Meng Hua, Zhang Shuangyi, Ling Min, Hu Yuanyuan, Xie Xiaohong
Department of Breast Surgery, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
The First Clinical College, Zhejiang Chinese Medical University, Hangzhou, China.
Transl Cancer Res. 2025 Feb 28;14(2):1190-1204. doi: 10.21037/tcr-24-1668. Epub 2025 Feb 24.
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).
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.
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.
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.
不饱和脂肪酸（UFA）的生物合成与乳腺癌（BC）的发生和发展有关。本研究旨在基于UFA相关基因（UFAG）开发BC的分子亚型和预后特征。
本研究整合了来自公共数据库的多组学和生存数据，以阐明基于UFAG的分子分类和风险概况。分别采用一致性聚类和Lasso Cox回归方法进行亚型鉴定和风险特征开发。使用CIBERSORT和ESTIMATE算法进行免疫微环境评估，同时通过pRRophetic和TIDE方法评估药物敏感性和对免疫治疗的反应。基因集富集分析增强了特征表征，随后构建并验证了列线图。
我们利用与预后相关的UFAG成功鉴定出两种预后显著不同的BC分子亚型。开发了一种由三个UFAG组成的预后特征[乙酰辅酶A酰基转移酶1（）、酰基辅酶A硫酯酶2（）和ELOVL脂肪酸延长酶2（）]，将患者分为高风险和低风险组，这两组在预后、临床病理特征、基因表达模式、免疫浸润特征、治疗敏感性和免疫治疗反应方面存在差异。该特征在训练和验证队列中均表现出强大的预后性能，与年龄一起成为独立的预测因子，并被整合到列线图中。决策曲线分析突出了列线图在预后预测方面优于其他因素。校准图和受试者工作特征曲线证实了其在BC预后评估中的优异性能。
UFAG的表达谱与BC预后相关，能够创建一个风险特征，有助于理解BC进展的分子机制。
