The Expression Pattern and Regulatory Mechanism of the G0/G1 Switch Gene 2 (G0S2) in the Pathogenesis and Treatment of AChR Myasthenia Gravis (MG)

G0S2 promotes antiestrogenic and pro-migratory responses in ER+ and ER- breast cancer cells

G0/G1 switch gene 2 (G0S2) is known to inhibit lipolysis by inhibiting adipose triglyceride lipase (ATGL). In this report, we dissect the role of G0S2 in ER+ versus ER- breast cancer. Overexpression of G0S2 in ER- cells increased cell proliferation, while G0S2 overexpression in ER+ cells decreased cell proliferation. Transcriptome analysis revealed that G0S2 mediated distinct but overlapping transcriptional responses in ER- and ER+ cells. G0S2 reduced genes associated with an epithelial phenotype, especially in ER- cells, including CDH1, ELF3, STEAP4 and TACSTD2, suggesting promotion of the epithelial-mesenchymal transition (EMT). G0S2 also repressed estrogen signaling and estrogen receptor target gene signatures, especially in ER+ cells, including TFF1 and TFF3. In addition, G0S2 overexpression increased cell migration in ER- cells and increased estrogen deprivation sensitivity in ER+ cells. Interestingly, two genes downstream of ATGL in fat utilization and very important in steroid hormone biosynthesis, HMGCS1 and HMGCS2, were downregulated in G0S2 overexpressing ER+ cells. In addition, HSD17B11, a gene that converts estradiol to its less estrogenic derivative, estrone, was highly upregulated in G0S2 overexpressing ER+ cells, suggesting G0S2 overexpression has a negative effect on estradiol production and maintenance. High expression of G0S2 and HSD17B11 was associated with improved relapse-free survival in breast cancer patients while high expression of HMGSC1 was associated with poor survival. Finally, we deleted G0S2 in breast cancer-prone MMTV-PyMT mice. Our data indicates a complex role for G0S2 in breast cancer, dependent on ER status, that may be partially mediated by suppression of the estrogen signaling pathway.

The effect of G0S2 on insulin sensitivity: A proteomic analysis in a G0S2-overexpressed high-fat diet mouse model

BACKGROUND

Previous research has shown a tight relationship between the G0/G1 switch gene 2 (G0S2) and metabolic diseases such as non-alcoholic fatty liver disease (NAFLD) and obesity and diabetes, and insulin resistance has been shown as the major risk factor for both NAFLD and T2DM. However, the mechanisms underlying the relationship between G0S2 and insulin resistance remain incompletely understood. Our study aimed to confirm the effect of G0S2 on insulin resistance, and determine whether the insulin resistance in mice fed a high-fat diet (HFD) results from G0S2 elevation.

METHODS

In this study, we extracted livers from mice that consumed HFD and received tail vein injections of AD-G0S2/Ad-LacZ, and performed a proteomics analysis.

RESULTS

Proteomic analysis revealed that there was a total of 125 differentially expressed proteins (DEPs) (56 increased and 69 decreased proteins) among the identified 3583 proteins. Functional enrichment analysis revealed that four insulin signaling pathway-associated proteins were significantly upregulated and five insulin signaling pathway -associated proteins were significantly downregulated.

CONCLUSION

These findings show that the DEPs, which were associated with insulin resistance, are generally consistent with enhanced insulin resistance in G0S2 overexpression mice. Collectively, this study demonstrates that G0S2 may be a potential target gene for the treatment of obesity, NAFLD, and diabetes.

Identification of LINC00173 in Myasthenia Gravis by Integration Analysis of Aberrantly Methylated- Differentially Expressed Genes and ceRNA Networks

Myasthenia gravis (MG) is an autoimmune disease associated with autoantibody production that leads to skeletal muscle weakness. The molecular mechanisms underlying MG are not fully understood. We analyzed the gene expression profile (GSE85452) and methylation profile (GSE85647) of MG samples from the GEO database to identify aberrantly methylated-differentially expressed genes. By integrating the datasets, we identified 143 hypermethylation-low expression genes and 91 hypomethylation-high expression genes. Then we constructed PPI network and ceRNA networks by these genes. Phosphatase and tensin homolog (PTEN) and Abelson tyrosine-protein kinase (ABL)1 were critical genes in both PPI networks and ceRNA networks. And potential MG associated lncRNAs were selected by comprehensive analysis of the critical genes and ceRNA networks. In the hypermethylation-low expression genes associated ceRNA network, sirtuin (SIRT)1 was the most important gene and the lncRNA HLA complex (HC) P5 had the highest connection degree. Meanwhile, PTEN was the most important gene and the lncRNA LINC00173 had the highest connection degree in the hypomethylation-high expression genes associated ceRNA network. LINC00173 was validated to be upregulated in MG patients by qRT-PCR (P = 0.005), which indicated LINC00173 might be a potential biomarker for MG. These results provide a basis for future studies on the molecular pathogenesis of MG.