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Abstract
Ulcerative colitis (UC) is an autoimmune inflammatory disorder of the gastrointestinal tract. Programmed cell death (PCD), including PANoptosis and autophagy, plays roles in inflammation and immunity. This study aimed to investigate the molecular signature and immune landscape of the PANoptosis- and autophagy-related differentially expressed genes (DEGs) in UC. Analyzing UC dataset GSE206285 yielded DEGs. Differentially expressed PANoptosis- and autophagy-related genes were identified using DEGs and relevant gene collections. Functional and pathway enrichment analyses were conducted. A protein-protein interaction (PPI) network was established to identify hub genes. TRRUST database predicted transcription factors (TFs), pivotal miRNAs, and drugs interacting with hub genes. Immune infiltration analysis, UC-associated single-cell sequencing data analysis, and construction of a competing endogenous RNA (ceRNA) network for hub genes were conducted. Machine learning identified key candidate genes, evaluated for diagnostic value via receiver operating characteristic (ROC) curves. A UC mice model verified expression of key candidate genes. Identifying ten PANoptosis-related hub DEGs and four autophagy-related hub DEGs associated them with cell chemotaxis, wound healing and positive MAPK cascade regulation. Immune infiltration analysis revealed increased immunocyte infiltration in UC patients, with hub genes closely linked to various immune cell infiltrations. Machine learning identified five key candidate genes, TIMP1, TIMP2, TIMP3, IL6, and CCL2, with strong diagnostic performance. At the single-cell level, these genes exhibited high expression in inflammatory fibroblasts (IAFs). They showed significant expression differences in the colon mucosa of both UC patients and UC mice model. This study identified and validated novel molecular signatures associated with PANoptosis and autophagy in UC, potentially influencing immune dysregulation and wound healing, thus opening avenues for future research and therapeutic interventions.
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