Dataset Information

Identification of key genes and pathways associated with spinal cord injury.

ABSTRACT: The present study was designed to identify key genes or significant signaling pathways associated with spinal cord injury (SCI), and to clarify the underlying molecular mechanisms of SCI. Data from the GSE45550 array were downloaded from the Gene Expression Omnibus database. A total of 6 control samples, 6 samples at 3 days post?SCI (SCI3d), 6 samples at 8 days post?SCI (SCI8d) and 6 samples at 14 days post?SCI (SCI14d) were included. The microarray data was preprocessed by the robust multi?array average algorithm. The differentially expressed genes (DEGs) were identified using the limma package. The overlapping DEGs among groups were analyzed using the Venny 2.0 online tool. Modules enriched by DEGs were selected by weighted gene co?expression network analysis. Gene Ontology annotation and the Kyoto Encyclopedia of Genes and Genomes pathways were identified for DEGs using the Database for Annotation, Visualization and Integrated Discovery. A total of 693 genes were obtained by combining the DEGs of the SCI3d, SCI8d and SCI14d groups. The pink module and green module with smaller P?values obtained from weighted gene co?expression network analysis module analyses of DEGs demonstrated a higher correlation with SCI. In addition, the peroxisome proliferator?activated receptor (PPAR) signaling pathway that the cluster of differentiation 36 (CD36) was significantly enriched in, was one of the significant pathways in the pink module. The p53 signaling pathway that Caspase?3 (Casp3) was significantly enriched in was one of the significant pathways in the green module. In conclusion, the results of the present study demonstrated that the PPAR and p53 signaling pathway may serve important roles in the progression of SCI. In addition, CD36 and Casp3 may be involved in the progression of SCI via the PPAR and p53 signaling pathways, respectively.

SUBMITTER: Zhang YH

PROVIDER: S-EPMC5364968 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Identification of key genes and pathways associated with spinal cord injury.

Zhang Yue-Hui YH Song Jia J Wang Li-Gang LG Shao Jiang J

Molecular medicine reports 20170210 4

The present study was designed to identify key genes or significant signaling pathways associated with spinal cord injury (SCI), and to clarify the underlying molecular mechanisms of SCI. Data from the GSE45550 array were downloaded from the Gene Expression Omnibus database. A total of 6 control samples, 6 samples at 3 days post‑SCI (SCI3d), 6 samples at 8 days post‑SCI (SCI8d) and 6 samples at 14 days post‑SCI (SCI14d) were included. The microarray data was preprocessed by the robust multi‑arra ...[more]

PMID: 28259986

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Project description:Background: Spinal cord injury (SCI) is a severe neurological deficit affecting both young and older people worldwide. The potential role of key enhancer RNAs (eRNAs) in SCI remains elusive, which is a prominent challenge in the trauma repair process. This study aims to investigate the roles of key eRNAs, transcription factors (TFs), signaling pathways, and small-molecule inhibitors in SCI using multi-omics bioinformatics analysis. Methods: Microarray data of peripheral blood mononuclear cell (PBMC) samples from 27 healthy volunteers and 25 chronic-phase SCI patients were retrieved from the Gene Expression Omnibus database. Differentially expressed transcription factors (DETFs), differentially expressed enhancer RNAs (DEeRNAs), and differentially expressed target genes (DETGs) were identified using the Linear Models for Microarray Data (limma) package. Fraction of immune cells was estimated using CIBERSORT algorithm. Gene Set Variation Analysis (GSVA) was applied to identify the downstream signaling pathways. The eRNA regulatory network was constructed based on the correlation results. Connectivity Map (CMap) database was used to find potential drugs for SCI patients. The cellular communication analysis was performed to explore the molecular regulation mechanism of SCI based on single-cell RNA sequencing (scRNA-seq) data. Chromatin immunoprecipitation sequencing (ChIP-seq) and Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data were used to validate the key regulatory mechanisms. scRNA-seq dataset was used to validate the cell subtype localization of the key eRNAs. Results: In total, 21 DETFs, 24 DEeRNAs, and 829 DETGs were identified. A regulatory network of 13 DETFs, six DEeRNAs, seven DETGs, two hallmark pathways, two immune cells, and six immune pathways was constructed. The link of Splicing factor proline and glutamine rich (SFPQ) (TF) and vesicular overexpressed in cancer prosurvival protein 1 (VOPP1) (eRNA) (R = 0.990, p < 0.001, positive), VOPP1 (eRNA) and epidermal growth factor receptor (EGFR) (target gene) (R = 0.974, p < 0.001, positive), VOPP1, and T helper (Th) cells (R = -0.987, p < 0.001, negative), and VOPP1 and hallmark coagulation (R = 0.937, p < 0.001, positive) was selected. Trichostatin A was considered the best compound target to SCI-related eRNAs (specificity = 0.471, p < 0.001). Conclusion: VOPP1, upregulated by SFPQ, strengthened the transient expression of EGFR. Th cells and coagulation were the potential downstream pathways of VOPP1. This regulatory network and potential inhibitors provide novel diagnostic biomarkers and therapeutic targets for SCI.

Dataset Information

Identification of key genes and pathways associated with spinal cord injury.

Publications

Identification of key genes and pathways associated with spinal cord injury.

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