BACKGROUND

The biosynthesis of unsaturated fatty acids (UFAs) has been implicated in the onset and advancement of breast cancer (BC). This study aimed to develop molecular subtypes and prognostic signatures for BC based on UFA-related genes (UFAGs).

METHODS

This study integrates multi-omics and survival data from public databases to elucidate molecular classifications and risk profiles based on UFAGs. Consensus clustering and Lasso Cox regression methodologies are employed for subtype identification and risk signature development, respectively. Immune microenvironment assessment is conducted using CIBERSORT and ESTIMATE algorithms, while drug sensitivity and response to immunotherapy are evaluated via pRRophetic and TIDE methods. Gene set enrichment analysis augments signature characterization, followed by nomogram construction and validation.

RESULTS

We successfully identified two distinct BC molecular subtypes with significantly different prognoses utilizing UFAGs correlated with outcomes. A prognostic signature comprising three UFAGs [acetyl-CoA acyltransferase 1 (), acyl-CoA thioesterase 2 (), and ELOVL fatty acid elongase 2 ()] is developed, stratifying patients into high- and low-risk groups exhibiting divergent outcomes, clinicopathological traits, gene expression patterns, immune infiltration profiles, therapeutic susceptibility, and immunotherapy responses. The signature demonstrates robust prognostic performance in both training and validation cohorts, emerging as an independent predictor alongside age, which is integrated into a nomogram. Decision curve analysis highlights the nomogram's superiority over other factors in prognosis prediction. Calibration plots and receiver operating characteristic curves affirm its excellent performance in BC prognosis assessment.

CONCLUSIONS

Expression profiles of UFAGs are associated with BC prognosis, enabling the creation of a risk signature with implications for understanding the molecular mechanisms underlying BC progression.