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Yang J, Zhou Y, Zhang J, Zheng Y, He J. Identification of genes related to fatty acid metabolism in type 2 diabetes mellitus. Biochem Biophys Rep 2024; 40:101849. [PMID: 39498440 PMCID: PMC11532806 DOI: 10.1016/j.bbrep.2024.101849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2024] [Revised: 10/10/2024] [Accepted: 10/14/2024] [Indexed: 11/07/2024] Open
Abstract
Aim Fatty acid metabolism is pivotal for lipid synthesis, cellular signaling, and maintaining cell membrane integrity. However, its diagnostic significance in type 2 diabetes mellitus (T2DM) remains unclear. Materials and methods Three datasets and fatty acid metabolism-related genes were retrieved. Differential expression analysis, WGCNA, machine learning algorithms, diagnostic analysis, and validation were employed to identify key feature genes. Functional analysis, ceRNA network construction, immune microenvironment assessment, and drug prediction were conducted to explore the underlying molecular mechanisms. Results Six feature genes were identified with strong diagnostic performance and were involved in processes such as ribosome function and fatty acid metabolism. Immune cells, including dendritic cells, eosinophils, and neutrophils, may play a role in the progression of T2DM. ceRNA and drug-target network analysis revealed potential interactions, such as RP11-miR-29a-YTHDF3 and BPA-MSANTD1. The expression patterns of the feature genes, except for YTHDF3, were consistently upregulated in T2DM, aligning with trends observed in the training set. Conclusion This study investigated the potential molecular mechanisms of six fatty acid metabolism-related genes in T2DM, offering valuable insights that may guide future research and therapeutic development.
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Affiliation(s)
- Ji Yang
- Medical School, Kunming University of Science and Technology, Kunming, Yunnan, China
- Department of Endocrinology and Metabolism, The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Yikun Zhou
- Department of Endocrinology and Metabolism, The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Jiarui Zhang
- Medical School, Kunming University of Science and Technology, Kunming, Yunnan, China
- Department of Endocrinology and Metabolism, The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Yongqin Zheng
- Department of Endocrinology and Metabolism, The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Jundong He
- Medical School, Kunming University of Science and Technology, Kunming, Yunnan, China
- Department of Endocrinology and Metabolism, The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, Yunnan, China
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2
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Roy D, Ghosh R, Ghosh R, Khokhar M, Naing MYY, Benito-León J. Decoding visceral adipose tissue molecular signatures in obesity and insulin resistance: a multi-omics approach. Obesity (Silver Spring) 2024; 32:2149-2160. [PMID: 39400526 DOI: 10.1002/oby.24146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Revised: 07/23/2024] [Accepted: 08/04/2024] [Indexed: 10/15/2024]
Abstract
OBJECTIVE Obesity-associated insulin resistance (IR) is responsible for considerable morbidity and mortality globally. Despite vast genomic data, many areas, from pathogenesis to management, still have significant knowledge gaps. We aimed to characterize visceral adipose tissue (VAT) in obesity and IR through a multi-omics approach. METHODS We procured data on VAT samples from the Gene Expression Omnibus (GEO) for the following two groups: 1) populations with obesity (n = 34) versus those without (n = 26); and 2) populations with obesity and IR (n = 15) versus those with obesity but without IR (n = 15). Gene set enrichment, protein-protein interaction network construction, hub gene identification, and drug-gene interactions were performed, followed by regulatory network prediction involving transcription factors (TFs) and microRNAs (miRNAs). RESULTS Interleukin signaling pathways, cellular differentiation, and regulation of immune response revealed a significant cross talk between VAT and the immune system. Other findings include cancer pathways, neurotrophin signaling, and aging. A total of 10 hub genes, i.e., STAT1, KLF4, DUSP1, EGR1, FOS, JUN, IL2, IL6, MMP9, and FGF9, 24 TFs, and approved hub gene-targeting drugs were obtained. A total of 10 targeting miRNAs (e.g., hsa-miR-155-5p, hsa-miR-34a-5p) were associated with obesity and IR-related pathways. CONCLUSIONS Our multi-omics integration method revealed hub genes, TFs, and miRNAs that can be potential targets for investigation in VAT-related inflammatory processes and IR, therapeutic management, and risk stratifications.
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Affiliation(s)
- Dipayan Roy
- Department of Biochemistry, All India Institute of Medical Sciences (AIIMS), Patna, India
- Department of Biochemistry, All India Institute of Medical Sciences (AIIMS), Jodhpur, India
| | - Raghumoy Ghosh
- Department of Biochemistry, All India Institute of Medical Sciences (AIIMS), Jodhpur, India
- Lee Kong Chian School of Medicine, Nanyang Technological University (NTU), Singapore
| | - Ritwik Ghosh
- Department of General Medicine, Burdwan Medical College & Hospital, Burdwan, India
| | - Manoj Khokhar
- Department of Biochemistry, All India Institute of Medical Sciences (AIIMS), Jodhpur, India
| | - Ma Yin Yin Naing
- Lee Kong Chian School of Medicine, Nanyang Technological University (NTU), Singapore
| | - Julián Benito-León
- Department of Neurology, University Hospital "12 de Octubre", Madrid, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
- Department of Medicine, Faculty of Medicine, Complutense University, Madrid, Spain
- Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), Madrid, Spain
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Zhang Y, Liu G, Ding H, Fan B. High expression of CNOT6L contributes to the negative development of type 2 diabetes. Sci Rep 2024; 14:24723. [PMID: 39433858 PMCID: PMC11494123 DOI: 10.1038/s41598-024-76095-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Accepted: 10/10/2024] [Indexed: 10/23/2024] Open
Abstract
OBJECTIVE Type 2 diabetes (T2D) is a chronic metabolic disorder characterized by reduced responsiveness of body cells to insulin, leading to elevated blood sugar levels. CNOT6L is involved in glucose metabolism, insulin secretion regulation, pancreatic beta-cell proliferation, and apoptosis. These functions may be closely related to the pathogenesis of T2D. However, the exact molecular mechanisms linking CNOT6L to T2D remain unclear. Therefore, this study aims to elucidate the role of CNOT6L in T2D. METHODS The T2D datasets GSE163980 and GSE26168 profiles were downloaded from the Gene Expression Omnibusdatabase generated by GPL20115 and GPL6883.The R package limma was used to screen differentially expressed genes (DEGs). A weighted gene co-expression network analysis was performed. Construction and analysis of the protein-protein interaction (PPI) network, functional enrichment analysis, gene set enrichment analysis, and comparative toxicogenomics database (CTD) analysis were performed. Target Scan was used to screen miRNAs that regulate central DEGs. The results were verified by reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR), western blotting (WB), and blood glucose measurements in mice. RESULTS A total of 1951 DEGs were identified. GO and KEGG enrichment analysis revealed that differentially expressed genes were mainly enriched in the insulin signaling pathway, ECM-receptor interaction, and PPAR signaling pathway. Metascape analysis indicated enrichment primarily in the cAMP signaling pathway and enzyme-linked receptor protein signaling pathway. WGCNA analysis yielded 50 intersecting genes. PPI network construction and algorithm identification identified two core genes (CNOT6L and GRIN2B), among which CNOT6L gene was associated with multiple miRNAs. CTD analysis revealed associations of core genes with type 2 diabetes, diabetic complications, dyslipidemia, hyperglycemia, and inflammation. WB and RT-qPCR results showed that in different pathways, CNOT6L protein and mRNA levels were upregulated in type 2 diabetes. CONCLUSION CNOT6L is highly expressed in type 2 diabetes mellitus, and can cause diabetes complications, inflammation and other physiological processes by regulating miRNA, PPAR and other related signaling pathways, with poor prognosis. CNOT6L can be used as a potential therapeutic target for type 2 diabetes.
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Affiliation(s)
- Yuna Zhang
- Department of Endocrinology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China
| | - Guihong Liu
- Department of Endocrinology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China
| | - Haiyan Ding
- Department of Endocrinology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China
| | - Bingge Fan
- Department of Endocrinology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, China.
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Pelissier A, Laragione T, Gulko PS, Rodríguez Martínez M. Cell-specific gene networks and drivers in rheumatoid arthritis synovial tissues. Front Immunol 2024; 15:1428773. [PMID: 39161769 PMCID: PMC11330812 DOI: 10.3389/fimmu.2024.1428773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Accepted: 06/24/2024] [Indexed: 08/21/2024] Open
Abstract
Rheumatoid arthritis (RA) is a common autoimmune and inflammatory disease characterized by inflammation and hyperplasia of the synovial tissues. RA pathogenesis involves multiple cell types, genes, transcription factors (TFs) and networks. Yet, little is known about the TFs, and key drivers and networks regulating cell function and disease at the synovial tissue level, which is the site of disease. In the present study, we used available RNA-seq databases generated from synovial tissues and developed a novel approach to elucidate cell type-specific regulatory networks on synovial tissue genes in RA. We leverage established computational methodologies to infer sample-specific gene regulatory networks and applied statistical methods to compare network properties across phenotypic groups (RA versus osteoarthritis). We developed computational approaches to rank TFs based on their contribution to the observed phenotypic differences between RA and controls across different cell types. We identified 18 (fibroblast-like synoviocyte), 16 (T cells), 19 (B cells) and 11 (monocyte) key regulators in RA synovial tissues. Interestingly, fibroblast-like synoviocyte (FLS) and B cells were driven by multiple independent co-regulatory TF clusters that included MITF, HLX, BACH1 (FLS) and KLF13, FOSB, FOSL1 (B cells). However, monocytes were collectively governed by a single cluster of TF drivers, responsible for the main phenotypic differences between RA and controls, which included RFX5, IRF9, CREB5. Among several cell subset and pathway changes, we also detected reduced presence of Natural killer T (NKT) cells and eosinophils in RA synovial tissues. Overall, our novel approach identified new and previously unsuspected Key driver genes (KDG), TF and networks and should help better understanding individual cell regulation and co-regulatory networks in RA pathogenesis, as well as potentially generate new targets for treatment.
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Affiliation(s)
- Aurelien Pelissier
- Institute of Computational Life Sciences, Zürich University of Applied Sciences (ZHAW), Wädenswil, Switzerland
- AI for Scientific Discovery, IBM Research Europe, Rüschlikon, Switzerland
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Teresina Laragione
- Division of Rheumatology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Percio S. Gulko
- Division of Rheumatology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - María Rodríguez Martínez
- AI for Scientific Discovery, IBM Research Europe, Rüschlikon, Switzerland
- Department of Biomedical Informatics & Data Science, Yale School of Medicine, New Haven, CT, United States
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5
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Čugalj Kern B, Kovač J, Šket R, Tesovnik T, Jenko Bizjan B, Galhardo J, Battelino T, Bratina N, Dovč K. Exploring early DNA methylation alterations in type 1 diabetes: implications of glycemic control. Front Endocrinol (Lausanne) 2024; 15:1416433. [PMID: 38904047 PMCID: PMC11188314 DOI: 10.3389/fendo.2024.1416433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Accepted: 05/16/2024] [Indexed: 06/22/2024] Open
Abstract
Background Prolonged hyperglycemia causes diabetes-related micro- and macrovascular complications, which combined represent a significant burden for individuals living with diabetes. The growing scope of evidence indicates that hyperglycemia affects the development of vascular complications through DNA methylation. Methods A genome-wide differential DNA methylation analysis was performed on pooled peripheral blood DNA samples from individuals with type 1 diabetes (T1D) with direct DNA sequencing. Strict selection criteria were used to ensure two age- and sex-matched groups with no clinical signs of chronic complications according to persistent mean glycated hemoglobin (HbA1c) values over 5 years: HbA1c<7% (N=10) and HbA1c>8% (N=10). Results Between the two groups, 8385 differentially methylated CpG sites, annotated to 1802 genes, were identified. Genes annotated to hypomethylated CpG sites were enriched in 48 signaling pathways. Further analysis of key CpG sites revealed four specific regions, two of which were hypermethylated and two hypomethylated, associated with long non-coding RNA and processed pseudogenes. Conclusions Prolonged hyperglycemia in individuals with T1D, who have no clinical manifestation of diabetes-related complications, is associated with multiple differentially methylated CpG sites in crucial genes and pathways known to be linked to chronic complications in T1D.
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Affiliation(s)
- Barbara Čugalj Kern
- University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Jernej Kovač
- University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Robert Šket
- University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Tine Tesovnik
- University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Barbara Jenko Bizjan
- University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Julia Galhardo
- Paediatric Endocrinology and Diabetes Unit, Hospital de Dona Estefânia - Central Lisbon University Hospital Center, Lisbon, Portugal
- Lisbon Academic and Clinical Center, NOVA Medical School, Lisbon, Portugal
| | - Tadej Battelino
- University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Nataša Bratina
- University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Klemen Dovč
- University Children’s Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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Pelissier A, Laragione T, Gulko PS, Rodríguez Martínez M. Cell-Specific Gene Networks and Drivers in Rheumatoid Arthritis Synovial Tissues. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.28.573505. [PMID: 38234732 PMCID: PMC10793435 DOI: 10.1101/2023.12.28.573505] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Rheumatoid arthritis (RA) is a common autoimmune and inflammatory disease characterized by inflammation and hyperplasia of the synovial tissues. RA pathogenesis involves multiple cell types, genes, transcription factors (TFs) and networks. Yet, little is known about the TFs, and key drivers and networks regulating cell function and disease at the synovial tissue level, which is the site of disease. In the present study, we used available RNA-seq databases generated from synovial tissues and developed a novel approach to elucidate cell type-specific regulatory networks on synovial tissue genes in RA. We leverage established computational methodologies to infer sample-specific gene regulatory networks and applied statistical methods to compare network properties across phenotypic groups (RA versus osteoarthritis). We developed computational approaches to rank TFs based on their contribution to the observed phenotypic differences between RA and controls across different cell types. We identified 18,16,19,11 key regulators of fibroblast-like synoviocyte (FLS), T cells, B cells, and monocyte signatures and networks, respectively, in RA synovial tissues. Interestingly, FLS and B cells were driven by multiple independent co-regulatory TF clusters that included MITF, HLX, BACH1 (FLS) and KLF13, FOSB, FOSL1 (synovial B cells). However, monocytes were collectively governed by a single cluster of TF drivers, responsible for the main phenotypic differences between RA and controls, which included RFX5, IRF9, CREB5. Among several cell subset and pathway changes, we also detected reduced presence of NKT cell and eosinophils in RA synovial tissues. Overall, our novel approach identified new and previously unsuspected KDG, TF and networks and should help better understanding individual cell regulation and co-regulatory networks in RA pathogenesis, as well as potentially generate new targets for treatment.
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Affiliation(s)
- Aurelien Pelissier
- IBM Research Europe, 8803 Rüschlikon, Switzerland
- Department of Biosystems Science and Engineering, ETH Zurich, 4058 Basel, Switzerland
- Currently at Institute of Computational Life Sciences, ZHAW, 8400 Winterthur, Switzerland
| | - Teresina Laragione
- Division of Rheumatology, Icahn School of Medicine at Mount Sinai, 10029 New York, United States
| | - Percio S. Gulko
- Division of Rheumatology, Icahn School of Medicine at Mount Sinai, 10029 New York, United States
| | - María Rodríguez Martínez
- IBM Research Europe, 8803 Rüschlikon, Switzerland
- Currently at Yale School of Medicine, 06510 New Haven, United States
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7
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Rabby MG, Rahman MH, Islam MN, Kamal MM, Biswas M, Bonny M, Hasan MM. In silico identification and functional prediction of differentially expressed genes in South Asian populations associated with type 2 diabetes. PLoS One 2023; 18:e0294399. [PMID: 38096208 PMCID: PMC10721103 DOI: 10.1371/journal.pone.0294399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Accepted: 11/01/2023] [Indexed: 12/17/2023] Open
Abstract
Type 2 diabetes (T2D) is one of the major metabolic disorders in humans caused by hyperglycemia and insulin resistance syndrome. Although significant genetic effects on T2D pathogenesis are experimentally proved, the molecular mechanism of T2D in South Asian Populations (SAPs) is still limited. Hence, the current research analyzed two Gene Expression Omnibus (GEO) and 17 Genome-Wide Association Studies (GWAS) datasets associated with T2D in SAP to identify DEGs (differentially expressed genes). The identified DEGs were further analyzed to explore the molecular mechanism of T2D pathogenesis following a series of bioinformatics approaches. Following PPI (Protein-Protein Interaction), 867 potential DEGs and nine hub genes were identified that might play significant roles in T2D pathogenesis. Interestingly, CTNNB1 and RUNX2 hub genes were found to be unique for T2D pathogenesis in SAPs. Then, the GO (Gene Ontology) showed the potential biological, molecular, and cellular functions of the DEGs. The target genes also interacted with different pathways of T2D pathogenesis. In fact, 118 genes (including HNF1A and TCF7L2 hub genes) were directly associated with T2D pathogenesis. Indeed, eight key miRNAs among 2582 significantly interacted with the target genes. Even 64 genes were downregulated by 367 FDA-approved drugs. Interestingly, 11 genes showed a wide range (9-43) of drug specificity. Hence, the identified DEGs may guide to elucidate the molecular mechanism of T2D pathogenesis in SAPs. Therefore, integrating the research findings of the potential roles of DEGs and candidate drug-mediated downregulation of marker genes, future drugs or treatments could be developed to treat T2D in SAPs.
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Affiliation(s)
- Md. Golam Rabby
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Md. Hafizur Rahman
- Department of Agro Product Processing Technology, Jashore University of Science and Technology, Khulna, Bangladesh
- Faculty of Food Sciences and Safety, Department of Quality Control and Safety Management, Khulna Agricultural University, Khulna, Bangladesh
| | - Md. Numan Islam
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Md. Mostafa Kamal
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Mrityunjoy Biswas
- Department of Agro Product Processing Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Mantasa Bonny
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Md. Mahmudul Hasan
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
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Lou F, Zhang M. RFC2 promotes aerobic glycolysis and progression of colorectal cancer. BMC Gastroenterol 2023; 23:353. [PMID: 37821801 PMCID: PMC10566032 DOI: 10.1186/s12876-023-02984-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 09/29/2023] [Indexed: 10/13/2023] Open
Abstract
BACKGROUND Replication factor C subunit 2 (RFC2) participates in the growth and metastasis of various malignancies. Our study investigated the roles of RFC2 in colorectal cancer (CRC). RESULTS RFC2 expression was upregulated in CRC tissues and cells. High RFC2 expression was associated with poor prognosis. Knockdown RFC2 inhibited proliferation, induced apoptosis, and suppressed migration and invasion of CRC cells. CREB5 was a transcription factor of RFC2, and CREB5 knockdown suppressed RFC2 expression. Furthermore, RFC2 promoted aerobic glycolysis and MET/PI3K/AKT/mTOR pathway. CONCLUSION RFC2 promoted the progression of CRC cells via activating aerobic glycolysis and the MET/PI3K/AKT/mTOR pathway.
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Affiliation(s)
- Fuchen Lou
- Department of Endocrinology, The Second Hospital of Shandong University, Jinan, Shandong, 250033, P.R. China
| | - Mingbao Zhang
- Department of Gastroenterology, The Second Hospital of Shandong University, Beiyuan Street 247,Tianqiao District, Jinan, Shandong, 250033, P.R. China.
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9
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Song Y, Jiang Y, Shi L, He C, Zhang W, Xu Z, Yang M, Xu Y. Comprehensive analysis of key m5C modification-related genes in type 2 diabetes. Front Genet 2022; 13:1015879. [PMID: 36276976 PMCID: PMC9582283 DOI: 10.3389/fgene.2022.1015879] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 09/20/2022] [Indexed: 11/13/2022] Open
Abstract
Background: 5-methylcytosine (m5C) RNA methylation plays a significant role in several human diseases. However, the functional role of m5C in type 2 diabetes (T2D) remains unclear.Methods: The merged gene expression profiles from two Gene Expression Omnibus (GEO) datasets were used to identify m5C-related genes and T2D-related differentially expressed genes (DEGs). Least-absolute shrinkage and selection operator (LASSO) regression analysis was performed to identify optimal predictors of T2D. After LASSO regression, we constructed a diagnostic model and validated its accuracy. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to confirm the biological functions of DEGs. Gene Set Enrichment Analysis (GSEA) was used to determine the functional enrichment of molecular subtypes. Weighted gene co-expression network analysis (WGCNA) was used to select the module that correlated with the most pyroptosis-related genes. Protein-protein interaction (PPI) network was established using the STRING database, and hub genes were identified using Cytoscape software. The competitive endogenous RNA (ceRNA) interaction network of the hub genes was obtained. The CIBERSORT algorithm was applied to analyze the interactions between hub gene expression and immune infiltration.Results: m5C-related genes were significantly differentially expressed in T2D and correlated with most T2D-related DEGs. LASSO regression showed that ZBTB4 could be a predictive gene for T2D. GO, KEGG, and GSEA indicated that the enriched modules and pathways were closely related to metabolism-related biological processes and cell death. The top five genes were identified as hub genes in the PPI network. In addition, a ceRNA interaction network of hub genes was obtained. Moreover, the expression levels of the hub genes were significantly correlated with the abundance of various immune cells.Conclusion: Our findings may provide insights into the molecular mechanisms underlying T2D based on its pathophysiology and suggest potential biomarkers and therapeutic targets for T2D.
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Affiliation(s)
- Yaxian Song
- Department of Endocrinology, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yan Jiang
- Department of Endocrinology, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Li Shi
- Department of Endocrinology, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Chen He
- Department of Geriatric Medicine, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Wenhua Zhang
- Department of Endocrinology, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Zhao Xu
- Department of Endocrinology, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Mengshi Yang
- Department of Endocrinology, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yushan Xu
- Department of Endocrinology, The First Affiliated Hospital of Kunming Medical University, Kunming, China
- *Correspondence: Yushan Xu,
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Cai JL, Li XP, Zhu YL, Yi GQ, Wang W, Chen XY, Deng GM, Yang L, Cai HZ, Tong QZ, Zhou L, Tian M, Xia XH, Liu PA. Polygonatum sibiricum polysaccharides (PSP) improve the palmitic acid (PA)-induced inhibition of survival, inflammation, and glucose uptake in skeletal muscle cells. Bioengineered 2021; 12:10147-10159. [PMID: 34872451 PMCID: PMC8810107 DOI: 10.1080/21655979.2021.2001184] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Polygonatum sibiricum polysaccharides (PSP) can decrease the levels of fasting blood glucose, total cholesterol, and triglyceride (TG) in hyperlipidemic and diabetic animals. It can also reduce inflammatory cytokines and promote glucose uptake in adipocytes. However, the underlying molecular mechanisms of PSP in improving insulin resistance (IR) in skeletal muscle remain unclear. In this study, palmitic acid (PA) induced an IR model in L6 myotubes. After treatment, cell proliferation was measured using the CCK8. miR-340-3p, glucose transporter 4 (GLUT-4), and interleukin-1 receptor-associated kinase 3 (IRAK3) expression was measured by qRT-PCR. IRAK3 protein levels were measured by Western blotting. Glucose in the cell supernatant, TG concentration in L6 myotubes, and the levels of IL-1β, IL-6, and TNF-α were measured by an ELISA. We found that cell survival, glucose uptake, and GLUT-4 expression in L6 myotubes were significantly suppressed, while lipid accumulation and inflammatory factor levels were enhanced by PA stimulation. Furthermore, PSP treatment markedly alleviated these effects. Interestingly, PSP also significantly reduced the upregulated expression of miR-340-3p in the L6 myotube model of IR. Furthermore, overexpression of miR-340-3p reversed the beneficial effects of PSP in the same IR model. miR-340-3p can bind to the 3′-untranslated regions of IRAK3. Additionally, PA treatment inhibited IRAK3 expression, whereas PSP treatment enhanced IRAK3 expression in L6 myotubes. Additionally, miR-340-3p also inhibited IRAK3 expression in L6 myotubes. Taken together, PSP improved inflammation and glucose uptake in PA-treated L6 myotubes by regulating miR-340-3p/IRAK3, suggesting that PSP may be suitable as a novel therapeutic agent for IR.
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Affiliation(s)
- Jia-Luo Cai
- Preventive Treatment of Disease Center, The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China.,School of Pharmacy, Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Xiao-Ping Li
- Preventive Treatment of Disease Center, The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Yi-Lin Zhu
- Student Affairs Office, Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Gang-Qiang Yi
- Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Wei Wang
- Tcm and Ethnomedicine Innovation & Development International Laboratory, School of Pharmacy, Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Xin-Yu Chen
- The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Gui-Ming Deng
- Department of Scientific Research, The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Lei Yang
- Preparation Center, the First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Hu-Zhi Cai
- Department of Scientific Research, The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Qiao-Zhen Tong
- Hunan University of Chinese Medicine, Changsha, Hunan, China.,Yueyang Affiliated Hospital of Hunan University of Chinese Medicine, Yueyang, Hunan, China
| | - Li Zhou
- Preventive Treatment of Disease Center, The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Mengying Tian
- Preventive Treatment of Disease Center, The First Hospital of Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Xin-Hua Xia
- School of Pharmacy, Hunan University of Chinese Medicine, Changsha, Hunan, China
| | - Ping-An Liu
- Hunan University of Chinese Medicine, Changsha, Hunan, China
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11
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Li H, Ming X, Xu D, Mo H, Liu Z, Hu L, Zhou X. Transcriptome Analysis and Weighted Gene Co-expression Network Reveal Multitarget-Directed Antibacterial Mechanisms of Benzyl Isothiocyanate against Staphylococcus aureus. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2021; 69:11733-11741. [PMID: 34558287 DOI: 10.1021/acs.jafc.1c03979] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Staphylococcus aureus can cause many diseases and has a strong tendency to develop resistance to multiple antibiotics. In this study, benzyl isothiocyanate (BITC) was shown to have an excellent inhibitory effect on S. aureus ATCC25923 and methicillin-resistant S. aureus strains, with a minimum inhibitory concentration of 10 μg/mL. Under a scanning electron microscope, shrinkage and lysis of the cellular envelope were observed when exposed to BITC, and a bactericidal mode of BITC against S. aureus was further confirmed through flow cytometry. Additionally, the RNA profiles of S. aureus cells exposed to BITC indicated a violent transcriptional response to BITC. Through Kyoto Encyclopedia of Genes and Genomes analysis, it was found that many pathways involving bacterial survival were significantly affected, such as RNA degradation, oxidative phosphorylation, arginine biosynthesis, and so forth. A gene co-expression network was constructed using weighted gene co-expression network analysis, and six biologically meaningful co-expression modules and 125 hub genes were identified from the network. Among them, EfeB, GroES, SmpB, and Lsp were possibly targeted by BITC, leading to the death of S. aureus. Our results indicated a great potential of BITC to be applied in food safety and pharmaceuticals, highlighting its multitarget-directed bactericidal effects on S. aureus.
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Affiliation(s)
- Hongbo Li
- Department of Food and Bioengineering, Shaanxi University of Science and Technology, Shaanxi 710021, China
| | - Xujia Ming
- Department of Food and Bioengineering, Shaanxi University of Science and Technology, Shaanxi 710021, China
| | - Dan Xu
- Department of Food and Bioengineering, Shaanxi University of Science and Technology, Shaanxi 710021, China
| | - Haizhen Mo
- Department of Food and Bioengineering, Shaanxi University of Science and Technology, Shaanxi 710021, China
| | - Zhenbin Liu
- Department of Food and Bioengineering, Shaanxi University of Science and Technology, Shaanxi 710021, China
| | - Liangbin Hu
- Department of Food and Bioengineering, Shaanxi University of Science and Technology, Shaanxi 710021, China
| | - Xiaohui Zhou
- Department of Pathobiology & Veterinary Science, University of Connecticut, 61 North Eagleville Road, Storrs, Connecticut 06269, United States
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12
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Zhu M, Wu M, Bian S, Song Q, Xiao M, Huang H, You L, Zhang J, Zhang J, Cheng C, Ni W, Zheng W. DNA primase subunit 1 deteriorated progression of hepatocellular carcinoma by activating AKT/mTOR signaling and UBE2C-mediated P53 ubiquitination. Cell Biosci 2021; 11:42. [PMID: 33622397 PMCID: PMC7903777 DOI: 10.1186/s13578-021-00555-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 02/11/2021] [Indexed: 12/13/2022] Open
Abstract
Background DNA primase subunit 1 (PRIM1) has been reported as a novel oncogene in several cancer types. However, its roles in hepatocellular carcinoma (HCC) remain unclear. This study aimed to investigate underlying mechanisms of PRIM1 and identify it as a potential molecular target for HCC. Methods Hub genes were screened between HCC tissues and normal liver tissues in 3 gene expression omnibus (GEO) datasets and the cancer genome atlas (TCGA). The expression features and prognostic value of one of the hub genes PRIM1 were analyzed by bioinformatic analyses and immunohistochemistry. Loss-of-function and gain-of-function studies were used to investigate the regulatory role of PRIM1 in HCC cells. Real-time (RT)-qPCR, western blotting, and ubiquitin immunoprecipitation assays were performed to explore the underlying mechanisms. The xenograft model was employed to detect the roles of PRIM1 in tumor growth in vivo. Finally, the 3D spheroid model was conducted to validate the role of PRIM1 in tumor growth and sorafenib resistance. Results The hub genes of HCC were screened in multiple bioinformatic datasets. PRIM1, as one of the hub genes, was significantly overexpressed in HCC tissues in mRNA and protein levels. In addition, high expression of PRIM1 indicated poor prognosis of HCC patients in TCGA, ICGC, and Nantong cohorts. Overexpression of PRIM1 promoted the proliferation, migration/invasion, and sorafenib resistance of HCC cells, with the decrease in apoptosis and cell cycle arrest. Mechanically, PRIM1 facilitated epithelial-mesenchymal transition (EMT) process and the activity of PI3K/AKT/mTOR signaling of HCC cells. Additionally, PRIM1 could cause the ubiquitination and degradation of P53 by upregulating Ubiquitin Conjugating Enzyme E2 C (UBE2C). Furthermore, knockdown of PRIM1 significantly inhibited the growth of xenograft tumors and HCC cells-derived spheroids with enhanced sorafenib resistance. Conclusion This study implies that PRIM1 may play a key role in the progression of HCC and may serve as a potential target for HCC treatment.
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Affiliation(s)
- Mengqi Zhu
- Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, Jiangsu, China.,School of Medicine, Nantong University, 19 Qixiu Road, Nantong, 226001, Jiangsu, China.,Department of Oncology, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, Jiangsu, China
| | - Mengna Wu
- Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, Jiangsu, China
| | - Saiyan Bian
- Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, Jiangsu, China.,School of Medicine, Nantong University, 19 Qixiu Road, Nantong, 226001, Jiangsu, China
| | - Qianqian Song
- Department of Radiology, Wake Forest School of Medicine, One Medical Center Boulevard, Winston-Salem, 27157 NC, USA
| | - Mingbing Xiao
- Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, Jiangsu, China
| | - Hua Huang
- Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, Jiangsu, China
| | - Li You
- Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, Jiangsu, China
| | - Jianping Zhang
- Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, Jiangsu, China
| | - Jie Zhang
- Department of Oncology, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, Jiangsu, China
| | - Chun Cheng
- School of Medicine, Nantong University, 19 Qixiu Road, Nantong, 226001, Jiangsu, China
| | - Wenkai Ni
- Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, Jiangsu, China.
| | - Wenjie Zheng
- Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, Jiangsu, China. .,Department of Oncology, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, Jiangsu, China.
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13
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Zhai M, Luan P, Shi Y, Li B, Kang J, Hu F, Li M, Du L, Zhou D, Jian W, Peng W. Identification of Three Significant Genes Associated with Immune Cells Infiltration in Dysfunctional Adipose Tissue-Induced Insulin-Resistance of Obese Patients via Comprehensive Bioinformatics Analysis. Int J Endocrinol 2021; 2021:8820089. [PMID: 33564304 PMCID: PMC7850849 DOI: 10.1155/2021/8820089] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 12/10/2020] [Accepted: 01/06/2021] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Low-grade chronic inflammation in dysfunctional adipose tissue links obesity with insulin resistance through the activation of tissue-infiltrating immune cells. Numerous studies have reported on the pathogenesis of insulin-resistance. However, few studies focused on genes from genomic database. In this study, we would like to explore the correlation of genes and immune cells infiltration in adipose tissue via comprehensive bioinformatics analyses and experimental validation in mice and human adipose tissue. METHODS Gene Expression Omnibus (GEO) datasets (GSE27951, GSE55200, and GSE26637) of insulin-resistant individuals or type 2 diabetes patients and normal controls were downloaded to get differently expressed genes (DEGs), and GO and KEGG pathway analyses were performed. Subsequently, we integrated DEGs from three datasets and constructed commonly expressed DEGs' PPI net-works across datasets. Center regulating module of DEGs and hub genes were screened through MCODE and cytoHubba in Cytoscape. Three most significant hub genes were further analyzed by GSEA analysis. Moreover, we verified the predicted hub genes by performing RT qPCR analysis in animals and human samples. Besides, the relative fraction of 22 immune cell types in adipose tissue was detected by using the deconvolution algorithm of CIBERSORT (Cell Type Identification by Estimating Relative Subsets of RNA Transcripts). Furthermore, based on the significantly changed types of immune cells, we performed correlation analysis between hub genes and immune cells. And, we performed immunohistochemistry and immunofluorescence analysis to verify that the hub genes were associated with adipose tissue macrophages (ATM). RESULTS Thirty DEGs were commonly expressed across three datasets, most of which were upregulated. DEGs mainly participated in the process of multiple immune cells' infiltration. In protein-protein interaction network, we identified CSF1R, C1QC, and TYROBP as hub genes. GSEA analysis suggested high expression of the three hub genes was correlated with immune cells functional pathway's activation. Immune cell infiltration and correlation analysis revealed that there were significant positive correlations between TYROBP and M0 macrophages, CSF1R and M0 macrophages, Plasma cells, and CD8 T cells. Finally, hub genes were associated with ATMs infiltration by experimental verification. CONCLUSIONS This article revealed that CSF1R, C1QC, and TYROBP were potential hub genes associated with immune cells' infiltration and the function of proinflammation, especially adipose tissue macrophages, in the progression of obesity-induced diabetes or insulin-resistance.
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Affiliation(s)
- Ming Zhai
- Department of Cardiology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, 301 Middle Yanchang Road, Shanghai 200072, China
| | - Peipei Luan
- Department of Cardiology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, 301 Middle Yanchang Road, Shanghai 200072, China
| | - Yefei Shi
- Department of Cardiology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, 301 Middle Yanchang Road, Shanghai 200072, China
| | - Bo Li
- Department of Cardiology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, 301 Middle Yanchang Road, Shanghai 200072, China
| | - Jianhua Kang
- Department of Endocrinology, Xinhua Hospital, Shanghai Jiaotong University, School of Medicine, 1665 Kongjiang Road, Shanghai 200092, China
| | - Fan Hu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai 200233, China
| | - Mingjie Li
- Department of Endocrinology, Xinhua Hospital, Shanghai Jiaotong University, School of Medicine, 1665 Kongjiang Road, Shanghai 200092, China
| | - Lei Du
- Department of Metabolic Surgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, 301 Middle Yanchang Road, Shanghai 200072, China
| | - Donglei Zhou
- Department of General Surgery, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, 301 Middle Yanchang Road, Shanghai 200072, China
| | - Weixia Jian
- Department of Endocrinology, Xinhua Hospital, Shanghai Jiaotong University, School of Medicine, 1665 Kongjiang Road, Shanghai 200092, China
| | - Wenhui Peng
- Department of Cardiology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, 301 Middle Yanchang Road, Shanghai 200072, China
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