Integration of machine learning found SAT1 as a prognostic biomarker for acute pancreatitis, suggesting therapeutic targets.
Background Ferroptosis and immune responses are catching more and more attention in inflammatory diseases. However, the specific function and mechanism of the popular ferroptosis‐related gene SAT1 in acute pancreatitis (AP) still remain unknown. Methods Differentially expressed genes (DEGs) and the Weighted Gene Co‐Expression Network Analysis (WGCNA) were integrated to screen the core gene set related to AP. The characteristic gene was identified through three machine learning algorithms (LASSO, SVM‐REF, and RF). Experimental approaches were performed to validate the findings by using qRT‐PCR and immunohistochemistry (IHC). Results Machine learning combined with bioinformatics determined that the ferroptosis gene SAT1 was the key regulatory gene of AP. The expression level of SAT1 was positively correlated with the severity of AP ( p < 0.05), which was also involved in immune functions. Experiments in vivo and in vitro validated that SAT1 was significantly upregulated in murine AP models ( p < 0.01). Knockdown of SAT1 could alleviate inflammation responses by reducing IL1 β and IL6, especially TNF α . Conclusion SAT1 is elevated in AP, serving as a potential diagnostic and prognostic biomarker. Down regulation of SAT1 can decrease the release of inflammatory factors. We identified SAT1 as a potential therapeutic target for AP.
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Zhou et al. (2025) studied this question.
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