A novel gene-expression-signature-based model for prediction of response to Tripterysium glycosides tablet for rheumatoid arthritis patients.

ABSTRACT:

Background

Approximately 30% of rheumatoid arthritis (RA) patients treated with Tripterysium glycosides (TG) tablets fail to achieve clinical improvement, implying the essentiality of predictive biomarkers and tools. Herein, we aimed to identify possible biomarkers predictive of therapeutic effects of TG tablets in RA.

Methods

Gene expression profile in peripheral blood mononuclear cells obtained from a discovery cohort treated with TG tablets was detected by Affymetrix EG1.0 arrays. Then, a list of candidate gene biomarkers of response to TG tablets were identified by integrating differential expression data analysis and gene signal transduction network analysis. After that, a partial-least-squares (PLS) model based on the expression levels of the candidate gene biomarkers

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC6032531 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature