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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↗

PubMed2025

Dissecting adult plant resistance to stem rust through multi-model GWAS in a diverse barley germplasm panel.

INTRODUCTION: Stem rust (SR), caused by Puccinia graminis f. sp. tritici (Pgt), remains a major threat to global barley production, particularly in regions with conducive environments and evolving pathogen populations. Despite progress in understanding seedling resistance, adult plant resistance (APR) to SR remains underexplored in diverse barley germplasm. This study aimed to dissect the genetic architecture of APR to SR in a panel of diverse origins of two-row spring barley using a genome-wide association study (GWAS). METHODS: A total of 273 barley accessions were evaluated for APR to SR in two distinct environments in Kazakhstan. Phenotypic data were combined with high-density SNP genotyping to perform GWAS using five statistical models (GLM, MLM, MLMM, FarmCPU, and BLINK). Population structure and kinship were accounted for to identify robust marker-trait associations (MTAs), followed by haplotype-based QTL delineation. Transcriptomic data from 16 barley tissues were used to identify candidate genes within major QTL regions. Substantial phenotypic variation in SR severity was observed across environments. RESULTS: A total of 204 MTAs were identified, among which 96 were stable across models, resulting in 19 model-stable QTLs spanning all seven barley chromosomes. Six QTLs co-localized with known SR-resistance QTLs and genes, including Rpg1 and Rpg6. Q_rpg_7H.1 (coinciding with Rpg1) was one of the strongest and most consistent QTL, harboring 42 highly expressed candidate genes. A novel major-effect QTL on chromosome 5H, Q_rpg_5H.1 (3.5 - 9.9 Mb), not previously associated with known resistance loci, contained 10 highly expressed genes grouped into three co-expression clusters, including WRKY transcription factors and PR-5 proteins. CONCLUSION: This study provides new insights into the complex, multilayered genetic control of SR resistance in barley. The discovery of both known and novel QTLs offers valuable targets for marker-assisted selection and lays the foundation for breeding durable SR-resistant barley adapted to diverse agroecological conditions.

Hordeum vulgare L.↗

PubMed2026

Integrated Metabolomic and Transcriptomic Analysis Reveals Tissue-Specific Secondary Metabolic Differentiation and Indole Alkaloid Accumulation in Evodia rutaecarpa.

Evodia rutaecarpa is a valuable medicinal plant, yet its non-medicinal tissues remain largely underexplored. Here, we integrated ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS)-based widely targeted metabolomics and RNA sequencing (RNA-seq) transcriptomics to systematically profile the metabolic and transcriptional landscapes of roots, stems, leaves, and flowers of Evodia rutaecarpa (Juss.) Benth. Our aim was to characterize tissue-specific metabolic differentiation and its underlying transcriptional regulatory mechanisms. Metabolomic analysis, employing principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) with robust model parameters (R2Y > 0.9, Q2 > 0.5), identified 3090 differential metabolite features (variable importance in projection, VIP > 1.0; p < 0.05) across the four tissues, which exhibited distinct tissue-specific clustering patterns. Integrated Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and weighted gene co-expression network analysis (WGCNA) revealed that roots specifically accumulated quinolone alkaloids and flavonoid glycosides, accompanied by the coordinated upregulation of genes involved in flavonoid and phenylpropanoid biosynthetic pathways. In contrast, stems, leaves, and flowers were enriched in indole alkaloids (evodiamine and rutaecarpine) and volatile oil precursors, with concurrent upregulation of genes involved in tryptophan metabolism and indole alkaloid biosynthesis (e.g., tryptophan decarboxylase, TDC; s N-methyltransferase, NMT). Notably, leaves and flowers displayed particularly high accumulation levels of these bioactive alkaloids, suggesting their potential as alternative sources for industrial and pharmaceutical applications. WGCNA further identified multiple transcription factors and structural gene modules tightly correlated with evodiamine accumulation, offering promising candidate regulators for future biosynthetic pathway engineering. Collectively, this multi-omics integration study systematically elucidates the tissue-partitioned secondary metabolism of Evodia rutaecarpa (Juss.) Benth. and provides a solid scientific foundation for full-plant resource utilization, targeted development of non-medicinal tissues, and future metabolic engineering of indole alkaloid production.

Evodia rutaecarpa↗

PubMed2026

Comprehensive Identification of WDR Gene Family in Panax ginseng: PgWDR Gene Expression Analysis with Ginsenosides Biosynthesis Under MeJA.

Panax ginseng (Panax ginseng C.A. Mey.) produces pharmacologically valuable ginsenosides. WD40-repeat (WDR) proteins act as versatile regulators of plant specialized metabolism, yet their biological roles under methyl jasmonate (MeJA) elicitation remain largely uncharacterized in ginseng. In this study, we identified 29 PgWDR family members at the whole-genome level, and systematically analyzed their phylogeny, gene structure, cis-acting promoter elements, as well as organ- and development-dependent expression patterns. Six candidate genes potentially associated with ginsenoside biosynthesis were screened through integrating gene-metabolite correlation analysis and gene co-expression analysis. Under MeJA treatment, three of these candidates showed statistically significant expression responses, while the other three exhibited variable expression fluctuations with no statistical significance. PgWDR24 displayed a positive correlation with key ginsenoside biosynthetic enzyme genes, and a negative correlation with protopanaxadiol-type ginsenoside accumulation. Combined with its predicted nuclear localization, we hypothesize that PgWDR24 participates in the negative modulation of protopanaxadiol-type ginsenoside accumulation, although further genetic functional validation is still required. This work provides valuable candidate genes for deciphering ginsenoside regulatory networks and offers support for molecular-assisted breeding of high-quality ginseng.

Panax ginseng C. A. Mey.↗

PubMed2025

Multi-Omics and Integrative Analytics in Natural Products Discovery.

Natural products (NPs) have long been an essential source of new bioactive compounds for drug discovery; however, traditional methods for screening and isolating these compounds can be slow and often yield diminishing returns. Fortunately, advanced multi-omics and computational approaches present powerful solutions to these challenges. This review highlights innovative methodologies that integrate metabolomics, genomics, transcriptomics, and proteomics with bioinformatics and analytical chemistry to accelerate NP discovery. For instance, untargeted metabolomics platforms like high-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) and Global Natural Products Social (GNPS) molecular networking allow for comprehensive profiling of new compounds, while targeted isotope-labeling strategies enhance this process. Additionally, genome and metagenome mining tools such as antibiotics and secondary metabolite analysis shell (antiSMASH), Deep Biosynthetic Gene Cluster (DeepBGC), and Pipeline for Reconstructing Integrated Syntheses of Metabolites (PRISM) quickly identify biosynthetic gene clusters (BGCs) in both cultured and uncultured organisms, often using heterologous expression to validate products. Transcriptomic analyses, including RNA sequencing (RNA-seq), co-expression networks, and fluxomics, help clarify how pathways are regulated, while quantitative proteomics techniques like tandem mass tags/isobaric tags for relative and absolute quantitation (TMT/iTRAQ) and label-free methods, along with chemoproteomics approaches such as cellular thermal shift assay and thermal proteome profiling (TPP), uncover molecular targets and their mechanisms of action. This review also places significant emphasis on the role of artificial intelligence (AI) and machine learning (ML) in integrating multi-omics data, spanning activities from constructing gene-metabolite correlation networks to leveraging knowledge graphs and graph neural networks for data fusion and functional prediction. Finally, this review concludes by discussing the synergistic benefits of multi-omics for natural-product discovery, addressing current technical challenges, and exploring future directions toward high-throughput, intelligent data integration for next-generation NP research.

Biological Products↗

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

LINC01871-Mediated Sensitivity to Cyclin-Dependent Kinase 4/6 Inhibitors in Human Breast Cancer.

Breast cancer remains the most frequently diagnosed malignancy in women, and resistance to cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors limits long-term treatment efficacy. This study aimed to identify long non-coding RNAs (lncRNAs) associated with predicted sensitivity to CDK4/6 inhibitors and to investigate their biological functions in breast cancer. Transcriptomic data from The Cancer Genome Atlas (TCGA) and drug sensitivity data from the Genomics of Drug Sensitivity in Cancer 2 (GDSC2) database were integrated, and drug sensitivity was predicted using the oncoPredict algorithm. Candidate lncRNAs were identified through differential expression analysis, weighted gene co-expression network analysis, prognostic analysis, and machine learning. The biological functions of LINC01871 were subsequently evaluated using in vitro and in vivo experiments. Sixty-two lncRNAs associated with predicted sensitivity to ribociclib and palbociclib were identified, and six core lncRNAs were selected. LINC01871 showed the highest discriminatory performance for predicted drug sensitivity. Overexpression of LINC01871 was associated with increased sensitivity of breast cancer cells to ribociclib and palbociclib, inhibition of cell proliferation, promotion of apoptosis, and suppression of nuclear factor kappa B (NF-κB) signaling. Single-cell transcriptomic analysis demonstrated high LINC01871 expression in T cells and natural killer (NK) cells, while transcriptome-based immune infiltration analyses showed that high LINC01871 expression was associated with increased immune infiltration. These findings identify LINC01871 as a candidate biomarker of sensitivity to CDK4/6 inhibitors and demonstrate its tumor-suppressive effects in breast cancer. Further clinical and mechanistic studies are required to validate its predictive value and therapeutic relevance.

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

CCT2 defines a highly cisplatin-resistant and poor-prognosis subtype of lung adenocarcinoma.

Cisplatin-based chemotherapy is a standard treatment for lung adenocarcinoma (LUAD), yet acquired cisplatin resistance remains a marked cause of treatment failure. The molecular mechanisms driving cisplatin resistance in LUAD have not been fully elucidated. The present study integrated bulk transcriptomic data, genomic mutation profiles and single-cell RNA sequencing data to systematically investigate cisplatin resistance in LUAD. Resistance-associated genes were identified through differential expression, survival analysis and database integration. Unsupervised clustering was used to define cisplatin resistance-associated subtypes. Functional characteristics were explored using pathway enrichment, immune infiltration, tumor mutation burden and weighted gene co-expression network analysis. A machine learning framework incorporating 101 algorithms was applied to identify key genes and construct a prognostic model. Single-cell analyses and in vitro experiments were performed to validate the biological role of the core gene. Molecular docking and molecular dynamics simulations were conducted to identify potential therapeutic compounds. A total of two molecular subtypes with distinct cisplatin resistance levels and prognostic outcomes were identified. The high-resistance subtype exhibited enhanced cell cycle activity, DNA repair signaling and immune heterogeneity. Machine learning analysis revealed a five-gene signature, with chaperonin-containing TCP1 subunit 2 (CCT2) emerging as a key regulator of cisplatin resistance. Single-cell analyses showed that CCT2 was predominantly enriched in resistant epithelial cell subpopulations. Functional experiments demonstrated that CCT2 knockdown significantly inhibited cell proliferation and enhanced cisplatin sensitivity in LUAD cell lines. A number of candidate compounds targeting CCT2 exhibited stable binding in silico. The present findings identified CCT2 as a key mediator of cisplatin resistance in LUAD and provided potential therapeutic strategies to overcome chemotherapy resistance.

chaperonin-containing TCP-1 subunit 2↗

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↗

PubMed2026

Analysis of end-stage renal disease mediated by cuproptosis-related genes.

OBJECTIVE: The complex pathophysiological mechanism of end-stage renal disease (ESRD) has not been fully understood. Cuproptosis is a newly discovered type of programmed cell death. Therefore, this study attempts to clarify the relationship between cuproptosis-related genes (CRGs) and the phenotype of ESRD. MATERIALS AND METHODS: The National Center for Biological Information Gene Expression Omnibus database was applied to obtain the GSE37171 dataset comprising whole-genome microarray analysis of peripheral blood samples. A 3 : 1 case-control design was employed with 75 ESRD patients and 20 healthy controls who were frequency-matched for age, sex, and ethnicity. Based on differentially expressed genes (DEGs) and genes related to cuproptosis, CRGs were identified. Thereafter, we explored two different subpopulations based on the cuproptosis gene and analyzed their expression and immune infiltration. Genes specific to the CRG cluster were identified through the weighted gene co-expression network analysis algorithm, and the best prediction model was determined and verified by four machine learning methods. RESULTS: The study identified 14 differentially expressed CRGs, among which ATP7B, SLC31A1, LIAS, LIPT1, DLD, MTF1, CDKN2A, DBT, and DLST had relatively high expression levels in the ESRD samples. Compared with the control group, expression levels of FDX1, DLAT, PDHA1, PDHB, and GLS were significantly lower in the ESRD group, and CRGs played a key role in the regulation of immune infiltration in ESRD. Two cuproptosis-related molecular clusters were identified in the ESRD samples. Cluster2 was more correlated with the immune infiltration of ESRD. By analyzing the intersection points between CRG cluster and key genes of ESRD, a total of 888 specific DEGs were identified. Functional differences related to specific DEGs were further explored using gene set variation analysis. Five significant genes (SMC5, USP47, USP53, AGA, and DMXL1) were identified by the support vector machine model as key predictors for ESRD disease risk, achieving an area under the curve (AUC) of 1.00 in internal validation. However, external validation in independent cohorts is required prior to clinical application. Individual gene analysis showed an AUC > 0.81 in discriminating ESRD patients from healthy controls, and the expression of all 5 genes in ESRD patients was significantly lower than in the control group. CONCLUSION: This study clarified the relationship between CRGs and the phenotype of ESRD, analyzed their specific roles in the immune microenvironment, and obtained a predictive model, providing new insights for the study of its potential therapeutic targets.

Humans↗

PubMed2026

Distinct periarticular muscle transcriptomes: inflammation in rheumatoid arthritis versus metabolic dysregulation in osteoarthritis.

OBJECTIVES: Periarticular skeletal muscle abnormalities are recognised in rheumatoid arthritis (RA) and osteoarthritis (OA), but their divergent molecular pathologies are poorly defined. This study aimed to elucidate and directly compare the transcriptomic profiles of periarticular muscle in patients with RA and OA. METHODS: We performed bulk RNA sequencing of periarticular skeletal muscle samples collected during total joint arthroplasty from RA (n=6) and OA (n=4) patients. Differential gene expression analysis, weighted gene co-expression network analysis (WGCNA), pathway enrichment, and gene set variation analyses were conducted to identify disease-specific molecular features and their clinical associations. RESULTS: The two conditions showed fundamentally distinct profiles. RA muscle exhibited a pronounced inflammatory signature, characterised by upregulation of cytokine-responsive genes including FOS, EGR1, and CXCL2, and enrichment of tumour necrosis factor-α and interleukin-6 (IL-6)/JAK-STAT3 signalling. In contrast, OA muscle was characterised by metabolic dysregulation, with upregulation of genes linked to adipogenesis (PCK1, SFRP4) and significant enrichment of epithelial-to-mesenchymal transition (EMT) signalling. These divergent profiles were further supported by WGCNA, which identified distinct modules reflecting heightened innate immune and complement activation in RA, and disrupted metabolic processes in OA. Notably, in RA, the IL-2-STAT5 signalling pathway was unique among those tested in showing a strong positive correlation with DAS28-ESR (r=0.94, p=0.019). CONCLUSIONS: This study reveals distinct molecular pathologies in the periarticular muscle of RA and OA. RA muscle shows an intense inflammatory profile potentially linked to cachexia, whereas OA muscle displays features of metabolic disease and pro-fibrotic remodelling.

Humans↗

PubMed2024

Polycystic ovarian syndrome (PCOS) and recurrent spontaneous abortion (RSA) are associated with the PI3K-AKT pathway activation.

AIMS: We aimed to elucidate the mechanism leading to polycystic ovarian syndrome (PCOS) and recurrent spontaneous abortion (RSA). BACKGROUND: PCOS is an endocrine disorder. Patients with RSA also have a high incidence rate of PCOS, implying that PCOS and RSA may share the same pathological mechanism. OBJECTIVE: The single-cell RNA-seq datasets of PCOS (GSE168404 and GSE193123) and RSA GSE113790 and GSE178535) were downloaded from the Gene Expression Omnibus (GEO) database. METHODS: Datasets of PSCO and RSA patients were retrieved from the Gene Expression Omnibus (GEO) database. The "WGCNA" package was used to determine the module eigengenes associated with the PCOS and RSA phenotypes and the gene functions were analyzed using the "DAVID" database. The GSEA analysis was performed in "clusterProfiler" package, and key genes in the activated pathways were identified using the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Real-time quantitative PCR (RT-qPCR) was conducted to determine the mRNA level. Cell viability and apoptosis were measured by cell counting kit-8 (CCK-8) and flow cytometry, respectively. RESULTS: The modules related to PCOS and RSA were sectioned by weighted gene co-expression network analysis (WGCNA) and positive correlation modules of PCOS and RSA were all enriched in angiogenesis and Wnt pathways. The GSEA further revealed that these biological processes of angiogenesis, Wnt and regulation of cell cycle were significantly positively correlated with the PCOS and RSA phenotypes. The intersection of the positive correlation modules of PCOS and RSA contained 80 key genes, which were mainly enriched in kinase-related signal pathways and were significant high-expressed in the disease samples. Subsequently, visualization of these genes including PDGFC, GHR, PRLR and ITGA3 showed that these genes were associated with the PI3K-AKT signal pathway. Moreover, the experimental results showed that PRLR had a higher expression in KGN cells, and that knocking PRLR down suppressed cell viability and promoted apoptosis of KGN cells. CONCLUSION: This study revealed the common pathological mechanisms between PCOS and RSA and explored the role of the PI3K-AKT signaling pathway in the two diseases, providing a new direction for the clinical treatment of PCOS and RSA.

Humans↗

PubMed1978

Regulation of immunoglobulin biosynthesis in the murine plasmacytoma MOPC 315.

We have examined certain aspects of IgG biosynthesis by constructing hybrids between MPC11 (gamma2b, kappa) and MOPC 315 (alpha,lambda2) that have lost the ability to synthesize one or the other heavy chain. Cells express the three chains in a stable fashion, and both autologous (parental) and heterologous (nonparental) H and L chain pairs form and are secreted. The alpha H chain was found in polymeric form when associated with the heterologous kappa L chain. The lambda2 L chain covalently assembled to the heterologous gamma2b H chain. Surprisingly, autologous pairing was always favored over heterologous pairing in vivo by 5 to 10:1 in terms of rate of assembly. Similar ratios were maintained in the secreted protein. These results suggest that co-expression of particular H and L chain pairs is predetermined. Evolution presumably operates to improve antigen recognition as well as rate of assembly of active molecules.

Animals↗

PubMedDate not supplied

Vimentin expression in benign and malignant lesions in the human mammary gland.

The distribution pattern of vimentin in mammary gland lesions, including benign lesions (36 cases) and adenocarcinomas (40 cases), was studied with the use of a monoclonal antibody. In myoepithelial cells of mastopathy, the positive vimentin staining was seen in 6 cases (33.3%). Gynecomastia showed strong vimentin expression in myoepithelial cells. Fibroadenomas (14 cases) expressed positive vimentin staining in 8 cases (57.1%) with various staining intensities in myoepithelial cells. Lactating mammary gland tissue was positive for vimentin staining in narrow myoepithelium. In adenocarcinoma, positive reactions in tumor cells were found in 17 cases (41.2%) of solid tubular, 12 cases (33.3%) of papillo-tubular, and 11 cases (54.5%) of scirrhous carcinomas. The staining intensity for vimentin was weak in modified myoepithelial cells and neoplastic cells. Malignant cells in mammary carcinomas with vimentin reactivity usually expressed keratin staining; thus a co-expression of vimentin and keratin was found in mammary carcinomas.

Adenocarcinoma↗

PubMed2025

Whole genome duplication drives transcriptome reprogramming in response to drought in alfalfa.

Genome doubling did not enhance drought tolerance in alfalfa, but may set the stage for long-term adaptation to drought through a novel transcriptional landscape. Whole genome duplication (WGD) has been shown to enhance stress tolerance in plants. Cultivated alfalfa is autotetraploid, but diploid wild relatives are important sources of genetic variation for breeding. Investigating how WGD affects gene expression in stress conditions could provide better understanding for use of diploid genetic resources. In this work, we compared the drought response of neotetraploid plants obtained by bilateral sexual polyploidization with diploid full sibs, by measuring physiological and biochemical traits and RNA-seq. Without drought, 4x plants had lower photosynthetic potential than 2x plants per unit leaf area, but larger leaves allowed them to outperform the per leaf photosynthetic potential of 2x plants. Physiological and biochemical traits were significantly affected by drought in both 2x and 4x plants, but the differences between ploidies were small and nonsignificant. Proline levels were higher in 4x than 2x plants, both in control and drought conditions, indicating that larger cells with higher volume-to-surface ratio of 4x  plants require a higher osmolyte concentration. RNA-seq and gene network analyses showed that more genes were affected by drought at 4x than at 2x level, with downregulation of hundreds of genes involved in photosynthesis and stomatal movement at 4x level, suggesting that WGD made the 4x plants more responsive to drought. Genes involved in proline, phytormone and cell wall functions were also transcriptionally affected by drought in 4x plants. We conclude that WGD did not immediately enhance drought tolerance in alfalfa, but may set the stage for long-term adaptation to drought through a novel transcriptional landscape.

Medicago sativa↗