Eur J Med Res. 2025 Nov 11;30(1):1107. doi: 10.1186/s40001-025-03338-0.
ABSTRACT
BACKGROUND: Solute carrier (SLC) is involved in diverse malignancies. This research analyzed the involvement of SLC-related genes in acute myeloid leukemia (AML).
METHODS: This study analyzed transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), with SLC-related genes from GeneCards. SLC scores were obtained using single-sample gene set enrichment analysis (ssGSEA), and key modules were identified with weighted gene co-expression network analysis (WGCNA). Functional enrichment was performed using the clusterProfiler package. Prognostic genes were screened by univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression, and a RiskScore model was built. Tumor immune microenvironment features were assessed by Gene Set Variation Analysis (GSVA) and the ESTIMATE algorithm. Mutation profiles and pathways were compared between risk groups, and hub gene expression and function were validated by quantitative real-time polymerase chain reaction (qRT-PCR) and cell counting kit-8 (CCK-8) assay.
RESULTS: This study identified the turquoise module significantly associated with the SLC score using WGCNA, and enrichment analysis showed immune-related pathways. A RiskScore model (FERMT3, CLCN5, DUSP7, and CSRP1) was constructed. High-risk patients showed significantly worse survival, and a stronger prognostic efficacy was seen in the model proposed in this study with an overall C-index of 0.626. Immune profiling revealed higher immune cell infiltration and checkpoint expression in the high-risk group. Additionally, the genes with higher mutation rates in the high-risk group were DNMT3A, RUNX1, and NPM1. The RiskScore showed significant positive correlations with multiple oncogenic signaling pathways, such as EGFR and MAPK. In-vitro cell assays demonstrated that FERMT3 and CLCN5 were significantly upregulated in AML cell lines, and gene knockout significantly inhibits cell viability.
CONCLUSION: Overall, these SLC-related genes may have predictive relevance in AML, and our study identified some promising targets for AML.
PMID:41219979 | DOI:10.1186/s40001-025-03338-0
