Identification of subtypes and biomarkers associated with disulfidptosis-related ferroptosis in ulcerative colitis

Abstract Background Disulfidptosis and ferroptosis are different programmed cell death modes, which are closely related to the development of a variety of diseases, but the relationship between them and ulcerative colitis (UC) is still unclear. Therefore, our study aimed to explore the molecular subtypes and biomarkers associated with disulfidptosis-related ferroptosis (DRF) in UC. Methods We used Pearson analysis to identify DRF genes. Then, we classified 140 UC samples into different subtypes based on the DRF genes and explored the biological and clinical characteristics between them. Next, the hub genes were identified by differential analysis and WGCNA algorithms, and three machine learning algorithms were used to screen biomarkers for UC from hub genes. In addition, we analyzed the relationship between biomarkers of immune cells and transcription factors and predicted natural compounds that might be used to treat UC. Finally, we further verified the reliability of the markers by RT-qPCR experiments. Results 118 DRF genes were identified using Pearson analysis. Based on the expression level of the DRF genes, we classified UC patients into C1 and C2 subtypes, with significant differences in the abundance of immune infiltration and disease activity between the two subtypes. The machine learning algorithms identified three biomarkers, including XBP1, FH, and MAP3K5. Further analyses revealed that the three biomarkers were closely associated with a variety of immune cells and transcription factors. In addition, six natural compounds corresponding to the biomarkers were predicted, which may contribute to the effective treatment of UC. Finally, the expression trends of XBP1, FH, and MAP3K5 in animal experiments were consistent with the results of bioinformatics analysis. Conclusion In this study, we systematically elucidated the role of DRF genes in the development of UC, and identified three potential biomarkers, providing a new idea for the diagnosis and treatment of UC.