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Life sciences · Journal article
Cancer Plus · November 2, 2026
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Triple-negative breast cancer (TNBC) is aggressive and lacks effective targeted therapies. Using estrogen receptor (ER)-negative breast cancer as a proxy for TNBC, we explored circulating metabolite associations and downstream candidate genes. A two-sample Mendelian randomization (MR) analysis used large-scale metabolome genome-wide association study data (~1,400 metabolites). Candidate metabolites underwent Kyoto Encyclopedia of Genes and Genomes enrichment. Computationally predicted targets were intersected with common differentially expressed genes from three Gene Expression Omnibus datasets and Weighted Gene Co-expression Network Analysis modules. Least absolute shrinkage and selection operator-Cox and random survival forest prioritized genes in the Cancer Genome Atlas–TNBC. Single-cell RNA-seq (GSE176078) explored heterogeneity and pathways. MR identified 38 candidate metabolites nominally associated with ER-negative breast cancer risk, enriched in unsaturated fatty acid and arachidonic acid metabolism. Integration yielded 39 candidate genes, and survival-based machine learning prioritized KRAS, MGST3, FADS2, UGT8, IDO1, and SRC. Single-cell analysis showed higher FADS2 in a presumed malignant epithelial subpopulation (log2FC = 2.53, false discovery rate < 0.05), associated with cholesterol biosynthesis, sterol metabolism, and cell-cycle programs. These exploratory findings nominate abnormal circulating unsaturated fatty acid metabolism and FADS2 as candidate factors in ER-negative/TNBC biology. FADS2 is a candidate biomarker and potential target requiring TNBC-specific genetic, patient-aware single-cell, prognostic, and experimental validation.