Construction of a prognostic signature for breast cancer based on genes involved in unsaturated fatty acid biosynthesis
Year: 2025
Type: article
Abstract: 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: )] 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.
Source: Translational Cancer Research
DOI: 10.21037/tcr-24-1668
Authors: Hua Meng, Shuangyi Zhang, Min Ling, Yuanyuan Hu, Xiaohong Xie
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W4408039083