Analysis of Hub Genes Involved in Distinction Between Aged and Fetal Bone Marrow Mesenchymal Stem Cells by Robust Rank Aggregation and Multiple Functional Annotation Methods

Abstract

Stem cells from fetal tissue protect against aging and possess greater proliferative capacity than their adult counterparts. These cells can more readily expand in vitro and senesce later in culture. However, the underlying molecular mechanisms for these differences are still not fully understood. In this study, we used a robust rank aggregation (RRA) method to discover robust differentially expressed genes (DEGs) between fetal bone marrow mesenchymal stem cells (fMSCs) and aged adult bone marrow mesenchymal stem cells (aMSCs). Multiple methods, including gene set enrichment analysis (GSEA), Gene Ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed for functional annotation of the robust DEGs, and the results were visualized using the R software. The hub genes and other genes with which they interacted directly were detected by protein–protein interaction (PPI) network analysis. Correlation of gene expression was measured by Pearson correlation coefficient. A total of 388 up-regulated and 289 down-regulated DEGs were identified between aMSCs and fMSCs. We found that the down-regulated genes were mainly involved in the cell cycle, telomerase activity, and stem cell proliferation. The up-regulated DEGs were associated with cell adhesion molecules, extracellular matrix (ECM)–receptor interactions, and the immune response. We screened out four hub genes, MYC, KIF20A, HLA-DRA, and HLA-DPA1, through PPI-network analysis. The MYC gene was negatively correlated with TXNIP, an age-related gene, and KIF20A was extensively involved in the cell cycle. The results suggested that MSCs derived from the bone marrow of an elderly donor present a pro-inflammatory phenotype compared with that of fMSCs, and the HLA-DRA and HLA-DPA1 genes are related to the immune response. These findings provide new insights into the differences between aMSCs and fMSCs and may suggest novel strategies for ex vivo expansion and application of adult MSCs.

A Five-Gene-Based Prognostic Signature for Hepatocellular Carcinoma

“…The genes with different degree values in the network were represented by different colors. According to PPI analysis results, the genes with degree greater than 10 were defined as core genes ( 15 , 16 ). Multivariate Cox analysis was used to analyze the core genes.…”

Robust Rank Aggregation and Least Absolute Shrinkage and Selection Operator Analysis of Novel Gene Signatures in Dilated Cardiomyopathy

“…However, most of the gene signatures were analyzed from a single data set, and a limited number of patients have been included in most previous studies, which may compromise the prediction power or reliability. In-depth exploration of the public datasets can reveal disease related genes and develop a efficient risk gene signature in combination with clinicopathological characteristics ( 13 ), which can help to form a promising tool for predicting status of DCM and individualized therapy.…”

Elucidating the genetic effect of vitamin D on mesenchymal stem cell differentiation in vitro

“…Ablation of CYP24A1 inhibits the antiproliferative and pro-differentiation effects of 1α,25-(OH) 2 D 3 on hMSCs [30], further con rming the importance of this gene in enabling the biological effects of vitamin D. Conversely, the enzyme responsible for vitamin D removal and breakdown, 25(OH)D-24-hydroxylase, (CYP24A1 gene encoded by CYP24A1), has also been implicated in bone metabolism [31]. Inactivating mutations of the CYP24A1 gene result in hypercalcemia and hypercalciuria secondary to diminished 1α,25-(OH) 2 D degradation [32].…”