Comprehensive bioinformatic analysis and experimental validation identify MT1M and MT1X as key metallothioneins in BC pathogenesis.
[BACKGROUND] Metallothioneins (MTs) are crucial metal-binding proteins involved in cellular zinc homeostasis and oxidative stress response.
APA
Su L, Wen S, et al. (2026). Comprehensive bioinformatic analysis and experimental validation identify MT1M and MT1X as key metallothioneins in BC pathogenesis.. Journal of trace elements in medicine and biology : organ of the Society for Minerals and Trace Elements (GMS), 94, 127832. https://doi.org/10.1016/j.jtemb.2026.127832
MLA
Su L, et al.. "Comprehensive bioinformatic analysis and experimental validation identify MT1M and MT1X as key metallothioneins in BC pathogenesis.." Journal of trace elements in medicine and biology : organ of the Society for Minerals and Trace Elements (GMS), vol. 94, 2026, pp. 127832.
PMID
41666661
Abstract
[BACKGROUND] Metallothioneins (MTs) are crucial metal-binding proteins involved in cellular zinc homeostasis and oxidative stress response. However, the role of metallothionein-related genes (MRGs) in breast cancer (BC) pathogenesis and their potential as therapeutic targets remains poorly understood.
[METHODS] We integrated two BC datasets, GSE42568 and GSE29044, to identify differentially expressed MRGs. Consensus clustering was applied to classify BC subtypes based on MRGs expression patterns. GSVA evaluated pathway activities between subtypes. LASSO regression, Random Forest, and Logistic Regression were employed to identify core MRGs. A predictive nomogram was constructed and validated using ROC curves, calibration curves, and decision curve analysis. Single-cell RNA sequencing and spatial transcriptomic analyses were performed to characterize core MRGs expression patterns. Finally, in vitro experiments, including PCR, western blot, CCK-8, migration, and invasion assays, were conducted for validation.
[RESULTS] Among 62 MRGs analyzed, 30 showed differential expression in BC. Consensus clustering revealed two MTs subtypes with distinct molecular signatures. Functional enrichment analysis indicated significant pathways, including Wnt signaling and zinc ion homeostasis. GSVA highlighted variations in metal ion homeostasis and immune responses between subtypes. Two core MRGs, MT1M and MT1X, were identified through machine learning approaches, both significantly downregulated in BC tissues. The constructed nomogram demonstrated excellent predictive performance. Single-cell analysis revealed cell-type-specific expression patterns, while pathway analysis showed differential activation of oncogenic signaling cascades. Experimental validation confirmed the downregulation of MT1M and MT1X in BC tissues at mRNA and protein levels. Functional assays demonstrated that overexpression of MT1M or MT1X suppressed BC cell viability, migration, and invasion.
[CONCLUSION] Our study establishes MRGs, particularly the core genes MT1M and MT1X, as crucial players in BC heterogeneity and pathogenesis. They serve as promising diagnostic biomarkers and potential therapeutic targets, with their tumor-suppressive roles likely mediated through the modulation of key oncogenic signaling pathways.
[METHODS] We integrated two BC datasets, GSE42568 and GSE29044, to identify differentially expressed MRGs. Consensus clustering was applied to classify BC subtypes based on MRGs expression patterns. GSVA evaluated pathway activities between subtypes. LASSO regression, Random Forest, and Logistic Regression were employed to identify core MRGs. A predictive nomogram was constructed and validated using ROC curves, calibration curves, and decision curve analysis. Single-cell RNA sequencing and spatial transcriptomic analyses were performed to characterize core MRGs expression patterns. Finally, in vitro experiments, including PCR, western blot, CCK-8, migration, and invasion assays, were conducted for validation.
[RESULTS] Among 62 MRGs analyzed, 30 showed differential expression in BC. Consensus clustering revealed two MTs subtypes with distinct molecular signatures. Functional enrichment analysis indicated significant pathways, including Wnt signaling and zinc ion homeostasis. GSVA highlighted variations in metal ion homeostasis and immune responses between subtypes. Two core MRGs, MT1M and MT1X, were identified through machine learning approaches, both significantly downregulated in BC tissues. The constructed nomogram demonstrated excellent predictive performance. Single-cell analysis revealed cell-type-specific expression patterns, while pathway analysis showed differential activation of oncogenic signaling cascades. Experimental validation confirmed the downregulation of MT1M and MT1X in BC tissues at mRNA and protein levels. Functional assays demonstrated that overexpression of MT1M or MT1X suppressed BC cell viability, migration, and invasion.
[CONCLUSION] Our study establishes MRGs, particularly the core genes MT1M and MT1X, as crucial players in BC heterogeneity and pathogenesis. They serve as promising diagnostic biomarkers and potential therapeutic targets, with their tumor-suppressive roles likely mediated through the modulation of key oncogenic signaling pathways.
MeSH Terms
Metallothionein; Humans; Breast Neoplasms; Computational Biology; Female; Cell Line, Tumor; Cell Movement; Gene Expression Regulation, Neoplastic
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