Breast cancer continues to pose a significant healthcare challenge worldwide for its inherent molecular heterogeneity. This review offers an in-depth assessment of the molecular profiling undertaken to understand this heterogeneity, focusing on multi-omics strategies applied both in traditional bulk and single-cell levels. Genomic investigations have profoundly informed our comprehension of breast cancer, enabling its categorization into six intrinsic molecular subtypes. Beyond genomics, transcriptomics has rendered deeper insights into the gene expression landscape of breast cancer cells. It has also facilitated the formulation of more precise predictive and prognostic models, thereby enriching the field of personalized medicine in breast cancer. The comparison between traditional and single-cell transcriptomics has identified unique gene expression patterns and facilitated the understanding of cell-to-cell variability. Proteomics provides further insights into breast cancer subtypes by illuminating intricate protein expression patterns and their post-translational modifications. The adoption of single-cell proteomics has been instrumental in this regard, revealing the complex dynamics of protein regulation and interaction. Despite these advancements, this review underscores the need for a holistic integration of multiple ‘omics’ strategies to fully decipher breast cancer heterogeneity. Such integration not only ensures a comprehensive understanding of breast cancer’s molecular complexities, but also promotes the development of personalized treatment strategies.
乳腺癌因其固有的分子异质性，持续构成全球性的重大健康挑战。本综述深入评估了为理解这种异质性所进行的分子谱分析，重点关注传统群体水平和单细胞水平应用的多组学策略。基因组学研究极大地深化了我们对乳腺癌的认识，使其得以划分为六种内在分子亚型。除基因组学外，转录组学为乳腺癌细胞的基因表达图谱提供了更深入的见解，并促进了更精准的预测和预后模型的构建，从而丰富了乳腺癌个体化医疗领域。传统与单细胞转录组学的比较揭示了独特的基因表达模式，促进了对细胞间变异性的理解。蛋白质组学通过阐明复杂的蛋白质表达模式及其翻译后修饰，为乳腺癌亚型提供了进一步解析。单细胞蛋白质组学的应用在这方面发挥了关键作用，揭示了蛋白质调控与相互作用的复杂动态。尽管取得了这些进展，本综述强调需要全面整合多种组学策略以完整解析乳腺癌异质性。这种整合不仅能确保对乳腺癌分子复杂性的全面理解，还将推动个体化治疗策略的发展。
肿瘤(癌症)患者之家