Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40131 Bologna, Italy.
Int J Mol Sci. 2023 Aug 11;24(16):12690. doi: 10.3390/ijms241612690.
Breast cancer (BC) has yielded approximately 2.26 million new cases and has caused nearly 685,000 deaths worldwide in the last two years, making it the most common diagnosed cancer type in the world. BC is an intricate ecosystem formed by both the tumor microenvironment and malignant cells, and its heterogeneity impacts the response to treatment. Biomedical research has entered the era of massive omics data thanks to the high-throughput sequencing revolution, quick progress and widespread adoption. These technologies-liquid biopsy, transcriptomics, epigenomics, proteomics, metabolomics, pharmaco-omics and artificial intelligence imaging-could help researchers and clinicians to better understand the formation and evolution of BC. This review focuses on the findings of recent multi-omics-based research that has been applied to BC research, with an introduction to every omics technique and their applications for the different BC phenotypes, biomarkers, target therapies, diagnosis, treatment and prognosis, to provide a comprehensive overview of the possibilities of BC research.
在过去两年中，乳腺癌（BC）在全球范围内导致约 226 万例新发病例和近 68.5 万人死亡，使其成为世界上最常见的诊断癌症类型。BC 是由肿瘤微环境和恶性细胞组成的复杂生态系统，其异质性影响治疗反应。由于高通量测序革命、快速进展和广泛采用，生物医学研究已经进入了大规模组学数据的时代。液体活检、转录组学、表观基因组学、蛋白质组学、代谢组学、药物基因组学和人工智能成像等技术可以帮助研究人员和临床医生更好地了解 BC 的形成和演变。本综述重点介绍了最近应用于 BC 研究的基于多组学的研究结果，介绍了每种组学技术及其在不同 BC 表型、生物标志物、靶向治疗、诊断、治疗和预后中的应用，为 BC 研究的可能性提供了全面的概述。
