Evaluating the significance of ECSCR in the diagnosis of ulcerative colitis and drug efficacy assessment.

ABSTRACT:

Background

The main challenge in diagnosing and treating ulcerative colitis (UC) has prompted this study to discover useful biomarkers and understand the underlying molecular mechanisms.

Methods

In this study, transcriptomic data from intestinal mucosal biopsies underwent Robust Rank Aggregation (RRA) analysis to identify differential genes. These genes intersected with UC key genes from Weighted Gene Co-expression Network Analysis (WGCNA). Machine learning identified UC signature genes, aiding predictive model development. Validation involved external data for diagnostic, progression, and drug efficacy assessment, along with ELISA testing of clinical serum samples.

Results

RRA integrative analysis identified 251 up-regulated and 211 down-regulated DEGs intersecting w

SUBMITTER: Feng B 

PROVIDER: S-EPMC11335526 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature