Frontiers in immunology · 2026
Multi-omics analysis of ST3GAL4-mediated lacto/neolacto glycosphingolipid metabolism reveals immune evasion and poor prognosis in TNBC.
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Zhang Yu, Wang Shuhan, Yu Xudong, Sun Kang, Wang Shengying
Аннотация
BACKGROUND: Triple-negative breast cancer (TNBC) is a highly aggressive subtype lacking effective targeted therapies. Increasing evidence highlights metabolic reprogramming as a hallmark of tumor progression and immune evasion. However, in this context, the specific metabolic-immune mechanisms underlying TNBC remain unclear.
METHODS: We performed an integrative multi-omics analysis combining bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics across TNBC and non-TNBC samples from TCGA, GEO, and 10X Genomics. Eighty-five KEGG metabolic pathways were profiled to identify TNBC-specific alterations. Machine learning models (Random Forest, XGBoost) were used to prioritize key metabolic genes. Immune infiltration was evaluated using CIBERSORT, ssGSEA, and ESTIMATE algorithms. Validation was conducted through immunohistochemistry (IHC) on 100 clinical samples from The First Affiliated Hospital of Anhui University Chinese Medicine.
RESULTS: The Lacto/Neolacto glycosphingolipid metabolism pathway was markedly activated in TNBC compared to adjacent and non-TNBC tissues, correlating with worse prognosis. Machine learning identified ST3GAL4 as the core enzyme within this pathway. High ST3GAL4 expression was associated with increased infiltration of regulatory T cells (Tregs) and M2 macrophages, reduced CD8+ T-cell activity, and enhanced epithelial-mesenchymal transition. Spatial transcriptomics confirmed localized enrichment of immunosuppressive cells in ST3GAL4-high regions. IHC validation demonstrated that ST3GAL4 overexpression in TNBC tissues predicts poor clinical outcomes.
CONCLUSIONS: ST3GAL4-driven glycosphingolipid metabolism promotes tumor immune evasion and aggressiveness in TNBC. This metabolic-immune coupling axis represents a potential therapeutic target, offering mechanistic rationale for combining metabolic and immune checkpoint blockade strategies.
METHODS: We performed an integrative multi-omics analysis combining bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics across TNBC and non-TNBC samples from TCGA, GEO, and 10X Genomics. Eighty-five KEGG metabolic pathways were profiled to identify TNBC-specific alterations. Machine learning models (Random Forest, XGBoost) were used to prioritize key metabolic genes. Immune infiltration was evaluated using CIBERSORT, ssGSEA, and ESTIMATE algorithms. Validation was conducted through immunohistochemistry (IHC) on 100 clinical samples from The First Affiliated Hospital of Anhui University Chinese Medicine.
RESULTS: The Lacto/Neolacto glycosphingolipid metabolism pathway was markedly activated in TNBC compared to adjacent and non-TNBC tissues, correlating with worse prognosis. Machine learning identified ST3GAL4 as the core enzyme within this pathway. High ST3GAL4 expression was associated with increased infiltration of regulatory T cells (Tregs) and M2 macrophages, reduced CD8+ T-cell activity, and enhanced epithelial-mesenchymal transition. Spatial transcriptomics confirmed localized enrichment of immunosuppressive cells in ST3GAL4-high regions. IHC validation demonstrated that ST3GAL4 overexpression in TNBC tissues predicts poor clinical outcomes.
CONCLUSIONS: ST3GAL4-driven glycosphingolipid metabolism promotes tumor immune evasion and aggressiveness in TNBC. This metabolic-immune coupling axis represents a potential therapeutic target, offering mechanistic rationale for combining metabolic and immune checkpoint blockade strategies.