Identification of key candidate genes in local dorsal root ganglion inflammation by integrated bioinformatics analysis.
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ABSTRACT:
SUBMITTER: Chen L
PROVIDER: S-EPMC8193217 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Rodent dorsal root ganglion (DRG) is widely used for studying axonal injury. Extensive studies have explored genome-wide profiles on rodent DRGs under peripheral nerve insults. However, systematic integration and exploration of these data still be limited. Herein, we re-analyzed 21 RNA-seq datasets and presented a web-based resource (DRGProfile). We identified 53 evolutionarily conserved injury response genes, including well-known injury genes (Atf3, Npy and Gal) and less-studied transcriptional factors (Arid5a, Csrnp1, Zfp367). Notably, we identified species-preference injury response candidates (e.g. Gpr151, Lipn, Anxa10 in mice; Crisp3, Csrp3, Vip, Hamp in rats). Temporal profile analysis reveals expression patterns of genes related to pre-regenerative and regenerating states. Finally, we found a large sex difference in response to sciatic nerve injury, and identified four male-specific markers (Uty, Eif2s3y, Kdm5d, Ddx3y) expressed in DRG. Our study provides a comprehensive integrated landscape for expression change in DRG upon injury which will greatly contribute to the neuroscience community.
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Project description:Breast cancer (BC) is the leading malignancy in women worldwide, yet relatively little is known about the genes and signaling pathways involved in BC tumorigenesis and progression. The present study aimed to elucidate potential key candidate genes and pathways in BC. Five gene expression profile data sets (GSE22035, GSE3744, GSE5764, GSE21422 and GSE26910) were downloaded from the Gene Expression Omnibus (GEO) database, which included data from 113 tumorous and 38 adjacent non?tumorous tissue samples. Differentially expressed genes (DEGs) were identified using t?tests in the limma R package. These DEGs were subsequently investigated by pathway enrichment analysis and a protein?protein interaction (PPI) network was constructed. The most significant module from the PPI network was selected for pathway enrichment analysis. In total, 227 DEGs were identified, of which 82 were upregulated and 145 were downregulated. Pathway enrichment analysis results revealed that the upregulated DEGs were mainly enriched in 'cell division', the 'proteinaceous extracellular matrix (ECM)', 'ECM structural constituents' and 'ECM?receptor interaction', whereas downregulated genes were mainly enriched in 'response to drugs', 'extracellular space', 'transcriptional activator activity' and the 'peroxisome proliferator?activated receptor signaling pathway'. The PPI network contained 174 nodes and 1,257 edges. DNA topoisomerase 2?a, baculoviral inhibitor of apoptosis repeat?containing protein 5, cyclin?dependent kinase 1, G2/mitotic?specific cyclin?B1 and kinetochore protein NDC80 homolog were identified as the top 5 hub genes. Furthermore, the genes in the most significant module were predominantly involved in 'mitotic nuclear division', 'mid?body', 'protein binding' and 'cell cycle'. In conclusion, the DEGs, relative pathways and hub genes identified in the present study may aid in understanding of the molecular mechanisms underlying BC progression and provide potential molecular targets and biomarkers for BC.
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Project description:Neuropathic pain (NP) is caused by primary or secondary impairment of the peripheral or central nervous systems. Its etiology is complex and involves abnormal patterns of gene expression and pathway activation. Using bioinformatics analysis, we aimed to identify NP-associated changes in genes and pathways in L4 and L5 dorsal root ganglia (DRG) in a rat model of NP induced by chronic compression of the DRG (CCD). Genome-wide transcriptional analyses were used to elucidate the molecular mechanisms underlying NP. We screened differentially expressed genes (DEGs) 7 days after CCD in comparison with sham-operated controls. Quantitative real-time polymerase chain reaction (RT-qPCR) and western blotting were used to confirm the presence of key DEGs. Kyoto Encyclopedia of Genes and Genomes (KEGG)-pathway analysis of DEGs and global signal transduction network analysis of DEGs were also conducted. The CCD group developed clear mechanical and thermal allodynia in the ipsilateral hind paw compared with the sham group. This comparison identified 1,887 DEGs, with 1156 upregulated and 731 downregulated DEGs, and 123 DEG-enriched pathways. We identified the key candidate genes that might play a role in the development of NP, namely syndecan 1 (Sdc1), phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit gamma (Pi3k), Janus kinase 2 (Jak2), jun proto-oncogene, AP-1 transcription factor subunit (Jun), and interleukin 6 (IL-6) by analyzing the global signal transduction network. RT-qPCR and western blot analysis confirmed the microarray results. The DEGs Sdc1, Pi3k, Jak2, Jun, and IL-6, and the cytokine signaling pathway, the neuroactive ligand-receptor interaction, the toll-like receptor signaling pathway, and the PI3K-Akt signaling pathway may have decisive modulatory roles in both nerve regeneration and NP. These results provide deeper insight into the mechanism underlying NP and promising therapeutic targets for its treatment.
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Project description:Background:Rheumatoid arthritis (RA) leads to pain through alteration of gene expression. Although gene expression alteration in knee cartilage or peripheral blood from RA patients has been identified using microarray, it remains unclear whether long non-coding RNA (lncRNA)-mediated gene regulation occurs in primary sensory neurons of dorsal root ganglia (DRG) during RA-like joint inflammation. In the present study, we aimed to analyze lncRNA and related mRNA profiles in the DRG in a knee joint inflammation rat model. Methods:Complete Freund's adjuvant (CFA) was injected in the rat knee joint for preparing the joint inflammation model. A lncRNA-mRNA microarray of rat DRG was employed for transcriptome analysis. Functional roles of differentially expressed lncRNAs and their related mRNAs in the injured DRG were delineated by bioinformatic analysis. Results:We observed that expression levels of 9000 lncRNAs were altered on day 7 post-CFA, of which 45.17% were up-regulated and 54.83% were down-regulated. Specifically, 69 lncRNAs (42 up and 27 down) were significantly regulated. We also observed that expression levels of 13,744 mRNAs were altered on day 7 post-CFA, of which 49.67% were up-regulated and 50.33% were down-regulated. Specifically, 102 mRNAs (51 up and 51 down) were significantly regulated. Using quantitative real-time PCR, we verified the changes in differentially expressed lncRNAs in the injured DRG. Conclusion:These results suggest that microarray-based RNA sequencing can be used to identify altered lncRNAs and relevant mRNAs in the DRG of rats with knee joint inflammation.
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Project description:Multiple myeloma (MM) is a common hematologic malignancy for which the underlying molecular mechanisms remain largely unclear. This study aimed to elucidate key candidate genes and pathways in MM by integrated bioinformatics analysis. Expression profiles GSE6477 and GSE47552 were obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) with p < .05 and [logFC] > 1 were identified. Functional enrichment, protein-protein interaction network construction and survival analyses were then performed. First, 51 upregulated and 78 downregulated DEGs shared between the two GSE datasets were identified. Second, functional enrichment analysis showed that these DEGs are mainly involved in the B cell receptor signaling pathway, hematopoietic cell lineage, and NF-kappa B pathway. Moreover, interrelation analysis of immune system processes showed enrichment of the downregulated DEGs mainly in B cell differentiation, positive regulation of monocyte chemotaxis and positive regulation of T cell proliferation. Finally, the correlation between DEG expression and survival in MM was evaluated using the PrognoScan database. In conclusion, we identified key candidate genes that affect the outcomes of patients with MM, and these genes might serve as potential therapeutic targets.
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Project description:PurposeNeuropathic pain is a complex chronic condition occurring post-nervous system damage. The transcriptional reprogramming of injured dorsal root ganglia (DRGs) drives neuropathic pain. However, few comparative analyses using high-throughput platforms have investigated uninjured DRG in neuropathic pain, and potential interactions among differentially expressed genes (DEGs) and pathways were not taken into consideration. The aim of this study was to identify changes in genes and pathways associated with neuropathic pain in uninjured L4 DRG after L5 spinal nerve ligation (SNL) by using bioinformatic analysis.Materials and methodsThe microarray profile GSE24982 was downloaded from the Gene Expression Omnibus database to identify DEGs between DRGs in SNL and sham rats. The prioritization for these DEGs was performed using the Toppgene database followed by gene ontology and pathway enrichment analyses. The relationships among DEGs from the protein interactive perspective were analyzed using protein-protein interaction (PPI) network and module analysis. Real-time polymerase chain reaction (PCR) and Western blotting were used to confirm the expression of DEGs in the rodent neuropathic pain model.ResultsA total of 206 DEGs that might play a role in neuropathic pain were identified in L4 DRG, of which 75 were upregulated and 131 were downregulated. The upregulated DEGs were enriched in biological processes related to transcription regulation and molecular functions such as DNA binding, cell cycle, and the FoxO signaling pathway. Ctnnb1 protein had the highest connectivity degrees in the PPI network. The in vivo studies also validated that mRNA and protein levels of Ctnnb1 were upregulated in both L4 and L5 DRGs.ConclusionThis study provides insight into the functional gene sets and pathways associated with neuropathic pain in L4 uninjured DRG after L5 SNL, which might promote our understanding of the molecular mechanisms underlying the development of neuropathic pain.
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Project description:Oral squamous cell carcinoma (OSCC) is one of the most common types of malignant head and neck tumor, which poses a serious threat to human health. In recent years, the incidence of OSCC has been increasing, while the prognosis has not significantly improved. Elucidation of the molecular mechanisms underlying the development of OSCC may provide novel therapeutic strategies. In the present study, the gene expression profiles from 4 datasets, including 244 OSCC and 95 normal oral mucosa samples, were subjected to statistical and Bioinformatics analysis. A total of 34 differentially expressed genes (DEGs) were identified, among which 14 were upregulated and 20 were downregulated in OSCC compared with normal oral mucosa tissues. Gene Ontology enrichment analysis indicated that the DEGs were mainly involved in regulation of the immune response, cell adhesion and cell proliferative processes. The Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the DEGs were mainly associated with the phosphoinositide-3 kinase Akt and Toll-like receptor signaling pathway. The key candidate DEGs were identified from the complex protein-protein interaction network, and secreted phosphoprotein 1 (SPP1), integrin subunit α 3 and plasminogen activator, urokinase (PLAU) were confirmed to be significantly associated with the survival rate. Cell Counting Kit-8 and Transwell assays demonstrated that SPP1 and PLAU regulate cell proliferation, migration and invasion. The candidate genes/pathways identified in the present study may include promising diagnostic biomarkers or therapeutic targets for OSCC.
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Project description:Globally, nearly 40 percent of all diabetic patients develop serious diabetic kidney disease (DKD). The identification of the potential early-stage biomarkers and elucidation of their underlying molecular mechanisms in DKD are required. In this study, we performed integrated bioinformatics analysis on the expression profiles GSE111154, GSE30528 and GSE30529 associated with early diabetic nephropathy (EDN), glomerular DKD (GDKD) and tubular DKD (TDKD), respectively. A total of 1,241, 318 and 280 differentially expressed genes (DEGs) were identified for GSE30258, GSE30529, and GSE111154 respectively. Subsequently, 280 upregulated and 27 downregulated DEGs shared between the three GSE datasets were identified. Further analysis of the gene expression levels conducted on the hub genes revealed SPARC (Secreted Protein Acidic And Cysteine Rich), POSTN (periostin), LUM (Lumican), KNG1 (Kininogen 1), FN1 (Fibronectin 1), VCAN (Versican) and PTPRO (Protein Tyrosine Phosphatase Receptor Type O) having potential roles in DKD progression. FN1, LUM and VCAN were identified as upregulated genes for GDKD whereas the downregulation of PTPRO was associated with all three diseases. Both POSTN and SPARC were identified as the overexpressed putative biomarkers whereas KNG1 was found as downregulated in TDKD. Additionally, we also identified two drugs, namely pidorubicine, a topoisomerase inhibitor (LINCS ID- BRD-K04548931) and Polo-like kinase inhibitor (LINCS ID- BRD-K41652870) having the validated role in reversing the differential gene expression patterns observed in the three GSE datasets used. Collectively, this study aids in the understanding of the molecular drivers, critical genes and pathways that underlie DKD initiation and progression.
| S-EPMC8453249 | biostudies-literature
Project description:Hepatocellular carcinoma (HCC) accounts for approximately 85-90% of all liver cancer cases and has poor relapse-free survival. There are many gene expression studies that have been performed to elucidate the genetic landscape and driver pathways leading to HCC. However, existing studies have been limited by the sample size and thus the pathogenesis of HCC is still unclear. In this study, we performed an integrated characterization using four independent datasets including 320 HCC samples and 270 normal liver tissues to identify the candidate genes and pathways in the progression of HCC. A total of 89 consistent differentially expression genes (DEGs) were identified. Gene-set enrichment analysis revealed that these genes were significantly enriched for cellular response to zinc ion in biological process group, collagen trimer in the cellular component group, extracellular matrix (ECM) structural constituent conferring tensile strength in the molecular function group, protein digestion and absorption, mineral absorption and ECM-receptor interaction. Network system biology based on the protein-protein interaction (PPI) network was also performed to identify the most connected and important genes based on our DEGs. The top five hub genes including osteopontin (SPP1), Collagen alpha-2(I) chain (COL1A2), Insulin-like growth factor I (IGF1), lipoprotein A (LPA), and Galectin-3 (LGALS3) were identified. Western blot and immunohistochemistry analysis were employed to verify the differential protein expression of hub genes in HCC patients. More importantly, we identified that these five hub genes were significantly associated with poor disease-free survival and overall survival. In summary, we have identified a potential clinical significance of these genes as prognostic biomarkers for HCC patients who would benefit from experimental approaches to obtain optimal outcome.
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Project description:ObjectiveTo screen and identify differentially expressed genes in the dorsal root ganglion (DRG) in early experimental diabetic rats.MethodsDiabetic model rats were induced by single intraperitoneal injection of streptozotocin (STZ). At the second week after STZ injection, the sensory nerve conduction velocities (SNCV) of sciatic nerve were measured as an indicator of neuropathy. The technique of silver-staining mRNA differential display polymerase chain reaction (DD-PCR) was used to detect the levels of differentially expressed genes in rat DRG. The cDNA fragments that displayed differentially were identified by reverse-hybridization, cloned and sequenced subsequently, and then confirmed by Northern blot.ResultsThe SNCV in the diabetic model group [n = 9, (45.25+/-10.38) m/s] reduced obviously compared with the control group [n = 8, (60.10+/-11.92) m/s] (P < 0.05). Seven distinct cDNA clones, one was up-regulated gene and the others were down-regulated ones, were isolated by silver-staining mRNA differential display method and confirmed by Northern blot. According to the results of sequence alignment with GenBank data, majority of the clones had no significant sequence similarity to previously reported genes except only one that showed high homology to 6-pyruvoyl-tetrahydropterin synthase mRNA (accession No. BC059140), which had not been reported to relate to diabetic neuropathy.ConclusionThese differentially expressed genes in the diabetic DRG may contribute to the pathogenesis of diabetic peripheral neuropathy.
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