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Results for “Functional enrichment analysis”

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PubMed2024

Relationship between inflammation/immunity and epilepsy: A multi-omics mendelian randomization study integrating GWAS, eQTL, and mQTL data.

OBJECTIVES: Increasing evidence suggests that activated innate/adaptive immunity induces an inflammatory response, thereby participating in epileptogenesis. However, the biological explanation of inflammation/immunity as a potential cause for epilepsy remains largely unknown. This research aimed to determine the causal effects of inflammation/immune-related genes in epilepsy based on multi-omics mendelian randomization (MR). METHODS: We employed summary-data-based MR (SMR) approach to combine GWAS for epilepsy (12,891 cases and 312,803 control) with gene expression quantitative trait loci (cis-eQTL, 31,684 participants) and DNA methylation QTL (cis-mQTL, 1,980 participants) data. Five additional MR methods were then used for sensitivity analyses to confirm the reliability of causal associations. In addition, enrichment analysis of key genes was conducted to provide insight into the biological functions of epilepsy risk variants. RESULTS: A total of 386 inflammation/immune-related genes were selected for further analyses. Primary SMR analysis indicated that 37 DNA methylation sites and six genes regulated by them had potential causal relationship with epilepsy. MR analysis further refined the results, identifying three genes that had a causal effect on epilepsy. Notably, VEGFA (OR: 0.925; 95 % CI: 0.862-0.994) expression was negatively correlated with epilepsy risk, whereas IL16 (OR: 1.076; 95 % CI: 1.028-1.126) and HLA-DPA1 (OR: 1.041; 95 % CI: 1.009-1.074) expressions were positively associated with epilepsy risk. Functional enrichment analysis revealed that the identified genes were involved in GO-BP terms related to VEGF activation signaling and chemotaxis regulation. CONCLUSION: This analysis confirms the causal role of inflammation/immunity in epilepsy, and the identified candidate genes provide clues for drug development in clinical practice.

Humans↗

PubMed2026

Identification of a novel human gut microbes and microbial metabolites related genes signature for prognostic implication in head and neck squamous carcinomas.

BACKGROUND: The gut microbiota acts as a critical driver influencing the pathogenesis, therapeutic response, and clinical outcomes across various cancer types. This study aimed to investigate the prognostic value of human gut microbes and microbial metabolites related genes (HGMMMRGs) in head and neck squamous cell carcinoma (HNSCC). METHODS: We constructed a prognostic risk model comprising 19 core HGMMMRGs using LASSO penalized regression and a multivariate Cox proportional hazards model. The predictive performance of the model was evaluated through Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, nomograms, and concordance index. In addition, functional enrichment analysis was performed on the differentially expressed risk genes. Furthermore, the relationship between the immune microenvironment of HNSCC and the risk diagnostic model was examined. Western blot analysis was used to assess the expression levels of IL10 in both HNSCC tissues and adjacent normal tissues. Finally, the correlation between IL10 and the gut microbiota was explored. RESULTS: This study developed a risk score model integrating 19 HGMMMRG genes, which can serve as a tool to guide prognosis and immune microenvironment assessment in HNSCC patients. Survival analysis showed that patients in the high-risk group had significantly worse outcomes (P < 0.05). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed significant enrichment of differentially expressed genes (DRLs) and immune-related pathways. Western blot analysis further confirmed that IL10 was highly expressed in HNSCC, and the abundance of Faecalibacterium prausnitzii and Enterococcus durans colonies was correlated with IL10 expression. CONCLUSION: We developed a prognostic model for HGMMMRGs that can be effectively used to predict OS in patients with HNSCC. Second, Faecalibacterium prausnitzii and Enterococcus durans can influence the prognosis of patients with HNSCC by mediating the expression IL10 and thereby affecting the prognosis of HNSCC patients. Thus, human gut microbes and microbial metabolite-related genes may be another promising strategy for the treatment of patients with HNSCC.

HNSCC↗

PubMed2026

Decreased expression of Krüppel-like factor 4 is associated with colorectal cancer progression.

Krüppel-like factor 4 (KLF4), a key transcription factor,plays an important role in cell proliferation, differentiation, and apoptosis. Here, we explored the prognostic value of KLF4 and its role in colorectal cancer (CRC) progression. We analyzed transcriptomic data and clinical information related to CRC from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. database. Immunohistochemistry was performed to evaluate KLF4 expression in CRC tissue samples. Additionally, we examined the relationship between clinicopathological factors and patient prognosis using Cox proportional hazards model analysis. Lentiviral transfection was used to create KLF4 knockdown HCT-116 cells. Analysis of the TCGA database and two GEO datasets (GSE21510 and GSE117606) revealed that KLF4 was expressed at low levels in CRC. Furthermore, reduced KLF4 levels correlated with lymph node metastasis, distant metastasis, and advanced TNM staging. ROC curve analysis indicated that KLF4 can effectively differentiate cancerous tissue from normal tissue. Functional enrichment analysis identified KLF4 as significantly linked to the glycoprotein metabolic pathway. Our detection of KLF4 expression in CRC tissue samples confirmed its decreased levels and their association with poorer patient survival. However, KLF4 was not identified as an independent prognostic factor. In vitro, KLF4 knockdown promoted HCT-116 cell migration and invasion and downregulated the mRNA expression of glycoprotein synthesis- and glycosylation-related genes. Conversely, KLF4 re-expression markedly reversed these effects. Our findings suggested that low KLF4 expression served as a predictor factor for disease progression in CRC patients. Furthermore, reduced KLF4 levels enhance the migration and invasion of CRC cells, which may be related to impaired glycoprotein metabolism.

Colorectal cancer↗

PubMed2025

Proteomic hub proteins CDKN2B, TRAPPC2L, WFS1, and ARPP19 drive biochemical recurrence and metastatic progression in prostate cancer: Protein macromolecule action.

The biological characteristics and metastasis mechanism of prostate cancer are complex, involving the important role of many proteins in cell transcriptional regulation. This study focused on the role of the proteomic hub proteins CDKN2B, TRAPPC2L, WFS1 and ARPP19 in the biochemical recurrence and metastasis progression of prostate cancer. Cross-platform transcriptome integration and differential expression analysis were used to evaluate transcriptome characteristics in a prostate cancer cohort. Functional enrichment analysis was performed by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation, and weighted gene co-expression network analysis (WGCNA) was used to investigate cancer progression subtypes. It was found that prostate cancer progression showed significant transcriptome heterogeneity, and low-expression genes dominated. We reveal the important role of epithelial-immune interactions and inflammatory signaling in transcriptional remodeling in prostate cancer. The co-expression network topology analysis showed that the immune-metabolic center module plays a central role in cancer progression. CDKN2B was identified as a key transcriptional determinant in prostate cancer typing, while TRAPPC2L and WFS1 acted as core transcriptional regulators, driving metastatic heterogeneity. ARPP19 and LOC650152 also show important transcriptional driving effects in advanced prostate cancer.

Humans↗

PubMed2026

Prognostic value of genes associated with metastasis and propionate metabolism in rectal cancer.

BACKGROUND: Research indicates that alterations in propionate metabolic pathways play a critical role in cancer development and invasion. Postoperative metastatic recurrence remains a major cause of mortality in patients with rectal cancer. However, propionate metabolism-related genes (PMRGs) in rectal cancer remain insufficiently characterized. Therefore, this study aimed to identify prognostic biomarkers associated with lymph node metastasis and propionate metabolism and construct a risk‑prediction model for rectal cancer via bioinformatic analyses. METHODS: The Cancer Genome Atlas-Rectum Adenocarcinoma (TCGA-READ) and GSE87211 datasets, together with a curated PMRGs gene set, were used in this study. Pearson correlation analysis was performed to assess associations between overlapping genes (differentially expressed genes between READ and normal tissues, as well as between N0 and N1-N2 stages) and PMRGs, leading to the identification of candidate genes. Functional enrichment analyses were subsequently conducted to characterize the biological roles of these candidates. Prognostic biomarkers were identified using univariate Cox regression combined with least absolute shrinkage and selection operator (LASSO) regression, and a prognostic model was constructed accordingly. Independent prognostic validation was then performed. In addition, immune checkpoint profiling and immunotherapy response analyses were conducted across risk subgroups. Single-gene Gene Set Enrichment Analysis (GSEA) was applied to elucidate the pathways associated with the identified biomarkers. Finally, drug sensitivity analyses were performed. RESULTS: A total of 157 candidate genes were identified through the analytical pipeline. Functional enrichment analysis indicated that these genes were primarily involved in inflammatory response regulation and tumor necrosis factor (TNF) signaling pathways. Five prognostic biomarkers were subsequently identified and incorporated into a predictive model. External validation using the GSE87211 cohort confirmed the robustness of the model. Risk score and disease status were identified as independent prognostic factors. Six immune checkpoint molecules exhibited differential expression between risk groups. Correlation analyses revealed that the risk score was positively associated with most immune checkpoint genes. Single-gene GSEA demonstrated that the biomarkers were mainly enriched in ribosomal biogenesis and cell adhesion molecule-related pathways. Furthermore, 51 therapeutic agents exhibited significantly different half-maximal inhibitory concentration (IC50) values between risk subgroups. CONCLUSIONS: This study identified five biomarkers (CCL24, IGFBP3, ODC1, PYGM, and VKORC1) associated with lymph node metastasis and propionate metabolism pathways, providing a potential foundation for prognostic prediction in patients with rectal cancer.

Rectal cancer↗

PubMed2005

EXPANDER--an integrative program suite for microarray data analysis.

BACKGROUND: Gene expression microarrays are a prominent experimental tool in functional genomics which has opened the opportunity for gaining global, systems-level understanding of transcriptional networks. Experiments that apply this technology typically generate overwhelming volumes of data, unprecedented in biological research. Therefore the task of mining meaningful biological knowledge out of the raw data is a major challenge in bioinformatics. Of special need are integrative packages that provide biologist users with advanced but yet easy to use, set of algorithms, together covering the whole range of steps in microarray data analysis. RESULTS: Here we present the EXPANDER 2.0 (EXPression ANalyzer and DisplayER) software package. EXPANDER 2.0 is an integrative package for the analysis of gene expression data, designed as a 'one-stop shop' tool that implements various data analysis algorithms ranging from the initial steps of normalization and filtering, through clustering and biclustering, to high-level functional enrichment analysis that points to biological processes that are active in the examined conditions, and to promoter cis-regulatory elements analysis that elucidates transcription factors that control the observed transcriptional response. EXPANDER is available with pre-compiled functional Gene Ontology (GO) and promoter sequence-derived data files for yeast, worm, fly, rat, mouse and human, supporting high-level analysis applied to data obtained from these six organisms. CONCLUSION: EXPANDER integrated capabilities and its built-in support of multiple organisms make it a very powerful tool for analysis of microarray data. The package is freely available for academic users at http://www.cs.tau.ac.il/~rshamir/expander.

Algorithms↗

PubMed2026

Role of IFIT1 and IFIT3 in systemic lupus erythematosus: modeling a diagnosis and exploring immune regulation.

Systemic lupus erythematosus (SLE) is a complex autoimmune disorder characterized by multi-organ involvement and a protracted clinical course. Current diagnostic strategies, which rely heavily on clinical symptoms and serology, are often insufficient for early detection. Therefore, highly accurate diagnostic biomarkers are urgently needed to facilitate early intervention and optimize personalized treatment strategies. D atasets GSE61635 and GSE135779 were integrated to identify differentially expressed genes. Weighted gene co-expression network analysis (WGCNA) was performed to isolate the module with the strongest clinical relevance. Mendelian randomization and single‑cell RNA‑seq were used to identify key disease‑relevant genes. A diagnostic model was then constructed, and gene set variation analysis (GSVA), along with gene set enrichment analysis (GSEA), was conducted to elucidate the underlying molecular pathways. IFIT1 and IFIT3 were identified as 2 core genes highly expressed in monocytes and T cells of SLE patients. Functional enrichment analysis revealed that these genes were enriched in immune-related pathways, metabolic pathways related to inflammation and genomic stability. The diagnostic model showed good accuracy, with an area under the curve (AUC) of 0.974 on the training set and 0.912 on the validation set. IFIT1 and IFIT3 represent promising biomarkers for diagnosing SLE and appear to mediate key immune and metabolic disturbances. Furthermore, the developed model serves as an accurate and reliable instrument for early diagnosis and personalized therapy. Large-scale clinical studies are warranted to further validate these findings and evaluate their clinical application.

Humans↗

PubMed2026

RECQL correlates with immune infiltration and serves as a prognostic biomarker and therapeutic predictor in gastric cancer.

BACKGROUND: RecQ-like helicase (RECQL), a member of the RecQ-like DNA helicase family, plays a crucial role in maintaining genomic stability. However, its relevance in gastric cancer (GC) has not been fully investigated. This study aimed to explore the clinical significance, biological functions, and potential role of RECQL in the tumor immune microenvironment of GC through comprehensive bioinformatics analyses and in vitro experiments. METHODS: Weighted gene co-expression network analysis (WGCNA), differential expression analysis, and least absolute shrinkage and selection operator (LASSO) regression were performed using public datasets [The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD), GSE150290] to identify key genes associated with GC progression. Subsequently, key pathways were identified through functional enrichment analysis, while immune infiltration and spatial transcriptomic analyses were conducted to characterize RECQL expression and its association with the tumor immune microenvironment. Finally, the effects of RECQL knockdown on the biological function of GC cells were assessed through Cell Counting Kit-8 (CCK-8), colony formation, scratch, and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assays. RESULTS: RECQL was significantly upregulated in GC tissues and correlated with advanced clinical stage and poor prognosis. Gene set enrichment analysis (GSEA) revealed a strong association between high RECQL expression and DNA repair pathway. Immune infiltration analysis indicated significant enrichment of M2 macrophages in the high-RECQL group, along with upregulation of immune checkpoint molecules including PDCD1, CTLA4, and CD274. Spatial transcriptomics further demonstrated co-localization of RECQL with myeloid cell-enriched regions in tumor parenchymal areas. Furthermore, in vitro experimental results indicated that RECQL was highly expressed in GC cell lines, and its knockdown effectively inhibited the viability, proliferation, and migration capabilities of HGC-27 cells, while enhancing their apoptosis. CONCLUSIONS: RECQL serves as a promising biomarker and potential therapeutic target in GC.

DNA repair↗

PubMed2026

Pan-cancer Bioinformatics Analysis Combined with Colon Cancer Experimental Validation: A Study on TMED3 as a Diagnostic and Prognostic Biomarker.

Transmembrane Emp24 Protein Transport Domain 3 (TMED3), a member of the p24 protein family, has been implicated in tumor proliferation, invasion, and migration. This study aimed to evaluate the expression patterns, prognostic significance, immune associations, and potential biological functions of TMED3 across multiple cancer types using pan-cancer bioinformatics analysis combined with immunohistochemical (IHC) validation in colon cancer. Multiomics datasets from The Cancer Genome Atlas, Genotype-Tissue Expression, UALCAN, Human Protein Atlas, and cBioPortal databases were analyzed to investigate TMED3 expression and genetic alterations in pan-cancer. Immunohistochemistry was performed to evaluate TMED3 protein expression in colon cancer tissues. Kaplan-Meier survival analysis and Cox regression analysis were used to assess the prognostic value of TMED3. Spearman correlation analysis was conducted to evaluate the associations of TMED3 with tumor mutational burden, microsatellite instability (MSI), immune cell infiltration, and immune checkpoints. Gene Set Enrichment Analysis was performed to investigate potential biological pathways associated with TMED3 in colon cancer. TMED3 expression was elevated in most tumor types and was associated with unfavorable overall survival and disease-specific survival in adrenocortical carcinoma, colon adenocarcinoma, and uveal melanoma. The greatest frequency of TMED3 genetic alterations was identified in mesothelioma, with amplification representing the predominant alteration type. In addition, TMED3 expression showed significant correlations with tumor mutational burden and microsatellite instability in kidney renal clear cell carcinoma, stomach adenocarcinoma, and uterine corpus endometrial carcinoma. TMED3 expression was also associated with immune infiltration and immune checkpoint expression in several tumors. IHC analysis demonstrated increased TMED3 expression in colon cancer tissues compared with normal colon tissues and showed an association with T stage. Functional enrichment analysis identified pathways related to ribosome, antigen processing and presentation, oxidative phosphorylation, and pentose phosphate. These findings indicate that TMED3 may represent a promising biomarker for the diagnosis and prognostic evaluation of colon cancer as well as other tumor types.

Humans↗

PubMed2026

ORBIT: Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space for cancer driver gene identification.

Accurate identification of cancer driver genes is crucial for precision oncology but remains challenging due to the complexity of integrating heterogeneous data and modeling dynamic biological systems. To address these limitations, we propose ORBIT (Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space). Our framework synergistically fuses multi-omics profiles with functional network data using a context-adaptive graph reweighting mechanism to capture cancer-specific dynamics. The model employs a bi-prototype contrastive learning strategy within hyperbolic space, which aligns gene representations around distinct driver and non-driver semantic anchors while preserving the intrinsic hierarchy of biological networks. Comprehensive evaluations demonstrate that ORBIT achieves highly competitive stability in pan-cancer analysis while consistently outperforming state-of-the-art methods in cancer-specific predictions. Furthermore, functional enrichment analysis confirms that the model effectively segregates core cancer pathways, and drug sensitivity profiling validates the clinical relevance of the identified drivers. By integrating hyperbolic geometry with context-adaptive learning, ORBIT offers a robust and interpretable paradigm for precision medicine. The source codes and datasets are publicly accessible at https://github.com/spcho-dev/ORBIT.

Humans↗

PubMed2025

An anti-androgen resistance-related gene signature acts as a prognostic marker and increases enzalutamide efficacy via PLK1 inhibition in prostate cancer.

BACKGROUND: Anti-androgen resistance remains a major clinical challenge in the treatment of prostate cancer (PCa), leading to disease progression and treatment failure. Despite extensive research on resistance mechanisms, a reliable prognostic model for predicting patient outcomes and guiding therapeutic strategies is still lacking. This study aimed to develop a novel gene signature related to anti-androgen resistance and evaluate its prognostic and therapeutic implications. METHODS: Anti-androgen resistance-related differentially expressed genes (ARRDEGs) were identified through transcriptomic analysis of enzalutamide- and dual enzalutamide abiraterone-resistant PCa cell lines from the GEO database. Functional enrichment analysis was performed to determine the biological roles of these genes. A prognostic gene signature was developed using univariate Cox regression, LASSO, and multivariate Cox regression models. The model was validated in independent PCa cohorts from The Cancer Genome Atlas (TCGA). Additionally, we assessed the correlation between the signature, immune infiltration, immune checkpoint expression, and drug sensitivity. The efficacy of PLK1 inhibition combined with enzalutamide was further explored using in vitro and in vivo experiments. RESULTS: We identified 304 ARRDEGs, from which three key genes (LMNB1, SSPO, and PLK1) were selected to construct a prognostic signature. This gene signature effectively stratified PCa patients into high- and low-risk groups, with the high-risk group exhibiting shorter recurrence-free survival and distinct immune characteristics. High-risk patients demonstrated elevated immune checkpoint expression (B7H3, CTLA-4, B7-1, and TIGIT), increased M2 macrophage infiltration, and enhanced sensitivity to chemotherapy and targeted therapy. Mechanistically, PLK1 inhibition potentiated the antitumor effect of enzalutamide by downregulating SLC7A11 and inducing ferroptosis, providing a potential therapeutic strategy to overcome anti-androgen resistance. CONCLUSION: We established a novel ARRDEGs-based prognostic signature that predicts PCa progression and response to chemotherapy and targeted therapy. The integration of this signature with immune profiling and drug sensitivity analysis provides a valuable tool for precision oncology in PCa. Our findings highlight the potential of PLK1 inhibition as a therapeutic strategy to enhance enzalutamide efficacy and overcome resistance.

Humans↗

PubMed2026

PLK1/FOXM1-associated tumor-cell state and macrophage-related immune features in endometrial cancer.

BACKGROUND: Polo-like kinase 1 (PLK1) and forkhead box M1 (FOXM1) have been widely studied in various cancers; however, their expression characteristics in endometrial cancer (EC) and their potential association with tumor microenvironment remodeling remain insufficiently characterized. METHODS: This study integrated The Cancer Genome Atlas uterine corpus endometrial carcinoma cohort, Gene Expression Omnibus, pan-cancer transcriptomic data, Human Protein Atlas/Clinical Proteomic Tumor Analysis Consortium, and local immunohistochemistry data to evaluate PLK1 expression and clinicopathological relevance across transcriptomic, proteomic, and histopathological data. Differential expression, survival, gene-set enrichment, transcription-factor enrichment, and immune-infiltration analyses characterized PLK1-associated features. In vitro experiments combined EC cell lines AN3CA and HEC-1A with co-immunoprecipitation, Western blotting, Transwell assays, and a THP-1 conditioned-medium model. Drug-response prediction and structure-based analysis prioritized candidate therapeutic hypotheses. RESULTS: PLK1 was consistently upregulated at both mRNA and protein levels in EC and was associated with higher tumor grade and International Federation of Gynecology and Obstetrics (FIGO) stage. In survival analysis, higher PLK1 expression was associated with poorer overall survival in univariable models but not after adjustment for age, tumor grade, and FIGO stage. Functional enrichment analysis showed that PLK1-associated genes were mainly involved in cell-cycle and mitotic processes. FOXM1 was identified as a potential candidate component of the PLK1-associated transcriptional program and was positively correlated with PLK1 expression and cell-cycle-related features. In vitro experiments supported an interaction between PLK1 and FOXM1 and suggested that FOXM1 Thr600 phosphorylation-related alterations were associated with migration and invasion phenotypes. Furthermore, the PLK1/FOXM1-associated tumor-cell state was linked to macrophage-related immune features and changes in the M2-like marker profile of THP-1-derived macrophage-like cells. Drug response analyses suggested differential predicted sensitivity patterns in PLK1-high tumors, providing candidate therapeutic hypotheses for further validation. CONCLUSION: The PLK1/FOXM1-associated tumor-cell state may represent a distinct molecular feature associated with proliferative activity, invasive phenotypes, and macrophage-related immune features in EC. This study provides preliminary evidence supporting the biological relevance of this molecular feature and highlights potential therapeutic directions for future investigation.

FoxM1↗

PubMed2025

Beyond parental lines: multi-omics analyses reveal epigenetic and transcriptional mechanisms underlying heterosis in Oryza sativa × Oryza rufipogon hybrids.

Heterosis, or hybrid vigor, refers to the superior phenotypes of a hybrid compared with their parents and is widely exploited in agriculture. Interspecific hybrids within the Oryza genus demonstrate significant potential for the systematic improvement of rice varieties. Nevertheless, the mechanistic basis underlying heterosis in interspecific Oryza hybrids remains poorly understood. Here, we systematically performed phenotypic characterization, whole-genome bisulfite sequencing, RNA sequencing, and small RNA profiling using Oryza sativa L. ssp. japonica cv. Nipponbare (NIP), Oryza rufipogon Griff. acc. CWR, and their resulting F1 hybrid (named as NC). NIP and CWR showed distinct phenotypic and molecular differences. The interspecific hybrid, NC, exhibited significant yield heterosis. In the hybrid, most epigenetic and transcriptional features displayed additive inheritance patterns relative to parental lines. Analysis revealed that domestication-selected genes maintained relatively low DNA methylation coupled with high expression levels in both hybrid and parental lines. Additionally, we identified that non-additive miRNAs were potentially involved in regulating fertility, cell growth, and cell division processes in the hybrid. A significant negative correlation was observed between DNA methylation level and gene expression. Functional enrichment analysis revealed that hybrid-MPV DEGs were significantly associated with flowering time regulation, carbohydrate metabolism, photosynthesis, protein phosphorylation, seed development, and defense responses. Through weighted gene co-expression network analysis, we identified 102 functional gene modules, six of which were significantly associated with yield-related heterosis. Collectively, our results provide a multi-omics framework for understanding interspecific hybridization between elite cultivars and wild rice relatives, highlighting CWR as an untapped genetic reservoir for rice improvement.

Oryza↗

PubMed2026

From immature to mature epithelium: unveiling structural dynamics and transcriptional programs in rainbow trout intestinal barrier.

The intestinal epithelium is crucial for nutrient absorption, immune defense, and barrier function in farmed fish. However, the molecular mechanisms underlying its development and maturation in salmonids remain poorly characterized, hindering our ability to address pervasive gut health challenges in aquaculture. In this study, we use the RTgutGC cell line to implement an epithelial maturation model with the aim of characterizing the global transcriptional program in rainbow trout (Oncorhynchus mykiss). We evaluated in vitro culture conditions to generate a polarized epithelial barrier with high transepithelial electrical resistance (TEER = 75.8 Ω × cm2), low permeability (6.2 × 10-6 cm/s), and well-defined apical specializations, including microvilli-like structures and clusters of these structures (brush border). Comparative transcriptomic profiling between immature (7 days post-seeding, dps) and mature (28 dps) epithelia revealed 3,817 differentially expressed genes (DEGs). Functional enrichment analysis showed that maturation was characterized by the downregulation of proliferative and ribosomal pathways and the concerted upregulation of processes critical for barrier function, including transmembrane transport, proteolysis, cell adhesion, extracellular matrix organization, and tight junction assembly. We identified a core set of 60 genes indicators of epithelial maturation, encompassing solute transporters (slc26a6, slc43a2), tight junction proteins (tjp1, cldn1, cldn3, cldn5, cldn18, among others), and structural components essential for microvilli formation and polarization (cdhr5b, pard6a). By integrating ultrastructural, functional, and transcriptomic data, this study established a framework for future mechanistic investigations into gut development and maturation in vitro. This set of mature epithelium indicators has diverse applications, such as the design of nutritional and pharmacological interventions to improve gut health and resilience in farmed fish.

Animals↗

PubMed2026

Genetically Predicted Gene Expression and Circulating Metabolites Associated with Cervical High-Grade Squamous Intraepithelial Lesion: A Mendelian Randomization Study.

BACKGROUND: High-grade squamous intraepithelial lesion (HSIL) is a precancerous condition of the cervix. Identifying risk factors associated with HSIL and understanding their potential mechanisms may inform prevention strategies. This study aimed to investigate the associations of genetically predicted gene expression and circulating metabolites with HSIL risk using Mendelian randomization (MR). METHODS: We performed two-sample MR analysis to evaluate the associations of genetically predicted gene expression (eQTLGen consortium, N=31,684) and circulating metabolites (genome-wide association study [GWAS], N=8,299) with HSIL risk (FinnGen R12, N=293,218; 8,291 cases). Mediation analysis was conducted to explore whether metabolites might mediate the associations between genes and HSIL. Sensitivity analyses, including Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO), leave-one-out, and colocalization, were performed to assess the robustness of the findings. All GWAS data used in this study were derived from European-ancestry populations. RESULTS: Eleven genes showed significant associations with HSIL after false discovery rate (FDR) correction (q<0.05), including VWA7, PAX8, GUSBP1, IKZF3, PAX8-AS1, NFKBIL1 (interpret with caution due to an influential single nucleotide polymorphism [SNP]), ERBB2, COL11A2, SKIV2L, TCF19, and PGAP3. Eleven circulating metabolites were also significantly associated with HSIL. Mediation analysis suggested that two phospholipid metabolites (GCST90200685 and GCST90200692) might mediate a small proportion of the total protective association of COL11A2 with HSIL (1.46% and 1.45%, respectively), indicating that the protective association of COL11A2 is largely independent of these circulating metabolites. Colocalization analysis showed strong evidence of shared causal variants for eight genes (PP.H4>0.98), while COL11A2 showed weak evidence of colocalization (PP.H4=1.58×10-15). Functional enrichment analysis indicated that COL11A2-related genes were enriched in extracellular matrix (ECM)-receptor interaction and PI3K-Akt signaling pathways. CONCLUSION: This MR study identified 11 genes and 11 circulating metabolites associated with HSIL risk. Among these, COL11A2 showed a protective association that appeared to be largely independent of circulating phospholipid metabolites, suggesting potential local mechanisms. These findings provide genetic and metabolic clues for future studies on HSIL etiology.

COL11A2↗

PubMed2026

The role of KIAA1467 in breast cancer: insights from pan-cancer and single-cell sequencing analysis.

BACKGROUND: Improving the response rate of single-agent immune checkpoint blockade (ICB) urgently requires the discovery of new therapeutic targets for combinatorial regimens. Analyses of tumor microenvironment (TME)-associated biomarkers have verified that KIAA1467 drives the formation of an immune-excluded, non-inflamed TME in breast cancer (BRCA). This study systematically explores the expression pattern, prognostic value, immune regulatory function, biological effects, and drug resistance relevance of FAM234B (also known as KIAA1467) in BRCA. METHODS: We performed pan-cancer survival analysis using The Cancer Genome Atlas (TCGA) datasets. Multi-omics bioinformatics analyses were conducted to evaluate KIAA1467 expression across malignancies. Single-cell RNA sequencing (scRNA-seq) data from GSE176078 was utilized to localize KIAA1467 expression at the cellular level. Immunohistochemistry and western blot assays validated KIAA1467 expression in BRCA clinical specimens. Correlation analyses were implemented to assess relationships between KIAA1467 expression, clinicopathological features, immune modulators, tumor-infiltrating immune cells, and p53 mutation status. Functional enrichment analysis uncovered relevant signaling pathways. Bioinformatic half maximal inhibitory concentration (IC50) prediction and in vitro cellular experiments were applied to evaluate associations between KIAA1467 and chemotherapeutic drug sensitivity. RESULTS: TCGA pan-cancer survival analysis demonstrated that elevated KIAA1467 expression significantly predicted shortened overall survival in BRCA and multiple other tumor types. KIAA1467 displayed distinct expression patterns across cancers, with prominent upregulation in BRCA. scRNA-seq confirmed enriched KIAA1467 expression within BRCA cells, and its upregulation in BRCA tissues was further verified by immunohistochemistry and western blot. High KIAA1467 expression was positively correlated with advanced tumor grade and lymphatic metastasis. KIAA1467 showed negative correlations with most immune modulators and core immune checkpoint molecules, as well as tumor-infiltrating immune cells in the TME, implying its potential function in tumor immune evasion. Low KIAA1467 expression was tightly linked to p53 mutations. Enrichment analysis indicated participation of KIAA1467 in epithelial-mesenchymal transition, apoptosis and cell cycle arrest. Furthermore, high KIAA1467 expression corresponded to higher estimated IC50 values of cisplatin, gefitinib, paclitaxel and gemcitabine, consistent with reduced chemosensitivity observed in vitro. CONCLUSIONS: This study reveals the multifaceted oncogenic role of KIAA1467 in BRCA. KIAA1467 participates in remodeling an immunosuppressive TME, correlates with malignant progression and chemoresistance, and may serve as a promising candidate target to optimize ICB-based combination therapy for BRCA. These findings offer new perspectives for the clinical treatment and comprehensive management of BRCA.

KIAA1467↗

PubMed2026

Integrative analysis and experiment validation of SLC12A8 as a biomarker for the malignant transition from endometriosis to endometriosis associated ovarian cancer.

Endometriosis (EM) is a chronic inflammatory, estrogen‑dependent benign gynecological disorder. A subset of patients with EM may subsequently develop endometriosis‑associated ovarian cancer (EAOC), implying a biological continuum between these two conditions. Nevertheless, the molecular events underlying the progression from benign endometriotic lesions toward EAOC remain incompletely characterized. In this study, transcriptomic datasets retrieved from the GEO database were interrogated through differentially expressed gene screening, functional enrichment analysis, and weighted gene co‑expression network analysis (WGCNA) to identify key genes and pathways relevant to EM and EAOC. Candidate genes were further prioritized by integrating survival analysis via the Kaplan‑Meier Plotter, LASSO regression, random‑forest modeling, and CIBERSORT immune‑infiltration profiling. Loss and gain‑of‑function cellular models were established using siRNA and overexpression plasmids, and in‑vitro functional assays were performed to characterize the phenotypic effects of target genes.We identified several candidate genes associated with EM and EAOC and evaluated their discriminatory performance. Among them, SLC12A8 elevated expression across EM and EAOC tissues and exhibited moderate diagnostic capacity. Higher SLC12A8 expression was also associated with poorer prognosis in EAOC patients. In‑vitro experiments further demonstrated that SLC12A8 modulates proliferation, invasion, and migration in both EM and EAOC cell lines. Collectively, our exploratory research findings support SLC12A8 as a candidate functional mediator and potential biomarker linked to EM‑EAOC pathological progression, thereby extending the mechanistic understanding of these disorders.

Female↗

PubMed2026

Characterisation of whole-blood extrachromosomal circular DNAs in Kawasaki disease complicated by coronary artery aneurysm.

BACKGROUND: Extrachromosomal circular DNAs are critical regulators of stress responses, immunity, and inflammation pathways. However, their role and underlying mechanisms in Kawasaki disease complicated by coronary artery aneurysm remain poorly understood. METHODS: Whole blood samples from six children with Kawasaki disease, including three with coronary artery aneurysm group and three without coronary artery aneurysm (control group), were subjected to extrachromosomal circular DNA sequencing. Putative extrachromosomal circular DNAs were identified using Circle-Map. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on genes associated with upregulated extrachromosomal circular DNAs, and an exploratory immune-signature profiling was performed using the single-sample gene set enrichment analysis algorithm. RESULTS: We identified 4,790 differential extrachromosomal circular DNAs between the coronary artery aneurysm and control groups, of which 4,789 were upregulated in the CAA group. The extrachromosomal circular DNAs in the coronary artery aneurysm group were more concentrated and shorter in length than those in the control group. Upregulated extrachromosomal circular DNAs were mainly derived from autosomes, particularly chromosomes 3, 4, and 7. Functional enrichment analysis indicated that genes associated with upregulated extrachromosomal circular DNAs were mainly involved in response to stimulus-related terms and pathways, including chemokine signalling, cGMP-PKG signalling, and calcium signalling. Immune-signature analysis suggested that the coronary artery aneurysm group exhibited more specific immune responses, whereas the control group tended towards broader immune regulatory processes. CONCLUSIONS: Coronary artery aneurysm and control groups exhibited distinct extrachromosomal circular DNA profiles. These findings suggest that extrachromosomal circular DNA alterations are associated with coronary artery aneurysm in Kawasaki disease and may provide new insights into the molecular features underlying this condition.

Coronary artery aneurysm↗