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Breast Cancer: Molecular Pathogenesis, Targeted Therapy, Screening, and Prevention

乳腺癌 靶向治疗 精密医学 医学 危险分层 个性化医疗 癌症 生物信息学 机制(生物学) 表观遗传学 计算生物学 曲妥珠单抗 工程伦理学 癌症治疗
作者
Huijun Lei,Jinzhen Fu,Wei Gu,Hongjin Qiao,H. Henry Guo,Z Chen,San Ming Wang,Tianhui Chen
出处
期刊:MedComm [Wiley]
卷期号:7 (1): e70560-e70560 被引量:3
标识
DOI:10.1002/mco2.70560
摘要

Breast cancer is the most common cancer and the leading cause of cancer-related death among women worldwide. Advances in molecular biology, high-throughput sequencing, and integrative-omics have deepened the understanding of its heterogeneity by clarifying mechanisms linked to genetic susceptibility, epigenetic regulation, oncogenic signaling, and immune evasion. Although those developments have driven progress in targeted therapy and screening, concerns on drug resistance, toxicity, global inequities, and suboptimal risk stratification continue to limit outcomes. This review systematically summarizes current advances across four interconnected areas of breast cancer research and management, including molecular pathogenesis, targeted therapy, screening, and prevention. It describes key biological processes that shape tumor heterogeneity and examines targeted therapies, including endocrine agents, HER2-directed drugs, CDK4/6 and PI3K/AKT/mTOR inhibitors, antibody-drug conjugates, and immunotherapies, together with mechanisms of resistance and emerging treatment targets. It also evaluates evolving approaches in risk stratification and screening, highlighting progress in digital breast tomosynthesis, magnetic resonance imaging, contrast-enhanced mammography, and artificial intelligence-assisted interpretation. By integrating cutting-edge molecular insights with clinical advances, this review further highlights the expanding opportunities for personalized therapy and precision prevention. It outlines future directions linking multiomics and artificial intelligence to more equitable and effective breast cancer management.
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