BACKGROUND: Pituitary neuroendocrine tumors (PitNETs) have different cell types and levels of growth. We do not fully understand why they grow so much. Cuproptosis is a new way that copper kills cells and it is important in cancer. But, we do not know how it works in PitNETs yet. METHODS: We used several methods like bulk and single-cell sequencing with machine learning to investigate cuproptosis in PitNETs. We used Weighted Gene Co-expression Network Analysis (WGCNA) and random forest to find important genes. Then, we did tests in the lab to see how these genes work. RESULTS: Analysis of cuproptosis-related genes (CRGs) revealed significant differences in expression and immune landscapes between invasive and non-invasive PitNETs. We established CRG-based molecular subtypes and a high-performance predictive model for tumor invasiveness. Notably, regulatory factor X1 (RFX1) was identified and validated as a key regulator that suppresses tumor growth and sensitizes cells to cuproptosis. These results highlight the clinical relevance of cuproptosis in PitNET progression and suggest RFX1 as a potential therapeutic target. CONCLUSION: This study establishes a single-cell-based molecular landscape of PitNETs and uncovers RFX1-mediated cuproptosis as a key suppressive mechanism of tumor progression. These findings not only deepen the understanding of PitNET heterogeneity but also propose RFX1 as a promising therapeutic target for PitNETs.
Yang et al. (Tue,) studied this question.