Integrated bulk and single-cell transcriptomic analysis reveals a tryptophan metabolism-driven prognostic signature and therapeutic landscape in triple- negative breast cancer

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Abstract

Background: Triple-negative breast cancer (TNBC) is an aggressive malignancy with limited therapeutic options and poor prognosis. The kynurenine pathway of tryptophan metabolism contributes to an immunosuppressive tumor microenvironment (TME); however, its prognostic significance and molecular mechanisms in TNBC require further multi-omics characterization. Methods: Bulk and single-cell RNA-seq datasets were obtained from public repositories. Differentially expressed tryptophan metabolism-related genes were identified and screened via univariate Cox regression. Nine machine learning algorithms were trained using 5-fold cross-validation, with SHAP analysis applied for model interpretability. A prognostic risk model was developed, externally validated, and further analyzed for immune infiltration, pathway activity, and AI-driven drug screening. ScRNA-seq data were used to identify key cell populations and differentiation trajectories. Results: Among 48 candidates, Random Survival Forest demonstrated optimal performance and was selected to construct an eight-gene prognostic signature (EIF4EBP1, NRTN, COL9A3, TRIM63, FABP7, ALAD, H4C13, PLAU). The model effectively stratified patients into high- and low-risk groups with significantly distinct survival outcomes across multiple cohorts. High-risk patients exhibited increased infiltration of central memory CD8+ T cells, immature dendritic cells, and neutrophils, along with upregulated ABC transporter and endocytosis pathways. AI-driven screening identified omega-3-carboxylic acids and sucralfate as potential therapeutics. ScRNA-seq revealed that prognostic markers were predominantly expressed in T cells, B cells, macrophages, and stromal cells, with dynamic changes along differentiation trajectories. Conclusion: This study establishes a novel tryptophan metabolism-derived prognostic signature for TNBC, providing insights into TME remodeling and identifying potential therapeutic strategies for high-risk patients.

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