BACKGROUND: The transcription factor POU2F1 regulates the expression levels of microRNAs in neoplasia. However, the miR-29b1/a cluster modulated by POU2F1 in gastric cancer (GC) remains unknown. METHODS: Gene expression in GC cells was evaluated using reverse-transcription polymerase chain reaction (PCR), western blotting, immunohistochemistry, and RNA in situ hybridization. Co-immunoprecipitation was performed to evaluate protein interactions. Transwell migration and invasion assays were performed to investigate the biological behavior of GC cells. MiR-29b1/a cluster promoter analysis and luciferase activity assay for the 3'-UTR study were performed in GC cells. In vivo tumor metastasis was evaluated in nude mice. RESULTS: POU2F1 is overexpressed in GC cell lines and binds to the miR-29b1/a cluster promoter. POU2F1 is upregulated, whereas mature miR-29b-3p and miR-29a-3p are downregulated in GC tissues. POU2F1 promotes GC metastasis by inhibiting miR-29b-3p or miR-29a-3p expression in vitro and in vivo . Furthermore, PIK3R1 and/or PIK3R3 are direct targets of miR-29b-3p and/or miR-29a-3p , and the ectopic expression of PIK3R1 or PIK3R3 reverses the suppressive effect of mature miR-29b-3p and/or miR-29a-3p on GC cell metastasis and invasion. Additionally, the interaction of PIK3R1 with PIK3R3 promotes migration and invasion, and miR-29b-3p , miR-29a-3p , PIK3R1 , and PIK3R3 regulate migration and invasion via the phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/Akt/mTOR) pathway in GC cells. In addition, POU2F1 , PIK3R1 , and PIK3R3 expression levels negatively correlated with miR-29b-3p and miR-29a-3p expression levels in GC tissue samples. CONCLUSIONS The POU2F1 - miR-29b-3p / miR-29a-3p-PIK3R1 / PIK3R1 signaling axis regulates tumor progression and may be a promising therapeutic target for GC.
MicroRNAs/metabolism* ; Humans ; Stomach Neoplasms/pathology* ; Cell Line, Tumor ; Cell Movement/physiology* ; Phosphatidylinositol 3-Kinases/metabolism* ; Animals ; Mice ; Octamer Transcription Factor-1/metabolism* ; Mice, Nude ; Class Ia Phosphatidylinositol 3-Kinase/metabolism* ; Neoplasm Invasiveness ; Gene Expression Regulation, Neoplastic/genetics* ; Male ; Immunohistochemistry ; Female

BACKGROUND: Growing evidence suggests that long non-coding RNAs (lncRNAs) exert pivotal roles in fostering chemoresistance across diverse tumors. Nevertheless, the precise involvement of lncRNAs in modulating chemoresistance within the context of gallbladder cancer (GBC) remains obscure. This study aimed to uncover how lncRNAs regulate chemoresistance in gallbladder cancer, offering potential targets to overcome drug resistance. METHODS: To elucidate the relationship between gemcitabine sensitivity and small nucleolar RNA host gene 1 ( SNHG1 ) expression, we utilized publicly available GBC databases, GBC tissues from Renji Hospital collected between January 2017 and December 2019, as well as GBC cell lines. The assessment of SNHG1, miR-23b-3p, and phosphatase and tensin homolog (PTEN) expression was performed using in situ  hybridization, quantitative real-time polymerase chain reaction, and western blotting. The cell counting kit-8 (CCK-8) assay was used to quantify the cell viability. Furthermore, a GBC xenograft model was employed to evaluate the impact of SNHG1 on the therapeutic efficacy of gemcitabine. Receiver operating characteristic (ROC) curve analyses were executed to assess the specificity and sensitivity of SNHG1. RESULTS: Our analyses revealed an inverse correlation between the lncRNA SNHG1 and gemcitabine resistance across genomics of drug sensitivity in cancer (GDSC) and Gene Expression Omnibus (GEO) datasets, GBC cell lines, and patients. Gain-of-function investigations underscored that SNHG1 heightened the gemcitabine sensitivity of GBC cells in both in vitro and in vivo  settings. Mechanistic explorations illuminated that SNHG1 could activate PTEN -a commonly suppressed tumor suppressor gene in cancers-thereby curbing the development of gemcitabine resistance in GBC cells. Notably, microRNA (miRNA) target prediction algorithms unveiled the presence of miR-23b-3p binding sites within SNHG1 and the 3'-untranslated region (UTR) of PTEN . Moreover, SNHG1 acted as a sponge for miR-23b-3p, competitively binding to the 3'-UTR of PTEN , thereby amplifying PTEN expression and heightening the susceptibility of GBC cells to gemcitabine. CONCLUSION The SNHG1/miR-23b-3p/PTEN axis emerges as a pivotal regulator of gemcitabine sensitivity in GBC cells, holding potential as a promising therapeutic target for managing GBC patients.
Humans ; Deoxycytidine/pharmacology* ; PTEN Phosphohydrolase/genetics* ; Gemcitabine ; RNA, Long Noncoding/metabolism* ; MicroRNAs/genetics* ; Gallbladder Neoplasms/genetics* ; Cell Line, Tumor ; Animals ; Mice ; Drug Resistance, Neoplasm/genetics* ; Mice, Nude ; Antimetabolites, Antineoplastic ; Gene Expression Regulation, Neoplastic

Noncoding RNAs (ncRNAs) are a class of RNA molecules with little or no protein-coding potential. Emerging evidence indicates that ncRNAs are frequently dysregulated and play pivotal roles in the pathogenesis of pancreatic cancer. Their aberrant expression can arise from chromosomal abnormalities, dysregulated transcriptional control, and epigenetic modifications. ncRNAs function as protein scaffolds or molecular decoys to modulate interactions between proteins and other biomolecules, thereby regulating gene expression and contributing to pancreatic cancer progression. In this review, we summarize the mechanisms underlying ncRNA dysregulation in pancreatic cancer, emphasize the biological significance of ncRNA-protein interactions, and highlight their clinical relevance. A deeper understanding of ncRNA-protein interactions is essential to elucidate molecular mechanisms and advance translational research in pancreatic cancer.
Humans ; Pancreatic Neoplasms/metabolism* ; RNA, Untranslated/metabolism* ; Gene Expression Regulation, Neoplastic/genetics*

BACKGROUND: Gluconeogenesis is a critical metabolic pathway for maintaining glucose homeostasis, and its dysregulation can lead to glycometabolic disorders. This study aimed to identify hub biomarkers of these disorders to provide a theoretical foundation for enhancing diagnosis and treatment. METHODS: Gene expression profiles from liver tissues of three well-characterized gluconeogenesis mouse models were analyzed to identify commonly differentially expressed genes (DEGs). Weighted gene co-expression network analysis (WGCNA), machine learning techniques, and diagnostic tests on transcriptome data from publicly available datasets of type 2 diabetes mellitus (T2DM) patients were employed to assess the clinical relevance of these DEGs. Subsequently, we identified hub biomarkers associated with gluconeogenesis-related glycometabolic disorders, investigated potential correlations with immune cell types, and validated expression using quantitative polymerase chain reaction in the mouse models. RESULTS: Only a few common DEGs were observed in gluconeogenesis-related glycometabolic disorders across different contributing factors. However, these DEGs were consistently associated with cytokine regulation and oxidative stress (OS). Enrichment analysis highlighted significant alterations in terms related to cytokines and OS. Importantly, osteomodulin ( OMD ), apolipoprotein A4 ( APOA4 ), and insulin like growth factor binding protein 6 ( IGFBP6 ) were identified with potential clinical significance in T2DM patients. These genes demonstrated robust diagnostic performance in T2DM cohorts and were positively correlated with resting dendritic cells. CONCLUSIONS Gluconeogenesis-related glycometabolic disorders exhibit considerable heterogeneity, yet changes in cytokine regulation and OS are universally present. OMD , APOA4 , and IGFBP6  may serve as hub biomarkers for gluconeogenesis-related glycometabolic disorders.
Machine Learning ; Humans ; Computational Biology/methods* ; Biomarkers/metabolism* ; Diabetes Mellitus, Type 2/genetics* ; Animals ; Mice ; Gluconeogenesis/physiology* ; Gene Expression Profiling ; Transcriptome/genetics* ; Gene Regulatory Networks/genetics* ; Clinical Relevance

The transcriptome sequencing based on Illumina Novaseq 6000 Platform was performed with the untreated seed embryo(DS), stratified seed embryo(SS), and germinated seed embryo(GS) of Zanthoxylum nitidum, aiming to explore the molecular mechanism regulating the seed dormancy and germination of Z. nitidum and uncover key differentially expressed genes(DEGs). A total of 61.41 Gb clean data was obtained, and 86 386 unigenes with an average length of 773.49 bp were assembled. A total of 29 290 DEGs were screened from three comparison groups(SS vs DS, GS vs SS, and GS vs DS), and these genes were annotated on 134 Kyoto Encyclopedia of Genes and Genomes(KEGG) pathways. KEGG enrichment analysis revealed that the plant hormone signal transduction pathway is the richest pathway, containing 226 DEGs. Among all DEGs, 894 transcription factors were identified, which were distributed across 34 transcription factor families. These transcription factors were also mainly concentrated in plant hormone signal transduction and mitogen-activated protein kinase(MAPK) signaling pathways. Further real-time quantitative polymerase chain reaction(RT-qPCR) validation of 12 DEGs showed that the transcriptome data is reliable. During the process of seed dormancy release and germination, a large number of DEGs involved in polysaccharide degradation, protein synthesis, lipid metabolism, and hormone signal transduction were expressed. These genes were involved in multiple metabolic pathways, forming a complex regulatory network for dormancy and germination. This study lays a solid foundation for analyzing the molecular mechanisms of seed dormancy and germination of Z. nitidum.
Zanthoxylum/metabolism* ; Plant Dormancy/genetics* ; Seeds/metabolism* ; Gene Expression Regulation, Plant ; Plant Proteins/metabolism* ; Transcriptome ; Gene Expression Profiling ; Germination ; Transcription Factors/metabolism* ; Plant Growth Regulators/genetics* ; Signal Transduction

Ginkgo biloba, an ancient relict plant, holds a lengthy medicinal tradition in China. The leaves and seeds of this remarkable species contain flavonoids, a class of active compounds that offer a multitude of pharmacological advantages. The understanding of the synthesis process of these flavonoids can be deepened substantially by elucidating their biosynthetic pathway and metabolic regulation mechanisms. This can thereby provide a foundation for achieving precise regulation of flavonoid biosynthesis, which is of great significance for improving the production efficiency and quality of flavonoids in G. biloba. This review comprehensively summarizes research advancements in metabolomics, genomics, and transcriptomics of flavonoids in G. biloba, aiming to establish a thorough academic framework. It examines key enzymes in the biosynthetic pathway of flavonoids in G. biloba and their functions, highlighting their crucial roles in flavonoid production. Additionally, it outlines transcriptional regulation mechanisms associated with flavonoid in G. biloba biosynthesis, focusing on transcription factors responsive to environmental cues and their regulatory networks that modulate flavonoid gene expression. These insights offer a theoretical foundation for precise control of G. biloba flavonoid production. By amalgamating these diverse research findings, this review aims to establish a robust theoretical groundwork for future studies on biosynthesis and efficient utilization of flavonoids in G. biloba.
Ginkgo biloba/chemistry* ; Flavonoids/biosynthesis* ; Gene Expression Regulation, Plant ; Plant Proteins/genetics* ; Biosynthetic Pathways

The p60 subunit of the chromatin assembly factor-1 complex, that is, chromatin assembly factor-1 subunit B (CHAF1B), is a histone H3/H4 chaperone crucial for the transcriptional regulation of cell differentiation and self-renewal. CHAF1B is overexpressed in several cancers and may represent a potential target for cancer therapy. However, its expression and clinical significance in lung squamous-cell carcinoma (LUSC) remain unclear. In this study, we performed weighted gene correlation network analysis to analyze the Gene Expression Omnibus GSE68793 LUSC dataset and identified CHAF1B as one of the most important driver gene candidates. Immunohistochemical analysis of 126 LUSC tumor samples and 80 adjacent normal lung tissues showed the marked upregulation of CHAF1B in tumor tissues and the negative association of its expression level with patient survival outcomes. Silencing of CHAF1B suppressed LUSC proliferation in vitro and LUSC tumor growth in vivo. Furthermore, bulk RNA sequencing of CHAF1B knockdown cells indicated SET domain containing 7 (SETD7) as a significant CHAF1B target gene. In addition, CHAF1B competitively binds to the SETD7 promoter region and represses its transcription. Altogether, these results imply that CHAF1B plays a vital role in LUSC tumorigenesis and may represent a potential molecular target for this deadly disease.
Humans ; Lung Neoplasms/metabolism* ; Histone-Lysine N-Methyltransferase/metabolism* ; Carcinoma, Squamous Cell/metabolism* ; Gene Expression Regulation, Neoplastic ; Disease Progression ; Cell Proliferation/genetics* ; Cell Line, Tumor ; Chromatin Assembly Factor-1/metabolism* ; Animals ; Mice ; Male ; Female

The transcription factor HOXB13 plays crucial roles in cancer development. HOXB13 is abnormally expressed in most cancers, which makes it a valuable therapeutic target for cancer therapy. The level of HOXB13 differs significantly between healthy and cancer tissues, which indicates that the level of HOXB13 is closely related to carcinogenesis. The regulatory network mediated by HOXB13 in cancer proliferation, metastasis, and invasion has been systematically investigated. Moreover, HOXB13 variants play distinct roles in different cancers and populations. By understanding the molecular mechanisms and mutation features of HOXB13, we provide a comprehensive overview of carcinogenesis networks dependent on HOXB13. Finally, we discuss advancements in anticancer therapy targeting HOXB13 and the roles of HOXB13 in drug resistance to molecular-targeted therapies, which serves as a foundation for developing HOXB13-targeted drugs for clinical diagnosis and cancer therapies.
Humans ; Neoplasms/metabolism* ; Homeodomain Proteins/metabolism* ; Carcinogenesis/genetics* ; Mutation ; Gene Expression Regulation, Neoplastic ; Molecular Targeted Therapy ; Drug Resistance, Neoplasm/genetics*

Ankylosing spondylitis (AS) is linked to an increased prevalence of myocardial infarction (MI). However, research dedicated to elucidating the pathogenesis of AS-MI is lacking. In this study, we explored the biomarkers for enhancing the diagnostic and therapeutic efficiency of AS-MI. Datasets were obtained from the Gene Expression Omnibus database. We employed weighted gene co-expression network analysis and machine learning models to screen hub genes. A receiver operating characteristic curve and a nomogram were designed to assess diagnostic accuracy. Gene set enrichment analysis was conducted to reveal the potential function of hub genes. Immune infiltration analysis indicated the correlation between hub genes and the immune landscape. Subsequently, we performed single-cell analysis to identify the expression and subcellular localization of hub genes. We further constructed a transcription factor (TF)-microRNA (miRNA) regulatory network. Finally, drug prediction and molecular docking were performed. S100A12 and MCEMP1 were identified as hub genes, which were correlated with immune-related biological processes. They exhibited high diagnostic value and were predominantly expressed in myeloid cells. Furthermore, 24 TFs and 9 miRNA were associated with these hub genes. Enzastaurin, meglitinide, and nifedipine were predicted as potential therapeutic agents. Our study indicates that S100A12 and MCEMP1 exhibit significant potential as biomarkers and therapeutic targets for AS-MI, offering novel insights into the underlying etiology of this condition.
Humans ; Spondylitis, Ankylosing/complications* ; Systems Biology/methods* ; Myocardial Infarction/diagnosis* ; Biomarkers/metabolism* ; MicroRNAs/genetics* ; Gene Regulatory Networks ; Gene Expression Profiling ; Machine Learning

OBJECTIVE: To elucidate the molecular mechanisms underlying sepsis-induced injury in mouse intestinal organoids and investigate the possible mechanisms or potential drug targets of myeloid differentiation factor 88 inhibitor [TJ-M2010-5 (TJ5)] on this condition. METHODS: Small intestinal organoids from C57BL/6 mice aged 6-8 weeks were established and characterized using immunofluorescence for cell growth and proliferation marker nuclear antigen Ki-67, goblet cell marker mucin-2 (MUC-2), epithelial cell marker E-cadherin, and Paneth cell marker lysozyme (Lyz). Small intestinal organoids after 3 days of passaging were divided into different groups: a normal control group treated with culture medium containing 0.2% dimethyl sulfoxide (DMSO) for 10 hours, a lipopolysaccharide (LPS) group treated with culture medium containing 200 mg/L LPS and 0.2% DMSO for 10 hours, and a TJ5 group pre-treated with 10 mmol/L TJ5 for 2 hours followed by treatment with culture medium containing 200 mg/L LPS for 10 hours. Real-time fluorescence quantitative reverse transcription-polymerase chain reaction (RT-qPCR) was used to measure the expression levels of interleukin-6 (IL-6) and zonula occludens-1 (ZO-1) in the small intestinal organoids. RNA transcriptome sequencing was performed on the small intestinal organoids from each group to analyze differentially expressed genes between groups, and significant enrichment was analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). RESULTS: By the 7th day of primary culture, mature organoids had formed, and their growth rate increased after passaging. Immunofluorescence identification showed expressions of Ki-67, MUC-2, E-cadherin, and Lyz, indicating that the mouse small intestinal organoids maintained their cellular composition and functional characteristics under in vitro culture conditions. RT-qPCR results showed that compared with the normal control group, the mRNA expression of IL-6 in the small intestinal organoids of the LPS group was significantly increased (2^-ΔΔCT: 1.83±0.16 vs. 1.02±0.28, P < 0.05), while the mRNA expression of ZO-1 was significantly decreased (2^-ΔΔCT: 0.53±0.11 vs. 1.01±0.18, P < 0.05). In contrast, the mRNA expression trends of both IL-6 and ZO-1 were reversed in the TJ5 group, showing statistically significant differences as compared with the LPS group (2^-ΔΔCT: IL-6 mRNA was 1.24±0.01 vs. 1.83±0.16, ZO-1 mRNA was 1.97±0.29 vs. 0.53±0.11, both P < 0.05). RNA transcriptome sequencing showed 49 differentially expressed genes in the LPS group compared to the normal control group, with 42 upregulated and 7 downregulated. Compared to the LPS group, the TJ5 group showed 84 differentially expressed genes, with 47 upregulated and 37 downregulated. GO enrichment analysis of these differentially expressed genes showed that the significantly enriched biological processes of the differentially expressed genes between the normal control group and the LPS group included responses to LPS, responses to molecule of bacterial origin and responses to bacterium. The significantly enriched biological processes of the differentially expressed genes between the LPS group and the TJ5 group included glutathione metabolic processes, responses to stress cellular and responses to chemical stimulus. In molecular function groups, glutathione binding and oligopeptide binding were significantly enriched by the differentially expressed genes. In cellular component classifications, the enrichment of the differentially expressed genes was mainly observed in the cytoplasm, endoplasmic reticulum, and microsomes. KEGG pathway enrichment analysis indicated that the differentially expressed genes between the normal control group and LPS group were enriched in IL-17 signaling pathways, tumor necrosis factor (TNF) signaling pathways, viral protein interactions with cytokines and cytokine receptors signaling pathways, and cytokine-cytokine receptor interaction signaling pathways. In contrast, the differentially expressed genes between the LPS and TJ5 groups were mainly enriched in atherosclerosis signaling pathways, ferroptosis signaling pathways, glutathione metabolism signaling pathways, and cytochrome P450-mediated drug metabolism signaling pathways. CONCLUSIONS Mouse small intestinal organoids were successfully extracted and cultured. TJ5 may exert its protective effects by regulating gene expression and related signaling pathways (fluid shear stress and atherosclerosis, ferroptosis, glutathione metabolism, cytochrome P450 drug metabolism, etc.) in sepsis-injured mouse small intestinal organoids. These genes and signaling pathways may be key targets for treating sepsis-induced intestinal injury.
Animals ; Mice ; Sepsis/genetics* ; Organoids/drug effects* ; Mice, Inbred C57BL ; Intestine, Small/metabolism* ; Gene Expression Profiling ; Transcriptome ; Lipopolysaccharides