Bioinformatics analysis of differentially expressed genes in rotator cuff tear patients using microarray data.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 30424787.
- Also identified by DOI 10.1186/s13018-018-0989-5 and PMC identifier 6234628.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Rotator cuff tear (RCT) is a common shoulder disorder in the elderly. Muscle atrophy, denervation and fatty infiltration exert secondary injuries on torn rotator cuff muscles. It has been reported that satellite cells (SCs) play roles in pathogenic process and regenerative capacity of human RCT via regulating of target genes. This study aims to complement the differentially expressed genes (DEGs) of SCs that regulated between the torn supraspinatus (SSP) samples and intact subscapularis (SSC) samples, identify their functions and molecular pathways. The gene expression profile GSE93661 was downloaded and bioinformatics analysis was made. Five hundred fifty one DEGs totally were identified. Among them, 272 DEGs were overexpressed, and the remaining 279 DEGs were underexpressed. Gene ontology (GO) and pathway enrichment analysis of target genes were performed. We furthermore identified some relevant core genes using gene-gene interaction network analysis such as GNG13, GCG, NOTCH1, BCL2, NMUR2, PMCH, FFAR1, AVPR2, GNA14, and KALRN, that may contribute to the understanding of the molecular mechanisms of secondary injuries in RCT. We also discovered that GNG13/calcium signaling pathway is highly correlated with the denervation atrophy pathological process of RCT. These genes and pathways provide a new perspective for revealing the underlying pathological mechanisms and therapy strategy of RCT.
Medical subject headings
- Computational Biology
- Gene Regulatory Networks
- Protein Array Analysis
- Rotator Cuff Injuries
- Transcriptome
Anatomy
- shoulder