Analysis of STAT1, STAT2 and STAT3 mRNA expression levels in the blood of patients with multiple sclerosis

Effect of sitagliptin therapy on IL-29 and its associated signaling molecules in patients with type 2 diabetes mellitus

OBJECTIVE

The potential immunoregulatory capacity of sitagliptin on interleukin-29 (IL-29) and genes involved in its intracellular pathway were explored in type 2 diabetes mellitus (T2D).

MATERIALS AND METHODS

T2D patients treated with six months of sitagliptin (Sita+), patients not treated with sitagliptin (Sita-), and healthy controls (HCs) were included. IL-29 levels in the supernatant of stimulated mononuclear immune cells was determined with ELISA. The mRNA expression levels of IL-29, FOS, JUN, NF-AT2, NF-KB1, STAT1-2, IRF1, IRF3, IRF7, and IRF9 was assessed with real-time qPCR.

RESULTS

Increased protein and gene levels of IL-29 were observed in Sita- group compared to HCs (p < 0.001 and p = 0.026), while those levels were diminished in Sita+ group in comparison with Sita- group (p < 0.001 and p = 0.008). Expression of FOS, NF-AT2 and NF-KB1 in Sita- patients was higher than HCs (p = 0.018, p = 0.021, and p = 0.001). A significant decrease in expression of FOS, NF-AT2, and NF-KB1 was found in Sita+ group versus Sita- parients (p = 0.027, p = 0.003, and p = 0.002). In Sita- patients, IL-29 levels were correlated to glucose metabolism parameters including FPG and HbA1c (p < 0.05 for all).

CONCLUSION

Sitagliptin administration has a regulatory effect on the aggressive expression of IL-29 and its signaling molecules including FOS, NF-AT2 and NF-KB1 in T2D.

Altered non-coding RNA profiles and potential disease marker identification in peripheral blood mononuclear cells of patients with NMOSD

Neuromyelitis optica spectrum disorder (NMOSD) is an inflammatory demyelination disorder, and dysregulation of RNAs contributes to its pathogenesis. We aimed to reveal the expression profiles of RNAs, including messenger RNA (mRNA), circular RNA (circRNA) and long non-coding RNA (lncRNA), in the peripheral blood mononuclear cells (PBMCs) of patients with NMOSD. Seven NMOSD patients and seven healthy controls (HCs) were enrolled in the competitive endogenous RNA (ceRNA) microarray analysis. Bioinformatics analysis was then performed on the microarray data. Selected RNAs were validated by RT-qPCR. Differentially expressed (DE) RNA profiles of patients and HCs were related to NK cell mediated cytotoxicity, the IL-17 signaling pathway, and the B cell receptor signaling pathway. Moreover, DE non-coding RNAs (DE ncRNAs) including DE circRNAs and DE lncRNAs, may participate in the transforming growth factor beta (TGF-β) signaling pathway, leukocyte migration and neutrophil chemotaxis. Immune cell infiltration analysis showed that the abundance of M1 macrophages and plasma cells significantly increased, while that of M2 macrophages significantly decreased in the NMOSD group. Finally, through RT-qPCR validation, lnc-HELZ-7:1 (95% confidential interval of area under curve [95%CI of AUC] = 0.6633-1.0000), ring finger protein-LIM domain interacting (RLIM; 95%CI of AUC = 0.6980-1.0000), and hsa_circ_0026993 (95%CI of AUC = 0.7550-1.0000) could discriminate NMOSD from HCs by receiver operating characteristic curve analysis. To our knowledge, this is the first study to preliminarily investigate the RNA profiles, especially circRNA profiles in PBMCs of NMOSD patients from North China. We identified lnc-HELZ-7:1, RLIM, and hsa_circ_0026993 as the potential disease markers for NMOSD.

The Shared Mechanism and Candidate Drugs of Multiple Sclerosis and Sjögren's Syndrome Analyzed by Bioinformatics Based on GWAS and Transcriptome Data

Objective

This study aimed to explore the shared mechanism and candidate drugs of multiple sclerosis (MS) and Sjögren's syndrome (SS).

Methods

MS- and SS-related susceptibility genes and differentially expressed genes (DEGs) were identified by bioinformatics analysis based on genome-wide association studies (GWAS) and transcriptome data from GWAS catalog and Gene Expression Omnibus (GEO) database. Pathway enrichment, Gene Ontology (GO) analysis, and protein-protein interaction analysis for susceptibility genes and DEGs were performed. The drugs targeting common pathways/genes were obtained through Comparative Toxicogenomics Database (CTD), DrugBank database, and Drug-Gene Interaction (DGI) Database. The target genes of approved/investigational drugs for MS and SS were obtained through DrugBank and compared with the common susceptibility genes.

Results

Based on GWAS data, we found 14 hub common susceptibility genes (HLA-DRB1, HLA-DRA, STAT3, JAK1, HLA-B, HLA-DQA1, HLA-DQA2, HLA-DQB1, HLA-DRB5, HLA-DPA1, HLA-DPB1, TYK2, IL2RA, and MAPK1), with 8 drugs targeting two or more than two genes, and 28 common susceptibility pathways, with 15 drugs targeting three or more than three pathways. Based on transcriptome data, we found 3 hub common DEGs (STAT1, GATA3, PIK3CA) with 3 drugs and 10 common risk pathways with 435 drugs. "JAK-STAT signaling pathway" was included in common susceptibility pathways and common risk pathways at the same time. There were 133 overlaps including JAK-STAT inhibitors between agents from GWAS and transcriptome data. Besides, we found that IL2RA and HLA-DRB1, identified as hub common susceptibility genes, were the targets of daclizumab and glatiramer that were used for MS, indicating that daclizumab and glatiramer may be therapeutic for SS.

Conclusion

We observed the shared mechanism of MS and SS, in which JAK-STAT signaling pathway played a vital role, which may be the genetic and molecular bases of comorbidity of MS with SS. Moreover, JAK-STAT inhibitors were potential therapies for MS and SS, especially for their comorbidity.

Transcription factors and regulators pathway-focused genes expression analysis in patients with different forms of thyroid pathology

BACKGROUND

Autoimmune thyroiditis (AIT) is a T cell-mediated organ-specific disorder and transcription factors have a critical role in the regulation of immune responses, especially in the fate of T-helper cells.

OBJECTIVE

This study aims to investigate changes in the gene expression profile of transcription factors and regulators in patients with different forms of thyroid pathology Methods. We used the pathway-specific real-time PCR array (Neurotrophins and Receptors RT2 Profiler PCR Array, QIAGEN, Germany) to identify and verify transcription factors and regulators pathway-focused genes expression in peripheral white blood cells of patients with postoperative hypothyroidism, hypothyroidism as a result of AIT and AIT with elevated serum an anti-thyroglobulin (anti-Tg) and anti-thyroid peroxidase (anti-TPO) antibodies.

RESULTS

It was shown that in patients with postoperative hypothyroidism FOS, NR1I2, STAT4, and TP53 significantly increased their expression whereas the expression of STAT1, STAT2, and STAT3 decreased. In patients with hypothyroidism as a result of AIT, we have found increased expression of NR1I2, STAT2, and STAT3. In contrast, the expression of STAT1 and TP53 decreased. FOS and STAT4 mRNAs did not change their expression. In patients with AIT and elevated serum anti-Tg and anti-TPO antibodies, the expression of FOS and NR1I2 reduced whereas the mRNA level of STAT3 increased. STAT1, STAT2, and STAT4 mRNAs did not change their expression. MYC did not change its expression in all groups of patients.

CONCLUSIONS

The results of this study demonstrate that autoimmune thyroiditis and hypothyroidism affect the mRNA-level expression of transcription factors and regulators genes in a gene-specific manner and that these changes to genes expression can be among the triggers of autoimmune inflammation progression in the thyroid gland.

Evaluation of Expression of STAT Genes in Immune-Mediated Polyneuropathies

Immune-mediated polyneuropathies are acquired conditions that can be categorized to acute and chronic forms based on the disease course. Although the basic mechanism of these conditions has not been clarified yet, genes that regulate immune responses are putative contributors in their development. In the current study, we assessed expression of signal transducer and activator of transcription (STAT)1-3 and STAT5a genes in peripheral blood of 51 patients and 40 healthy subjects. Expression of STAT1 was higher in female patients compared with female controls (Posterior Beta = 3.622, P = 0.044). The gender*group interaction was significant for this gene which indicates different direction of association in males and females. Expressions of other STAT genes were not different between cases and controls. The diagnostic power of STAT1 in female subjects was estimated to be 0.72 with sensitivity of 68.75% and specificity of 84.62%. There was no significant correlation either between expression of different STAT genes or between their expression and age of study participants. The current study potentiates STAT1 as a putative factor in the pathophysiology of acquired immune-mediated polyneuropathies in females and suggests conduction of further functional studies to elaborate the molecular mechanism of this contribution.

Cytokines and Transgenic Matrix in Autoimmune Diseases: Similarities and Differences

Autoimmune diseases are increasingly recognized as disease entities in which dysregulated cytokines contribute to tissue-specific inflammation. In organ-specific and multiorgan autoimmune diseases, the cytokine profiles show some similarities. Despite these similarities, the cytokines have different roles in the pathogenesis of different diseases. Altered levels or action of cytokines can result from changes in cell signaling. This article describes alterations in the JAK-STAT, TGF-β and NF-κB signaling pathways, which are involved in the pathogenesis of multiple sclerosis and systemic lupus erythematosus. There is a special focus on T cells in preclinical models and in patients afflicted with these chronic inflammatory diseases.

[High expression of STAT2 in ovarian cancer and its effect on metastasis of ovarian cancer cells]

OBJECTIVE

To investigate the expression of signal transduction and activator of transcription 2 (STAT2) in ovarian cancer and its correlation with the prognosis of ovarian cancer patients and explore the role of STAT2 inregulating metastasis of ovarian cancer cells.

METHODS

RT-qPCR was performed to detect the expression of STAT2 mRNA in 62 fresh frozen ovarian cancer tissues and 62 normal ovarian tissues; immunohistochemistry was used to detect STAT2 protein expressions in 95 paraffin-embedded ovarian cancer samples and 33 normal ovarian tissues. Kaplan-Meier method was used to analyze the correlation between the expression of STAT2 and the prognosis of the patients. We also examined the relationship between STAT2 and the patients' prognosis by analyzing the data in Kaplan-Meier Plotter database. Western blotting was performed to detect the expression of STAT2 in different ovarian cancer cell lines. In A2780 cells with the highest STAT2 expression, we examined the effects of STAT2 interference on cell migration and invasiveness using Transwell migration assay and on the expressions of the downstream molecule epidermal growth factor receptor (EGFR).

RESULTS

Ovarian cancer tissues expressed significantly higher levels of STAT2 mRNA than normal ovarian tissue. A high STAT2 mRNA expression was correlated with an advanced FIGO stage. Immunohistochemistry showed that 67.4% of the ovarian cancer samples, as compared with 28.3% of normal ovarian tissues, showed high STAT2 expressions. In ovarian cancer patients, a high expression of STAT2 protein was associated with ascites volume, distant metastasis and FIGO stage (P < 0.05). Survival analysis showed that ovarian cancer patients with a high expression of STAT2 protein had poor overall survival (P=0.021) and progression-free survival (P=0.018). STAT2 was overexpressed in all the ovarian cancer cell lines tested, and A2780 cell lines showed the highest expression. Interference of STAT2 significantly suppressed the migration and invasiveness (P < 0.01) and lowered the expression level of EGFR in A2780 cells.

CONCLUSIONS

STAT2 is overexpressed in ovarian cancer. A high expression of STAT2 is associated with a poor prognosis of ovarian cancer patients. STAT2 may promote the metastasis of ovarian cancer by enhancing the expression of EGFR.