FTO-CHRM3 axis regulates multiple myeloma progression: a machine learning-based identification

FTO-CHRM3轴调控多发性骨髓瘤进展:基于机器学习的识别

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Abstract

BACKGROUND: Fat Mass and Obesity-Associated (FTO) is linked to multiple myeloma (MM) progression, but its action mechanisms are poorly understood. METHODS: Machine learning and correlation analysis identified genes with consistent expression patterns as FTO-associated genes. Additionally, the expression levels of FTO and its associated genes in MM tissues were validated through immunohistochemistry. The impact of FTO-associated genes expression on the immune microenvironment of MM was assessed through immune infiltration analysis. Single-cell RNA sequencing (scRNA-seq) elucidated cellular expression patterns. RESULTS: FTO was found to be significantly upregulated in MM and associated with poor prognosis. Four potential FTO-associated genes (CHRM3, GINS3, RRM2, and SHCBP1) were identified. Correlation and immunohistochemical analyses further focused the FTO-CHRM3 axis. Functional enrichment analysis unveiled that FTO and CHRM3 were involved in "DNA replication" and "cell cycle". The infiltration of M2 macrophages and eosinophils were altered in high FTO/CHRM3 expression groups. ScRNA-seq highlighted the monocyte-specific expression of SLC8A1 in the calcium signaling pathway in MM. CONCLUSION: The FTO-CHRM3 axis contributes to MM progression via calcium signaling pathway dysregulation, and the exploration of its underlying mechanisms provides insights for targeted MM interventions.

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