Abstract
To analyze the role of disulfidptosis in ulcerative colitis (UC), large-scale datasets combined with weighted gene co-expression network analysis (WGCNA) and machine learning were utilized and analyzed. When the hub genes that are associated with UC disease phenotypes and have predictive performance were identified, immune cell infiltration and the CeRNA network were constructed, the role of hub genes in UC pathogenies and biotherapy were investigated, and molecular docking studies and mice-verified tests were carried out to further explore the potential core genes and potential target. Finally, we found 21 DRGs involved in UC pathogenesis, including SLC3A2, FLNA, CAPZB, TLN1, RPN1, etc. Moreover, SLC3A2, TLN1, and RPN1 show a notable correlation with UC inflammatory state, and the expression of DRGs is closely related to the response to UC biotherapy. Our study suggests that disulfidptosis plays a crucial role in the pathogenesis and disease progression of UC. Higher expression of DRGs is commonly observed in moderate to severe UC patients, which may also affect their response to biologic therapies. Among the identified genes, SLC3A2 stands out, providing new insights into the underlying mechanisms of UC and potentially serving as a novel therapeutic target for the treatment of UC.
Keywords:
SLC3A2; ceRNA network; disulfidptosis; integrated analysis; machine learning; small molecule agents prediction; ulcerative colitis.