targeted precision therapy, and identifying C5AR1/KDM2A/HCAR3 as computationally predicted diagnostic biomarkers and 1,3-Diphenylpropan-2-Ol/3-Indolepropionic Acid as candidate intervention molecules that warrant further experimental validation.

Molecular Docking Simulation↗

PubMed2026

Genome-wide cis-expression Quantitative Trait Loci (eQTL) and transcriptomic signals reveal distinct molecular regulation across correlated feed efficiency traits.

INTRODUCTION: Feed efficiency (FE) is a complex trait which determines livestock production profitability, yet the molecular mechanisms behind it remain unclear. This study investigated the blood transcriptomic profile of lambs, alongside genotype data with the aim to uncover the genetic basis of FE traits such as absolute dry matter intake (DMIabsolute), DMI adjusted for body size (DMIadjusted), average daily live weight gain (ADG), and residual feed intake (RFI). MATERIALS AND METHODS: Bulk RNA-Seq and genotype data were analysed using three complementary approaches: differential gene expression (DGE) analysis, weighted gene co-expression network analysis (WGCNA), and cis-expression Quantitative Trait Loci (cis-eQTL) mapping. These methods were used independently to identify genes and regulatory networks associated with FE traits and to investigate evidence supporting multi-trait candidate gene selection. RESULTS: DGE analysis revealed 2, 24, 85 and 4 differentially expressed genes for DMIabsolute, DMIadjusted, ADG, and RFI (Padjusted < 0.05), functionally enriched in sensory perception, ATP-dependent chromatin remodeling, Notch signaling and immune response pathways. 9 gene modules significantly associated with the FE traits (P ≤ 0.05) with correlations ranging from r = -0.56 to 0.49, were identified using WGCNA. Single nucleotide polymorphism (SNP)-level cis-eQTL analysis identified 93 eSNPs associated with 74 genes (false discovery rate (FDR) < 0.05), while permutation-derived gene level analysis identified 280 eGenes (FDR < 0.2, empirical P < 0.03). Across the three analyses, applying thresholds of DGE (Padjusted < 0.05), WGCNA (correlation, P ≤ 0.05), and cis-eQTL gene-level significance (empirical P < 0.05), multiple overlapping genes were identified including DNMT3A, KANSL1, NCOR1 for DMIadjusted, ACOX2, FANCF, CIMIP2B, LOC101115106, ARMH2, LOC132657496 for ADG, and LOC114114576 for RFI representing regulators of variations in FE. DISCUSSION: The integration of DGE, WGCNA, and cis-eQTL analyses identified key genes and regulatory mechanisms associated with variation in FE traits. These results highlight that integrated multi-trait candidate gene identification approaches can reveal key genes that lower feed intake while maintaining animal growth, supporting breeding strategies aimed at improving efficiency and long-term economic sustainability in sheep.

average daily gain (ADG)↗

PubMed2026

ZBTB16-associated NK cell alterations reveal shared immunometabolic signatures linking primary Sjögren's syndrome and type 1 diabetes mellitus.

BACKGROUND: Primary Sjögren's syndrome (pSS) and type 1 diabetes mellitus (T1DM) share immune-inflammatory features, yet conserved pathogenic signatures linking these autoimmune disorders remain incompletely understood. The present research sought to uncover common molecular markers and dissect the underlying immune-metabolic cross-talk underlying pSS and T1DM. METHODS: Gene expression profiles of patients with pSS and T1DM were retrieved from the Gene Expression Omnibus database, normalized, and corrected for batch effects prior to downstream analyses. Overlapping potential biomarkers were screened by integrating differential expression analysis, weighted gene co-expression network analysis and least absolute shrinkage and selection operator regression. Functional enrichment based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases was implemented to interpret gene biological properties, and a protein-protein interaction network was further established afterwards. Diagnostic performance was evaluated using receiver operating characteristic analysis. Experimental validation was conducted in non-obese diabetic (NOD) mice using quantitative PCR, immunohistochemistry, and flow cytometry. The CIBERSORT algorithm was adopted to quantify immune cell infiltration levels. RESULTS: ZBTB16 was identified as a shared hub biomarker in both pSS and T1DM and exhibited favorable diagnostic performance. Experimental validation confirmed significantly reduced ZBTB16 expression in peripheral blood mononuclear cells, salivary gland tissues, and pancreatic tissues of NOD mice. Gene Set Enrichment Analysis indicated that ZBTB16-associated signatures were enriched in mitochondrial-related processes, neuroactive ligand-receptor interactions, and ribosome-related pathways. Immune infiltration analysis revealed that resting natural killer (NK) cells were positively correlated with ZBTB16 expression in both diseases. Flow cytometric analysis further confirmed a reduced proportion of resting NK cells in peripheral blood of NOD mice, consistent with the CIBERSORT-based prediction. CONCLUSION: This study identifies ZBTB16 as a shared biomarker linking pSS and T1DM. Reduced resting NK-cell abundance was consistently observed in both computational and experimental analyses, and bioinformatic correlation analysis suggested a positive association with ZBTB16 expression. These findings provide evidence for shared molecular and immunological signatures underlying the two autoimmune disorders and support further investigation of the biological role and diagnostic value of ZBTB16 in pSS and T1DM.

Sjogren's Syndrome↗

PubMed2026

S100P as a Shared Biomarker in Inflammatory Bowel Disease, Colorectal Cancer, and Pancreatic Adenocarcinoma: An Integrated Transcriptomic Analysis.

Inflammatory bowel disease (IBD) is associated with an increased risk of colorectal cancer (CRC) and pancreatic adenocarcinoma (PAAD), yet the molecular features shared among these diseases remain incompletely understood. This study aimed to identify common genes and biological pathways associated with IBD, CRC, and PAAD through integrated transcriptomic analysis and experimental validation. Gene expression datasets for IBD, CRC, and PAAD were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. Weighted gene co-expression network analysis and differential expression analysis were performed to identify disease-associated and shared genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (analyses were used to explore enriched biological functions and pathways. Immune cell infiltration was evaluated using Cell-type Identification by Estimating Relative Subsets of RNA Transcripts. Receiver operating characteristic analysis was performed to assess the diagnostic performance of common genes. Single-cell RNA sequencing analysis was conducted to examine the cellular distribution of S100P. In addition, the effects of S100P downregulation were evaluated in lipopolysaccharide (LPS)-stimulated colonic epithelial cells. A total of 162 disease-associated genes and four common genes were identified. Functional enrichment analyses indicated significant enrichment of immune- and inflammation-related pathways, including the interleukin-17 signaling pathway. Immune infiltration analysis revealed similar trends in several immune cell populations across IBD, CRC, and PAAD. Single-cell analysis showed elevated S100P expression in epithelial cells from all three diseases. Downregulation of S100P restored the proliferative capacity of LPS-stimulated colonic epithelial cells and reduced inflammatory cytokine expression. Integrated transcriptomic analysis identified S100P as a biomarker associated with IBD, CRC, and PAAD and highlighted shared immune-related features across these diseases.

Humans↗

PubMed2026

Human Wings Apart-Like Protein as a Serum Diagnostic Biomarker in Cervical Cancer: An Integrative Bioinformatics Analysis with Serum Validation.

Cervical cancer remains a major threat to women's health worldwide, and reliable serum biomarkers for early detection and therapeutic stratification remain limited. Human wings-apart-like (hWAPL) protein has been implicated in cervical carcinogenesis, but its diagnostic and clinical value has not been fully elucidated. To address this gap, this study integrated public multi-omics datasets, including The Cancer Genome Atlas, GEPIA2, the Human Protein Atlas, and single-cell transcriptomic data, to characterize hWAPL expression, clinicopathological associations, immune infiltration, co-expression networks, post-translational modifications, and drug sensitivity predictions. These findings were evaluated in an independent single-center serum cohort comprising 89 patients with histologically confirmed cervical squamous cell carcinoma and 89 healthy female controls. Serum hWAPL and squamous cell carcinoma antigen (SCC) levels were measured, and diagnostic performance was assessed by receiver operating characteristic curve analysis. In silico, hWAPL was broadly upregulated across multiple malignancies, particularly cervical cancer, enriched in malignant epithelial cells and monocytes/macrophages, and associated with shorter progression-free interval, predicted reduced sensitivity to cisplatin, paclitaxel, and 5-fluorouracil, and predicted sensitivity to MCL-1 and Wee1 inhibitors. In the serum cohort, hWAPL levels were significantly higher in patients than controls and discriminated cervical cancer with an area under the curve of 0.961, exceeding SCC alone. Combining hWAPL with SCC further improved diagnostic performance (area under the curve, 0.974; sensitivity, 93.3%; specificity, 95.5%). These findings suggest that serum hWAPL is a potential novel diagnostic biomarker for cervical squamous cell carcinoma whose performance is enhanced by SCC, whereas the observed associations with chemoresistance and immune microenvironment remodeling are hypothesis-generating and require experimental confirmation.

Humans↗

PubMed2026

New insights into diagnostic values and mechanisms of ferroptosis associated with immune infiltration in diabetic kidney disease.

The pathogenesis of diabetic kidney disease (DKD) is complex and closely related to ferroptosis and immune dysregulation, but the relevance is unclear. The present study investigates the potential mechanisms of ferroptosis-related genes (FRGs) in DKD and their relationship with the immune-inflammatory response. It searches for new diagnostic biomarkers to help diagnose and treat DKD. Four Gene Expression Omnibus (GEO) datasets, GSE30528, GSE30529 and GSE30122 as the test set, and GSE96804 for validation, were analyzed. FRGs were obtained from GeneCards, and 47 ferroptosis-related differentially expressed genes (FRDEGs) were identified by intersecting with DKD-related differentially expressed genes. Functional enrichment analyses, including Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, Gene Set Enrichment Analysis and Gene Set Variation Analysis, revealed that these FRDEGs are primarily associated with ferroptosis, hypoxia response and immune inflammation. Subsequently, the weighted gene co-expression network analysis (WGCNA) was employed to expand the ferroptosis-related gene network, and intersection of the 47 FRDEGs with key WGCNA module genes yielded 10 key genes. Based on the 10 key genes, the least absolute shrinkage and selection operator and support vector machine algorithms identified three hub genes [chemokine ligand 5 (CCL5), forkhead box C1 (FOXC1) and lactotransferrin (LTF)] for DKD diagnosis. Receiver operating characteristic curves confirmed their diagnostic value, with FOXC1 and LTF validated in the independent dataset. Immune infiltration analysis via CIBERSORT revealed eight immune cell types with significantly different infiltration levels between the DKD and control group in the integrated GEO datasets. Notably, both LTF and CCL5 showed a significant positive correlation with gamma delta T cells (γδT). Quantitative PCR results confirmed differential expression of the three hub genes in the DKD group, with elevated expression observed in DKD mice following intervention with rosiglitazone and hyperoside.

bioinformatics analysis↗

PubMed2026

Histopathological evaluation of RPL5 expression in triple-negative breast cancer: an integrated immunohistochemical and transcriptomic study.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer characterized by high invasiveness, limited therapeutic options, and unfavorable clinical outcomes. Ribosomal protein L5 (RPL5), a component of the large ribosomal subunit, has been implicated in ribosome biogenesis, translational regulation, and p53-associated cellular processes. This study investigated the immunohistochemical expression pattern of RPL5 in TNBC tissues and explored its potential biological significance through integrated transcriptomic analyses. Tumor tissues from 37 patients with TNBC and 7 adjacent non-tumorous breast tissues were collected from the Affiliated Tumor Hospital of Xinjiang Medical University between December 2017 and December 2023. RPL5 protein expression was evaluated by immunohistochemistry, and its association with clinicopathological characteristics was analyzed. Public transcriptomic datasets from TCGA-BRCA and GEO were further used to validate RPL5 expression patterns in TNBC. Co-expression analysis and Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to investigate potential biological functions and signaling pathways associated with RPL5. Immunohistochemical analysis demonstrated significantly lower RPL5 protein expression in TNBC tissues compared with adjacent normal breast tissues (p=0.001). In contrast, transcriptomic analyses revealed significantly higher RPL5 expression in TNBC compared with non-TNBC breast cancer subtypes (p<0.001). No significant associations were observed between RPL5 expression and clinicopathological parameters, including age, tumor size, menopausal status, TNM stage, histological grade, or lymph node metastasis (all p>0.05). Survival analysis showed no significant difference in overall survival between patients with high and low RPL5 expression. Functional enrichment analyses indicated that RPL5-related genes were predominantly involved in ribosome biogenesis, translational regulation, and p53-related signaling pathways. These findings suggest that abnormal RPL5 expression may be associated with TNBC biology through ribosome-related programs, although causal roles require functional validation. RPL5 may represent a potential histopathological and molecular indicator associated with TNBC biology, although its precise functional role requires further experimental validation.

Humans↗

PubMed2026

Gastric amphicrine carcinoma in the stomach: an unexpected presentation of MUTYH-associated polyposis.

Amphicrine carcinomas of the stomach, defined by dual exocrine and neuroendocrine differentiation within the same neoplastic cell, are exceedingly rare. MUTYH-associated polyposis (MAP) is an autosomal recessive polyposis syndrome characterized by multiple colorectal adenomas and variable upper gastrointestinal involvement; however, amphicrine carcinomas have not been previously documented in this setting. We report a gastric amphicrine carcinoma arising in the background of extensive fundic gland polyposis in a patient with MAP. Endoscopy revealed a 3.5-cm flat elevated lesion in the gastric fundus amid extensive fundic gland polyposis. Histologically, the tumor consisted of a single population of cells exhibiting combined glandular and neuroendocrine differentiation without zonal or biphasic architecture, and many of these cells demonstrated true amphicrine morphology. Immunohistochemistry confirmed co-expression of cytokeratin and the neuroendocrine markers chromogranin A and synaptophysin in the same cell population. Germline targeted next-generation sequencing identified biallelic MUTYH variants in trans (c.733C>T, p.Arg245Cys [likely pathogenic]; c.842C>T, p.Ala281Val [variant of uncertain significance]), supporting a diagnosis of MAP. To our knowledge, this is the first reported case of a gastric amphicrine carcinoma in a MAP patient, expanding the spectrum of MAP-associated upper gastrointestinal neoplasia and underscoring the importance of vigilant endoscopic surveillance in hereditary polyposis syndromes.

Carcinoma↗