乳腺癌因其固有的分子异质性而在全球范围内持续构成重大医疗挑战。本综述深入评估了为了理解这种异质性而进行的分子分析，重点关注应用于传统批量和单细胞水平的多组学策略。基因组学研究极大地提升了我们对乳腺癌的理解，使其能够被归类为六个内在的分子亚型。除了基因组学，转录组学还深入了解了乳腺癌细胞的基因表达格局。它还促进了更精确的预测和预后模型的建立，从而丰富了乳腺癌个体化医学领域。传统转录组学和单细胞转录组学之间的比较确定了独特的基因表达模式，并促进了对细胞间变异的理解。蛋白质组学通过揭示复杂的蛋白质表达模式和其翻译后修饰，进一步了解了乳腺癌亚型。单细胞蛋白质组学的采用在这方面起到了重要作用，揭示了蛋白质调控和相互作用的复杂动态。尽管取得了这些进展，本综述强调了综合多组学策略的全面整合对于充分解读乳腺癌异质性的必要性。这种整合不仅确保了对乳腺癌分子复杂性的全面理解，还促进了个体化治疗策略的发展。

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.