Cuproptosis has been reported to affect a variety of diseases. Therefore, we aimed to examine the role of cuproptosis-related genes in active ulcerative colitis (UC). We acquired 2 datasets of active UC from the Gene Expression Omnibus database and created immune cell infiltrations to research immune cell dysregulation. Based on the cuproptosis gene set and differentially expressed genes (DEGs), we identified the differentially expressed genes of cuproptosis (CuDEGs). We then used 2 machine learning methods to screen hub CuDEGs. Subsequently, we performed validation on additional datasets and investigated the relationship between hub CuDEGs and drug treatments. Thirty-five controls with inactive UC and 90 patients with active UC were obtained from the training sets. A total of 9157 DEGs and 27 CuDEGs were identified, respectively. Immune cell infiltration analysis revealed that patients with active UC exhibited higher levels of activated dendritic cells and neutrophils as well as lower levels of CD8+ T cells, regulatory T cells (Tregs), and macrophage M2. A six-gene cuproptosis signature was identified using machine learning algorithms. We further validated that the 6 hub CuDEGs showed a strong correlation with active UC and acted as cuproptosis-related biomarkers of active UC. Moreover, the expression of ATOX1 was downregulated, and SUMF1, MT1G, ATP7B, FDX1, and LIAS expression was upregulated in the colonic mucosa of active UC patients who responded to golimumab or vedolizumab therapy. With the exception of ATP7B, the expression patterns of hub CuDEGs before and after infliximab treatment of patients with active UC were similar to those of golimumab and vedolizumab. Cuproptosis and active UC have a complex relationship, as illustrated in our study. ATOX1, SUMF1, MT1G, ATP7B, FDX1, and LIAS are cuproptosis-related hub genes of active UC. Our study opens new avenues for investigating UC progression and developing novel therapeutic potential targets for the disease.