Dataset Information

The Lnc-ENST00000602558/IGF1 axis as a predictor of response to treatment with tripterygium glycosides in rheumatoid arthritis patients.

ABSTRACT:

Aims

Growing clinical evidence suggests that not all patients with rheumatoid arthritis (RA) benefit to the same extent by treatment with tripterygium glycoside (TG), which highlights the need to identify RA-related genes that can be used to predict drug responses. In addition, single genes as markers of RA are not sufficiently accurate for use as predictors. Therefore, there is a need to identify paired expression genes that can serve as biomarkers for predicting the therapeutic effects of TG tablets in RA.

Methods

A total of 17 pairs of co-expressed genes were identified as candidates for predicting an RA patient's response to TG therapy, and genes involved in the Lnc-ENST00000602558/GF1 axis were selected for that purpose. A partial-least-squares (PLS)-based model was constructed based on the expression levels of Lnc-ENST00000602558/IGF1 in peripheral blood. The model showed high efficiency for predicting an RA patient's response to TG tablets.

Results

Our data confirmed that genes co-expressed in the Lnc-ENST00000602558/IGF1 axis mediate the efficacy of TG in RA treatment, reduce tumor necrosis factor-α induced IGF1 expression, and decrease the inflammatory response of MH7a cells.

Conclusion

We found that genes expressed in the Lnc-ENST00000602558/IGF1 axis may be useful for identifying RA patients who will not respond to TG treatment. Our findings provide a rationale for the individualized treatment of RA in clinical settings.

SUBMITTER: Gao Y

PROVIDER: S-EPMC10790680 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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Publications

The Lnc-ENST00000602558/IGF1 axis as a predictor of response to treatment with tripterygium glycosides in rheumatoid arthritis patients.

Gao Yang Y Wang Xiaoyue X Gao Yanfeng Y Bai Jian J Zhao Yanpeng Y Wang Renyi R Wang Hanzhou H Zhu Guangzhao G Wang Xixi X Han Xiaochen X Zhang Yanqiong Y Wang Hailong H

Immunity, inflammation and disease 20240101 1

<h4>Aims</h4>Growing clinical evidence suggests that not all patients with rheumatoid arthritis (RA) benefit to the same extent by treatment with tripterygium glycoside (TG), which highlights the need to identify RA-related genes that can be used to predict drug responses. In addition, single genes as markers of RA are not sufficiently accurate for use as predictors. Therefore, there is a need to identify paired expression genes that can serve as biomarkers for predicting the therapeutic effects ...[more]

PMID: 38270302

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Project description:Rheumatoid arthritis (RA), a chronic inflammatory synovitis systemic disease, can lead to joint deformities, loss of function and even death. The pathogenesis of RA may be related to genetics, infection and/or sex hormones; however, detailed accounts of the molecular mechanisms underlying its pathogenesis are lacking. In the present study, the synovial tissues of patients with RA and healthy individuals were analyzed to identify the pathogenic signaling pathways and key candidate genes involved in RA. Gene Ontology (GO), pathway enrichment and protein-protein interaction analysis were further used to identify the differentially expressed genes (DEGs) and their potential roles in RA. Molecular docking was used to screen the potential candidate drugs for management of RA. Small interfering RNA was used for knockdown of the CD2 protein. A Cell Counting Kit-8 assay was used to detect the proliferation of cells. Changes in the levels of inflammatory cytokines were detected using ELISA. A total of 279 DEGs were identified in RA; amongst these genes, 166 and 113 were upregulated and downregulated, respectively. GO analysis revealed that the upregulated DEGs were primarily enriched in the activation of the immune and adaptive immune responses, as well as the inflammatory response. The T-cell surface antigen CD2 (CD2) was identified as the most important hub gene by selecting the most important module from the protein-protein interaction network. Knockout of CD2 reduced the damaging effects of TNF-α on synovial cells. Through in situ screening using computer-aided drug design, the triptolide derivative (5R)-5-hydroxytriptolide (LLDT-8) was determined to have the highest docking score based on the CD2 protein structure. Cell experiments showed that LLDT-8 could inhibit the expression of CD2. Cell proliferation and inflammatory cytokine assays confirmed that CD2 was the direct target of LLDT-8. Together, the results of the present study determined factors involved in the pathogenesis of RA and the important role of CD2 in this process by analyzing the DEGs in the RA process. LLDT-8 inhibited CD2 and may thus be used to treat RA. These candidate genes and signaling pathways may serve as potential targets for the clinical treatment of RA.

Project description:BackgroundExtracts of the medicinal plant Tripterygium wilfordii Hook F (TwHF) have been used in China for centuries to treat a spectrum of inflammatory diseases.ObjectiveTo compare the benefits and side effects of TwHF extract with those of sulfasalazine for the treatment of active rheumatoid arthritis.DesignRandomized, controlled trial. A computer-generated code with random, permuted blocks was used to assign treatment.Setting2 U.S. academic centers (National Institutes of Health, Bethesda, Maryland, and University of Texas, Dallas, Texas) and 9 rheumatology subspecialty clinics (in Dallas and Austin, Texas; Tampa and Fort Lauderdale, Florida; Arlington, Virginia; Duncanville, Pennsylvania; Wheaton and Greenbelt, Maryland; and Lansing, Michigan).Patients121 patients with active rheumatoid arthritis and 6 or more painful and swollen joints.InterventionTwHF extract, 60 mg 3 times daily, or sulfasalazine, 1 g twice daily. Patients could continue stable doses of oral prednisone or nonsteroidal anti-inflammatory drugs but had to stop taking disease-modifying antirheumatic drugs at least 28 days before randomization.MeasurementsThe primary outcome was the rate of achievement of 20% improvement in the American College of Rheumatology criteria (ACR 20) at 24 weeks. Secondary end points were safety; radiographic scores of joint damage; and serum levels of interleukin-6, cholesterol, cortisol, and adrenocorticotropic hormone.ResultsOutcome data were available for only 62 patients at 24 weeks. In a mixed-model analysis that imputed data for patients who dropped out, 65.0% (95% CI, 51.6% to 76.9%) of the TwHF group and 32.8% (CI, 21.3% to 46.0%) of the sulfasalazine group met the ACR 20 response criteria (P=0.001). Patients receiving TwHF also had significantly higher response rates for ACR 50 and ACR 70 in mixed-model analyses. Analyses of only completers showed similar significant differences between the treatment groups. Significant improvement was demonstrated in all individual components of the ACR response, including the Health Assessment Questionnaire disability score. Interleukin-6 levels rapidly and significantly decreased in the TwHF group. Although not statistically significant, radiographic progression was lower in the TwHF group. The frequency of adverse events was similar in both groups.LimitationsOnly 62% and 41% of patients continued receiving TwHF extract and sulfasalazine, respectively, during the 24 weeks of the study. Long-term outcome data were not collected on participants who discontinued treatment.ConclusionIn patients who continued treatment for 24 weeks and could also use stable oral prednisone and nonsteroidal anti-inflammatory drugs, attainment of the ACR 20 response criteria was significantly greater with TwHF extract than with sulfasalazine.

Dataset Information

The Lnc-ENST00000602558/IGF1 axis as a predictor of response to treatment with tripterygium glycosides in rheumatoid arthritis patients.

Aims

Methods

Results

Conclusion

Publications

The Lnc-ENST00000602558/IGF1 axis as a predictor of response to treatment with tripterygium glycosides in rheumatoid arthritis patients.

Similar Datasets

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