Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China; Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Fudan University, Shanghai 200032, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China.
Department of Breast Surgery, Fudan University Shanghai Cancer Center, Shanghai 200032, China; Key Laboratory of Breast Cancer in Shanghai, Fudan University Shanghai Cancer Center, Fudan University, Shanghai 200032, China.
Mol Ther. 2021 Jul 7;29(7):2350-2365. doi: 10.1016/j.ymthe.2021.03.003. Epub 2021 Mar 5.
An emerging view regarding cancer metabolism is that it is heterogeneous and context-specific, but it remains to be elucidated in breast cancers. In this study, we characterized the energy-related metabolic features of breast cancers through integrative analyses of multiple datasets with genomics, transcriptomics, metabolomics, and single-cell transcriptome profiling. Energy-related metabolic signatures were used to stratify breast tumors into two prognostic clusters: cluster 1 exhibits high glycolytic activity and decreased survival rate, and the signatures of cluster 2 are enriched in fatty acid oxidation and glutaminolysis. The intertumoral metabolic heterogeneity was reflected by the clustering among three independent large cohorts, and the complexity was further verified at the metabolite level. In addition, we found that the metabolic status of malignant cells rather than that of nonmalignant cells is the major contributor at the single-cell resolution, and its interactions with factors derived from the tumor microenvironment are unanticipated. Notably, among various immune cells and their clusters with distinguishable metabolic features, those with immunosuppressive function presented higher metabolic activities. Collectively, we uncovered the heterogeneity in energy metabolism using a classifier with prognostic and therapeutic value. Single-cell transcriptome profiling provided novel metabolic insights that could ultimately tailor therapeutic strategies based on patient- or cell type-specific cancer metabolism.
关于癌症代谢的一个新观点是，它具有异质性和特定于上下文的特点，但在乳腺癌中仍有待阐明。在这项研究中，我们通过整合基因组学、转录组学、代谢组学和单细胞转录组谱分析的多个数据集，对乳腺癌的能量相关代谢特征进行了表征。能量相关的代谢特征用于将乳腺癌肿瘤分为两个预后聚类：聚类 1 表现出高糖酵解活性和降低的生存率，聚类 2 的特征富含脂肪酸氧化和谷氨酰胺分解。三个独立的大型队列的聚类反映了肿瘤间的代谢异质性，在代谢物水平上进一步验证了这种复杂性。此外，我们发现恶性细胞的代谢状态而不是非恶性细胞的代谢状态是单细胞分辨率的主要贡献者，其与来自肿瘤微环境的因素的相互作用是出乎意料的。值得注意的是，在具有可区分代谢特征的各种免疫细胞及其簇中，具有免疫抑制功能的细胞表现出更高的代谢活性。总的来说，我们使用具有预后和治疗价值的分类器揭示了能量代谢的异质性。单细胞转录组谱分析提供了新的代谢见解，最终可以根据患者或细胞类型特异性的癌症代谢来定制治疗策略。
