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Results for “Functional enrichment analysis”

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PubMed2026

Overexpression of TCF7L2 promotes the viability and migration of MHCC-97H human hepatocellular carcinoma cells by upregulating MT-ND4L.

BACKGROUND: Hepatocellular carcinoma (HCC) is a highly aggressive cancer with high metabolic adaptability. TCF7L2, a transcription factor implicated in type 2 diabetes and cancer, is overexpressed in HCC. However, its specific role in HCC metabolic reprogramming is not well defined. We aimed to elucidate the previously unrecognized molecular mechanisms through which TCF7L2 impacts HCC progression. METHODS: To investigate the function of TCF7L2, a stable MHCC-97H cell line with TCF7L2 overexpression was established via lentiviral transduction. Cell viability and migration were assessed by Cell Counting Kit-8 (CCK-8) and Transwell assays. Transcriptomic profiling [RNA sequencing (RNA-seq)] was performed to identify differentially expressed genes (DEGs). Functional enrichment analysis [Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA)] and bioinformatics promoter analysis (the JASPAR CORE database) were conducted. Clinical correlations, survival analysis, and tumor microenvironment (TME) interrogation were performed using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort and single-cell datasets [Human Protein Atlas (HPA), CellChat]. Drug sensitivity was predicted via the Genomics of Drug Sensitivity in Cancer (GDSC) database. RESULTS: TCF7L2 overexpression significantly promoted HCC cell proliferation and migration. Transcriptomic analysis revealed that TCF7L2 drives a profound metabolic shift, with key enrichments in lipid homeostasis, fatty acid β-oxidation, and the PI3K/Akt pathway. Mechanistically, TCF7L2 directly binds to the promoter of CPT1A, the rate-limiting enzyme of fatty acid oxidation, and indirectly upregulates the mitochondrial gene MT-ND4Lvia a strong positive correlation with the mitochondrial transcription factor TFAM. In clinical cohorts, TCF7L2 was overexpressed in HCC and its expression correlated positively with MT-ND4L, MKI67, and SNAI1, and served as a predictor of poor overall survival (OS). Furthermore, TCF7L2-high tumors were enriched in hepatic progenitor cell (HPC)-like niches, mediated by enhanced ANGPTL4 signaling. High TCF7L2 expression predicted increased sensitivity to PI3K/mTOR pathway inhibitors. CONCLUSIONS: TCF7L2 acts as a master metabolic regulator in HCC, coordinating lipid catabolism and mitochondrial biogenesis to drive aggressive tumor behavior. It further remodels the TME towards an HPC-like state and predicts sensitivity to metabolic-targeted therapies. These findings identify TCF7L2 as a key prognostic biomarker and a promising therapeutic target.

MHCC-97H hepatocellular carcinoma cells (MHCC-97H ↗

PubMed2026

Epigallocatechin gallate is associated with PDGFRB downregulation and altered PI3K-AKT signaling in gastric cancer.

BACKGROUND: Gastric cancer (GC) remains a major cause of cancer-related mortality worldwide. Epigallocatechin gallate (EGCG), a natural polyphenol derived from green tea, exhibits anticancer properties; however, its molecular targets and regulatory mechanisms in GC are not fully elucidated. This study aimed to identify candidate EGCG-associated genes in GC and generate a hypothesis for future mechanistic investigation. METHODS: Differentially expressed genes (DEGs) in GC were identified and intersected with EGCG-associated targets retrieved from The Cancer Genome Atlas (TCGA) and GeneCards public databases. Least absolute shrinkage and selection operator (LASSO) regression and Cox proportional hazards analyses were performed to screen prognostically relevant genes. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curves. Functional enrichment analysis was conducted to explore biological significance. Public single-cell RNA sequencing datasets were analyzed to determine the cellular localization of platelet-derived growth factor receptor beta (PDGFRB), while DepMap transcriptomic data were used to assess its expression across GC cell lines. In vitro assays, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), Transwell migration, and Western blotting, were performed to evaluate the biological effects of EGCG on GC-associated signaling pathways. RESULTS: Thirty-eight EGCG-associated DEGs were identified. Enrichment analysis revealed these genes were involved in cancer-associated pathways. LASSO-Cox modelling identified four candidate genes. Among them, PDGFRB was selected for further investigation based on its prognostic relevance and favorable diagnostic performance. PDGFRB expression was significantly higher in the TCGA genomically stable (GS) subtype than in the other molecular subtypes and was predominantly localized to cancer-associated fibroblasts (CAFs) and pericytes in single-cell RNA sequencing analysis. DepMap data demonstrated heterogeneous PDGFRB expression across GC cell lines. In vitro experiments showed that EGCG inhibited proliferation, migration, and invasion, reduced PDGFRB protein expression, and was associated with apoptosis-related protein changes and altered PI3K-AKT signaling. CONCLUSIONS: Our findings suggest that EGCG treatment was associated with reduced PDGFRB expression and altered PI3K-AKT signaling in GC cells. These findings identify PDGFRB as a candidate EGCG-associated gene and provide a hypothesis for future mechanistic investigation.

Gastric cancer (GC)↗

PubMed2025

Interconnected study of molecular pathways: miR-137 as a central element at the intersection of lipid metabolism and prostate carcinogenesis.

OBJECTIVE: To evaluate the roles of miR-137 and its target genes in lipid metabolism and prostate tumorigenesis. METHODS: We used a series of bioinformatic approaches to establish the relationship between miR-137 and its target genes. We mapped the metabolic pathways of interest in the Reactome database and identified the central target genes of miR-137 in this pathway using four platforms: Reactome, miRDB, miRmap, and TargetScan. To assess the expression and association with clinical parameters, we obtained information from the UALCAN, OncoDB, and GEPIA2 databases using a dataset of patients with prostate cancer from The Cancer Genome Atlas. For functional enrichment analysis and construction of the protein-protein interaction network, we used the Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and STRING. RESULTS: Our in silico study of The Cancer Genome Atlas database revealed that miR-137 is underexpressed in tumor tissues, and its reduction is associated with poor prognosis. An intriguing set of eight genes within the PPARα pathway: PPARGC1A, PPARGC1B, NCOA1, NCOA2, NCOA3, MED1, MED27, and ESRRA displayed synergy, positive correlations, and synchronized expression patterns in adipose, hepatic, and prostatic tissues, all linked to the enigmatic processes of metabolic regulation. Among the highlighted genes, ESRRA was overexpressed in the malignant environment, whereas its counterparts remained underexpressed. The plot was thickened with associations between the expression of NCOA1, NCOA3, and MED27, lymph node involvement, and the overexpression of several genes linked to advanced prostate cancer stages. An intriguing pattern emerged, with patients exhibiting reduced disease-free survival overexpressing NCOA2, NCOA3, MED27, and ESRRA. CONCLUSION: This study elucidates the possibility that miR-137 subtly modulates metabolic genes in prostate cancer, suggesting its latent therapeutic potential as a biomarker for disease progression. BACKGROUND: ■ The reduction of miR-137 in tumor tissues is associated with a worse prognosis. BACKGROUND: ■ miR-137 has eight oncogenically relevant target genes acting in the PPARα lipid pathway. BACKGROUND: ■ NCOA1, NCOA3, MED27, and ESRRA are associated with advanced prostate cancer. BACKGROUND: ■ miR-137 exhibits significant clinical potential by repressing the activation of pathways that influence prostate tumorigenesis in hyperstimulated metabolic environments. BACKGROUND: Prostate cancer progression is sustained by the simultaneous activation of pathways involving lipid uptake and de novo synthesis. In this context, miR-137 inhibits adipogenic differentiation and may reduce lipid uptake by tumor cells by modulating the PPAR/ p160/ESRRA axis, considerably attenuating metabolic effects and suppressing prostate tumorigenesis.

Male↗

PubMed2026

Research on identification of key genes and immune-metabolic mechanisms in atrial fibrillation through integrated multi-cohort transcriptomic analysis and machine learning.

This study aimed to integrate multiple datasets for the identification of atrial fibrillation (AF)-related differentially expressed genes (DEGs), analyze their underlying mechanisms through functional enrichment and machine learning, construct diagnostic models, and explore immune-metabolic interactions to provide novel biomarkers and theoretical foundations. Gene expression datasets were integrated and normalized, with batch effects removed using principal component analysis. Differential expression analysis, functional enrichment analysis (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways), and machine learning-based feature gene selection and model construction were performed. Shapley additive explanations analysis was utilized to interpret the constructed models, while gene set enrichment analysis, gene set variation analysis, and immune cell infiltration analysis were conducted to investigate the associations between feature genes and immune infiltration. After integrating and normalizing gene expression data and eliminating batch effects via principal component analysis, 6 DEGs were identified, including 4 upregulated and 2 down-regulated ones. Functional enrichment analysis showed these DEGs were significantly enriched in neuro-related biological processes and pathways, indicating their key roles in AF pathogenesis. Five key feature genes were selected using LASSO, random forest, and support vector machine-recursive feature elimination algorithms. They had significant expression differences between the AF and control groups (P < .001) and were located on distinct chromosomes. The constructed random forest and support vector machine models performed excellently (area under the curve ≥ 0.85). Shapley additive explanations analysis revealed TNNI1 contributed most to model prediction, with its expression significantly positively correlated with immune cell infiltration. Gene set enrichment analysis and gene set variation analysis analyses further showed feature genes participated in AF pathogenesis by regulating immune modulation, metabolic pathways, and autophagy. Immune cell infiltration analysis found altered proportions of T-cell subsets and M0 macrophages in the AF group, along with complex links between feature gene expression and immune cell function. This study systematically elucidated the unique gene expression patterns and key regulatory pathways associated with AF, clarifying the crucial roles of feature genes in immune regulation, metabolic imbalance, and cellular dysfunction. These findings provide a theoretical basis and potential therapeutic targets for understanding AF pathogenesis and developing targeted treatment strategies.

Atrial Fibrillation↗

PubMed2005

Targeted disruption of glycerol kinase gene in mice: expression analysis in liver shows alterations in network partners related to glycerol kinase activity.

Glycerol kinase deficiency (GKD) is an X-linked inborn error of metabolism with metabolic and neurological crises. Liver shows the highest level of glycerol kinase (GK) activity in humans and mice. Absence of genotype-phenotype correlations in patients with GKD indicates the involvement of modifier genes, including other network partners. To understand the molecular pathogenesis of GKD, we performed microarray analysis on liver mRNA from neonatal glycerol kinase (Gyk) knockout (KO) and wild-type (WT) mice. Unsupervised learning revealed that the overall gene expression profile of the KO mice was different from that of WT. Real-time PCR confirmed the differences for selected genes. Functional gene enrichment analysis was used to find 56 increased and 37 decreased gene functional categories. PathwayAssist analysis identified changes in gene expression levels of genes involved in organic acid metabolism indicating that GK was part of the same metabolic network which correlates well with the patients with GKD having metabolic acidemia during their episodic crises. Network component analysis (NCA) showed that transcription factors sterol regulatory element-binding protein (SREBP)-1c, carbohydrate response element-binding protein (ChREBP), hepatocyte nuclear factor-4 alpha (HNF-4alpha) and peroxisome proliferative-activated receptor-alpha (PPARalpha) had increased activity in the Gyk KO mice compared with WT mice, whereas SREBP-2 was less active in the Gyk KO mice. These studies show that Gyk deletion causes alterations in expression of genes in several regulatory networks and is the first time NCA has been used to expand on microarray data from a mouse KO model of a human disease.

Animals↗

PubMed2025

Integrated proteomic network analysis reveals PTPRC as a central hub protein orchestrating co-expression modules and metabolic dysregulation in renal carcinoma: PTPRC protein molecular action.

The occurrence of renal carcinoma is closely related to a variety of molecular mechanisms and metabolic disorders. PTPRC (protein tyrosine phosphatase receptor C), as an important regulatory protein, was studied to reveal the role of PTPRC in renal carcinoma through comprehensive proteomic network analysis, especially its core position in the coordination of co-expression modules and metabolic disorders. This study was the first to download and process multiple publicly available renal cancer transcriptome data to conduct differential gene expression analysis across datasets. Functional enrichment and disease ontology analysis were performed on the transcriptome of renal cancer, and weighted gene co-expression network (WGCNA) was constructed. The results showed that comprehensive principal component analysis revealed significant differences in the transcriptome of renal cancer, and functional annotation revealed specific pathways associated with renal cancer. WGCNA analysis identified tumor-associated co-expression modules, while multi-omics analysis further identified core regulatory networks including PTPRC. As a central hub protein, PTPRC plays an important coordinating role in the co-expression module and metabolic dysregulation of renal carcinoma. This discovery provides a new perspective for understanding the molecular mechanism of kidney cancer.

Humans↗

PubMed2026

Integrated bioinformatics analysis reveals cross-talking hub genes and therapeutic agents between sepsis and acute myocardial infarction.

BACKGROUND: Sepsis and acute myocardial infarction (AMI) are two significant diseases that may share overlapping etiological mechanisms. This study aims to systematically identify core genes common to both conditions and to explore their potential as therapeutic targets and drug candidates through an integrative analysis of clinical data and bioinformatics. METHODS: The AMI dataset was obtained from the GEO database, and RNA sequencing data were collected from blood samples of patients with sepsis at our hospital. Common genes were identified using differential expression gene analysis (DEG) and weighted gene co-expression network analysis (WGCNA). Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were performed. A protein-protein interaction (PPI) network was constructed, and hub genes were identified using the MCC/Degree algorithm. Diagnostic value was assessed via receiver operating characteristic curve analysis. Immune infiltration patterns, single-cell sequencing data, and molecular docking simulations were employed to evaluate immune relevance and identify potential therapeutic compounds. RESULTS: A total of 417 genes were identified between sepsis and AMI, with enrichment analysis revealing significant involvement in inflammatory responses. Three hub genes-JAK2, MYD88, and TIMP1-were selected for further investigation. ROC curves confirmed their strong diagnostic performance for both diseases. Immune infiltration analysis showed that these core genes were significantly correlated with the infiltration levels of various immune cell types. Molecular docking indicated that quercetin exhibited stable binding affinity with the proteins encoded by these genes. qPCR validation further confirmed the upregulation of these three genes, supporting the anti-inflammatory effects of quercetin as a potential targeted therapy. CONCLUSION: JAK2, MYD88, and TIMP1 were identified as shared core genes in sepsis and AMI. These genes not only serve as potential diagnostic biomarkers but also offer novel targets for developing common therapeutic strategies for both conditions. Furthermore, quercetin emerges as a promising candidate for targeted treatment.

Humans↗

PubMed2026

Quantitative Proteomic Analysis of APP/PS1 Transgenic Mice.

BACKGROUND: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder affecting the central nervous system (CNS), with its etiology still shrouded in uncertainty. The interplay of extracellular amyloid-β (Aβ) deposition, intracellular neurofibrillary tangles (NFTs) composed of tau protein, cholinergic neuronal impairment, and other pathogenic factors is implicated in the progression of AD. OBJECTIVE: The current study endeavors to delineate the proteomic landscape alterations in the hippocampus of an AD murine model, utilizing proteomic analysis to identify key physiological and pathological shifts induced by the disease. This endeavor aims to shed light on the underlying pathogenic mechanisms, which could facilitate early diagnosis and pave the way for novel therapeutic interventions for AD. METHODS: To dissect the proteomic perturbations induced by Aβ and Presenilin-1 (PS1) in the AD pathogenesis, we undertook a label-free quantitative (LFQ) proteomic analysis focusing on the hippocampal proteome of the APP/PS1 transgenic mouse model. Employing a multi-faceted approach that included differential protein functional enrichment, cluster analysis, and protein-protein interaction (PPI) network analysis, we conducted a comprehensive comparative proteomic study between APP/PS1 transgenic mice and their wild-type C57BL/6 counterparts. RESULTS: Mass spectrometry identified a total of 4817 proteins in the samples, with 2762 proteins being quantifiable. Comparative analysis revealed 396 proteins with differential expression between the APP/PS1 and control groups. Notably, 35 proteins exhibited consistent temporal regulation trends in the hippocampus, with concomitant alterations in biological pathways and PPI networks. CONCLUSIONS: This study presents a comparative proteomic profile of transgenic (APP/PS1) and wild-type mice, highlighting the proteomic divergences. Furthermore, it charts the trajectory of proteomic changes in the AD mouse model across the developmental stages from 2 to 12 months, providing insights into the physiological and pathological implications of the disease-associated genetic mutations.

Animals↗

PubMed2026

Integrative analysis of single-cell sequencing identifies CD8+ TIM3+ CD101+ T cell-associated genes as prognostic biomarkers in breast cancer.

BACKGROUND: Breast cancer is a prevalent and deadly malignancy that significantly impacts women's quality of life and imposes financial burdens. Despite therapeutic advancements, tumour heterogeneity and frequent relapses remain major challenges. Accordingly, this study aimed to characterize immune features associated with CD8+ TIM3+ CD101+ T cells and develop a prognostic signature for breast cancer. METHODS: This study integrated single-cell and bulk transcriptomic datasets to characterize CD8+ TIM3+ CD101+ T cell (CCT)-related immune features and construct a prognostic signature in breast cancer. Single-cell RNA-seq data were sourced from the Gene Expression Omnibus (GEO) repository, and bulk transcriptomic data were from The Cancer Genome Atlas (TCGA) and GEO databases. Analytical methods included pseudo-time trajectory reconstruction (Monocle2), intercellular signalling analysis (CellChat), functional enrichment (ClusterProfiler), and immune profiling (ssGSEA). Prognostic modeling was conducted using least absolute shrinkage and selection operator (LASSO) Cox regression, with validation via Kaplan-Meier and time-dependent receiver operating characteristic (ROC) analyses. RESULTS: Single-cell analysis identified 17 clusters spanning seven cell types, including T cells, myeloid cells, and epithelial cells. T-cell sub-clustering revealed four subtypes. Pseudotime analysis suggested a potential state-transition relationship between CD8+ CD101- TIM3+ and CD8+ CD101+ TIM3+ T-cell states. A total of 121 differentially expressed genes were enriched in vital biological processes. An 11-gene prognostic model showed strong predictive power across cohorts. Single-cell T-cell reclustering identified a CD8+ CD101+ TIM3+ T-cell subpopulation, which was primarily characterized by the expression of markers such as CD101 and HAVCR2/TIM3. CONCLUSIONS: This study maps cellular heterogeneity and molecular networks in breast cancer, offering insights for targeted therapy and improved prognosis.

Breast invasive carcinoma↗

PubMed2026

Integrated Bioinformatics Analysis Revealing that the NSDHL Gene Might Be Associated with the Progression of Western HFD/SW-Induced Hepatocellular Carcinoma.

BACKGROUND AND OBJECTIVE: Hepatocellular carcinoma (HCC) remains a significant global health concern. However, the etiology and pathogenesis of HCC have yet to be fully elucidated. Previous studies have indicated a close association between obesity and the occurrence and progression of HCC. The objective of this study was to employ bioinformatics strategies in order to explore key genes associated with the clinical diagnosis and prognosis of HCC induced by a Western high-fat diet and sugar water (HFD/SW). MATERIALS AND METHODS: We obtained the expression profile chip data GSE197884 from the Gene Expression Omnibus (GEO) database. Subsequently, “DESeq” and “Limma” R packages were employed to identify differentially expressed genes (DEGs) while constructing a co-expressed gene network using weighted gene co-expression analysis (WGCNA). Functional enrichment analyses were then carried out, followed by the construction of a protein-protein interaction (PPI) network to uncover core genes. The core genes were confirmed through data retrieved from The Cancer Genome Atlas (TCGA) database in order to determine their status as hub genes. Finally, survival and tumor immune infiltration analyses were performed to unveil the prognostic significance of these hub genes. RESULTS: In total, 126 intersection targets were retrieved through the Venn diagram. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed that the DEGs were primarily related to the proliferation and apoptosis of HCC cells, the digestion and metabolism of liver cells, the HCC tumor microenvironment, and immune response. The PPI network analysis identified 11 core targets, among which seven hub genes, including NSDHL, MVK, SQLW, GCAT, ALAS2, GLDC, and AGXT, were obtained after TCGA database validation. Furthermore, it was found that NSDHL was closely associated with the clinical diagnosis and prognosis of HCC induced by HFD/SW and also affected the cellular immune infiltration in the HCC tumor microenvironment. CONCLUSION: The present study demonstrated a significantly elevated expression of NSDHL in HCC tissues, suggesting its potential as a specific biomarker for precise clinical diagnosis and prognosis assessment of HCC induced by HFD/SW.

Computational Biology↗

PubMed2026

Ossicle occurrence characteristics and related molecular mechanisms in the sea cucumber Apostichopus japonicus.

To investigate the morphogenetic pattern and molecular mechanism of ossicle formation in the sea cucumber Apostichopus japonicus, this study systematically examined the morphological development and temporal sequence of spicules using the NaClO maceration method, in-situ squash preparation and microscopic observation. Comparative transcriptome sequencing was performed between doliolaria and pentactula larvae to screen differentially expressed genes (DEGs) related to ossicles formation, followed by pathway enrichment analysis. The function of the candidate key gene papilin-like was verified using siRNA-mediated gene silencing. The results were as follows: 1) Ossicles of A. japonicus first appeared at the late auricularia stage, initiating as X-shaped ossicles at the base of the oral tentacles. The number of X-shaped ossicles increased dramatically during the doliolaria stage. X-shaped ossicles were gradually replaced by table-shaped and rosette-shaped ossicles at the pentactula stage, suggesting that X-shaped ossicles may differentiate into these two ossicle types. The morphology of table-shaped ossicles showed a "simple-complex-simple" pattern with development. 2) Key genes related to ossicles formation, including CA1, COL1A2, and papilin-like, were identified by transcriptome analysis. After papilin-like knockdown, abnormal morphologies were observed in table-shaped ossicles of 1-year-old A. japonicus, such as spine-like protrusions on the outer margin of the disc and loss of table legs, confirming its crucial roles in maintaining ossicle morphology. This study clarified the morphological development pattern of ossicles in A. japonicus and identified a key regulatory gene (papilin-like) involved in ossicle morphogenesis, providing preliminary insights into the underlying molecular regulatory mechanism. These findings enrich our understanding on ossicles formation in echinoderms, and provide important morphological and molecular biological information for further studies on the developmental mechanism of ossicles in A. japonicus.

Animals↗

PubMed1995

A CD3+CD8+ T cell population lacking CD5 antigen expression is expanded in peripheral blood of human immunodeficiency virus-infected patients.

In this study we analyzed the behavior of a CD3+ T cell subpopulation lacking CD5 antigen expression in PBMC from HIV-1-infected patients. CD3+CD5- lymphocytes were greatly increased in peripheral blood of HIV-1+ patients, accounting for 20.6 +/- 9.9% of the total CD3+ cells, compared to seronegative individuals (5.5 +/- 3.2%). In both seropositive patients and controls, CD3+CD5- cells belonged to the CD8+ compartment; they were nonactivated, TCR alpha/beta+, naive lymphocytes, and in seronegative individuals preferentially expressed NK cell-associated markers, such as CD11b, CD16, CD56, and CD57. The phenotypic profile of this subset was slightly different in seropositive patients; while TCR expression and CD45RA/RO profile were comparable, CD11b and CD16 expression was lower compared to control figures, while CD56 expression was not changed, and CD57 expression was enhanced. Functional analysis of enriched CD3+CD8+CD5- cells showed an impaired ability to proliferate in response to mitogenic and antigenic stimuli; despite their NK-like phenotype, CD3+CD8+CD5- cells did not exert any NK cytotoxic activity, and only a lectin-dependent cytotoxic potential could be evidenced in this population. These results describe a novel alteration in the lymphocytes phenotypic profile during HIV-1 infection, involving a "transitional" population, which shares some properties of the T and of the NK cell lineage.

Biomarkers↗

PubMed2025

Identification and external validation of a prognostic signature based on myeloid-derived suppressor cells-related LncRNAs to evaluate survival prognosis and treatment efficacy in invasive breast carcinoma.

BACKGROUND: Originating in the hematopoietic tissue, myeloid-derived suppressor cells (MDSCs) significantly contribute to tumor-related immunological processes. However, their relationship with long noncoding RNAs (lncRNAs) and breast cancer remains incompletely understood. In this study, we introduced MDSCs-associated lncRNAs as novel prognostic biomarkers to assess outcomes in patients with invasive breast carcinoma (BRCA). METHODS: Information regarding BRCA cases, including clinical and genomic details, was obtained from the TCGA repository. Predictive indicators were discovered, and their reliability underwent thorough verification. A clinically useful nomogram was developed following application-based validation. Additional investigations encompassed functional analysis, TMB assessment, TME profiling, immunotherapy efficacy forecasting, and drug sensitivity testing along with target identification. Long non-coding RNA expression was measured using reverse transcription quantitative PCR. RESULTS: A risk stratification model incorporating eight MDSCs-related lncRNAs effectively predicted patient outcomes. Kaplan-Meier (K-M) survival analysis clearly indicated a much worse prognosis among patients classified as high-risk (p < 0.001). The nomogram accurately forecasted overall survival (OS). Analysis of functional enrichment revealed that pathways associated with epithelial cells showed activity among patients at higher risk. Characterization of the tumor microenvironment showed increased immune cell presence in those classified as low-risk. Conversely, individuals with greater risk displayed higher tumor mutational burden. TIDE and IPS analyses indicated superior immunotherapy responsiveness in the low-risk BRCA subgroup. Among 47 drugs with notable IC50 variations, Ribociclib, PD173074, KU-55933, NU7441, and nutlin-3a exhibited lower IC50 values within the low-risk group, whereas Lapatinib demonstrated greater efficacy among the high-risk group. Moreover, 10 potential therapeutic agents and their targets were predicted for high-risk patients. RT-qPCR validation confirmed the robustness of the model. CONCLUSIONS: We successfully verified a new model of molecular markers of MDSCs-related lncRNAs, offering critical insights for predicting outcomes and guiding therapeutic decisions in BRCA cases.

Bioinformatics↗

PubMed2026

Exploring the therapeutic targets and signaling mechanisms of quercetin activity against radiation skin ulcer based on the observational research of network pharmacology.

Radiation skin ulcer is a common adverse complication after radiotherapy. Currently, there is no efficient therapy for this complication. In this study, we searched for the potential pathological targets of radiation skin ulcer and the potential pharmacological targets of quercetin, respectively, and obtained the potential therapeutic targets after intersection. Subsequently, an array of bioinformatics assessments on possible therapeutic targets was conducted, encompassing functional enrichment studies, analysis of protein interaction networks, identification of key targets, and validation through molecular docking. The enrichment analysis of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways shows that the therapeutic effect of quercetin on radiation skin ulcer may be through targeting aging cells. In addition, we identified 5 core targets, including AKT1, EGFR, MAPK3, SRC, and TP53. They are significantly enriched in EGFR tyrosine kinase inhibitors (SRC, AKT1, EGFR, and MAPK3) and epidermal growth factor receptor signaling pathways (SRC, EGFR, and AKT1), indicating the importance of EGFR signaling. Quercetin may have a therapeutic effect on radiation skin ulcer by targeting aging cells. Specifically, it may act through 4 core targets, including AKT1, EGFR, SRC, and TP53.

Quercetin↗

PubMed2002

Characterization and functional analysis of a heart-enriched DnaJ/ Hsp40 homolog dj4/DjA4.

DnaJ homologs are cochaperones of the heat shock protein 70 (hsp70) family. Homologs dj1 (hsp40/hdj-1/ DjB1), dj2 (HSDJ/hdj-2/rdj-1/DjA1), and dj3 (cpr3/DNAJ3/HIRIP4/rdj2/DjA2) have been identified in the mammalian cytosol and characterized. In this paper we characterized newly found dj4 (DjA4) and compared it with other chaperones. The dj4 messenger ribonucleic acid (mRNA) and protein were expressed strongly in heart and testis, moderately in brain and ovary, and weakly in other tissues in mice. Dj4 constituted about 1% of the total protein in heart. Testis gave extraspecies of dj4 mRNA and protein in addition to those seen in other tissues. On subcellular fractionation of the mouse heart, dj4 was recovered mostly in the cytosol fraction. In immunocytochemical analysis of the H9c2 heart muscle cells, dj4 and heat shock cognate 70 (hsc70) colocalized in the cytoplasm under normal conditions, whereas they colocalized in the nucleus after heat shock. When H9c2 cells were differentiated by culturing for up to 28 days with a lowered serum concentration, dj4 was increased markedly, dj3 was increased moderately, and dj1 and dj2 were little changed. The homolog dj4 as well as hsp70, dj1, and dj2 were induced in H9c2 cells by heat treatment at 43 degrees C for 30 minutes, whereas hsc70 and dj3 were not induced. Heat pretreatment promoted survival of cells after severe heat shock at 47 degrees C for 90 minutes or 120 minutes. H9c2 cells overexpressing hsp70 were more resistant to severe heat shock, and a better survival was obtained when dj4 or dj2 was co-overexpressed with hsp70. Taking a high concentration of dj4 in heart into consideration, these results suggest that the hsc70/hsp70-dj4 chaperone pair protects the heart muscle cells from various stresses.

Animals↗

PubMed2025

Gene behaviors-based network enrichment analysis and its application to reveal immune disease pathways enriched with COVID-19 severity-specific gene networks.

MOTIVATION: Gene network analysis is essential for understanding the complex mechanisms underlying diseases, which often involve disruptions in molecular networks rather than individual genes. Despite the availability of large-scale omics datasets and computational tools for gene network analysis, interpretation of the biological relevance of these extensive networks remains challenging. RESULTS: We propose a novel computational strategy, gene behaviors-based network enrichment analysis, which systematically identifies functional pathways enriched in phenotype-specific gene networks. Our novel method incorporates comprehensive network characteristics, i.e. gene expression levels, edge strengths, and structural patterns of edges, to rank genes based on activity and assess pathway enrichment, effectively identifying functional pathways enriched within these networks. Through simulation studies, our strategy demonstrated superior performance compared with that of existing methods in identifying enriched pathways. We applied this strategy to whole-blood RNA-seq data from 1102 COVID-19 samples provided by the Japan COVID-19 Task Force. The analysis revealed immune disease pathways enriched with COVID-19 severity-specific gene networks, including "Systemic lupus erythematosus" in asymptomatic and severe samples and "Inflammatory bowel disease," "Primary immunodeficiency," and "Rheumatoid arthritis" in mild samples. Key biomarkers of COVID-19, such as CXCL8, S100A9, and HLA class I genes, have been identified as critical hub genes and the main players within these networks. AVAILABILITY AND IMPLEMENTATION: Code is available in Figshare (https://doi.org/10.6084/m9.figshare.29093648.v3).

COVID-19↗

PubMed2026

Comparative transcriptome analysis provides insights into dorso-ventral color pattern formation of Holothuria edulis.

Animal body color patterns are highly diverse and play critical roles in camouflage, intraspecific communication, and environmental adaptation. Holothuria edulis, an important echinoderm inhabiting tropical waters, exhibits a typical dorsoventral dichromatism. This unique body color difference represents a key phenotypic trait for its habitat adaptation; however, the core differential genes regulating this trait remain to be elucidated. In this study, comparative transcriptome sequencing was performed on the dorsal and ventral body wall tissues of H. edulis, leading to the identification of a number of differentially expressed genes (DEGs), followed by GO functional annotation and KEGG pathway enrichment analysis. GO enrichment analysis indicated that the DEGs were significantly enriched in functional categories such as extracellular region, peptidase inhibitor activity, and tetrapyrrole binding. KEGG pathway analysis further revealed significant enrichment of protein digestion and absorption, the TNF signaling pathway, and cholesterol metabolism. Notably, the pigmentation-related gene FMO2 was highly expressed in the dorsal body wall tissue, whereas cyp1a1, ZIC1, Slc7a11, WNT-1, and ADAMTS20 were highly expressed in the ventral body wall tissue. This study identified DEGs and enriched pathways associated with dorsoventral body color differences in H. edulis, providing new insights into the molecular regulatory mechanisms underlying body color pattern formation. From the perspective of aquaculture applications, body color is one of the important traits affecting the quality and market value of sea cucumber products. Elucidating the molecular mechanisms of body color variation can provide a scientific basis for molecular marker-assisted breeding of superior sea cucumber variety.

Animals↗

PubMed2006

Development and characterization of a normalized canine retinal cDNA library for genomic and expression studies.

PURPOSE: Identification of causative mutations for retinal blinding disorders is often limited by restricted understanding of gene expression and underlying molecular mechanisms that trigger degenerative processes. This study was conducted to develop a catalog of canine retina-expressed genes that would provide a unique tool to investigate normal and altered function in the adult retina. Because of the conserved syntenies between the dog and human, this approach would identify new potential disease candidate genes for both species. METHODS: A canine normalized retinal cDNA library was produced and analyzed by using a modified PhredPhrap algorithm. Computerized annotation provided gene homology and chromosomal location for individual clones and contigs in a Web-accessible database. RESULTS: From 6316 cDNA clones, 3980 retinal expressed sequence tags (ESTs) were derived. Homology to the canine genome draft sequence was found for more than 99% of all ESTs, but only for 32% when compared with annotated canine cDNAs. Functional analysis suggests an enrichment of this library for genes involved with eye function and development, chaperone, or ribosomal functions when compared with mouse and human National Center for Biotechnology Information (NCBI) RefSeq entries. CONCLUSIONS: A combination of annotation approaches with ongoing mapping and expression studies provide functional data covering at least 27% to 30% of the currently proposed canine catalog of genes expressed in the retina. This is an essential first step toward establishing an integrated network for gene identification and expression patterns suitable for functional genetics, comparative genomics and evolutionary analysis of genes and gene families with respect to the developmental and degenerative processes of the retina.

Animals↗