CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Advances in Breast Cancer Research: Immunological, Pathological, and Pharmacological Perspectives for Improving Patient Outcomes.
Advances in Breast Cancer Research: Immunological, Pathological, and Pharmacological Perspectives for Improving Patient Outcomes.
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乳腺癌仍是全球范围内诊断率最高的恶性肿瘤。过去十年间,分子生物学的进展已从肿瘤内在特征扩展到免疫微环境和患者特异性药物基因组学特征,深刻重塑了乳腺肿瘤学的诊断、预后和治疗范式。由于技术的快速进步和治疗手段的不断扩展,定期对基础原理和新兴证据进行综合梳理,对于批判性地解读正在进行的进展仍然至关重要。本综述全面概述了当代全球乳腺癌的整体格局,整合了诊断、风险分层和治疗创新方面的进展。
我们审视了正在重新定义肿瘤特征描述的新兴技术,包括数字病理学、人工智能辅助的形态学和分子分析,以及日益为预后和预测评估提供依据的先进分子谱分析方法。
我们进一步讨论了这些诊断框架如何转化为治疗进展,重点关注免疫治疗、抗体-药物偶联物、突变导向的靶向药物、治疗性疫苗和双特异性抗体。
总体而言,这些进展凸显了关键的转化研究优先事项,支持了循证临床决策,并明确承认了高收入地区与低收入和中等收入国家(LMICs)在可及性和实施方面存在的差距。
Breast cancer remains the most frequently diagnosed malignancy worldwide. Over the past decade, advances in molecular biology have expanded beyond tumor-intrinsic features to encompass the immune microenvironment and patient-specific pharmacogenomic profiles, profoundly reshaping diagnostic, prognostic, and therapeutic paradigms in breast oncology.
Owing to rapid technological progress and an expanding therapeutic armamentarium, periodic synthesis of both foundational principles and emerging evidence remains essential for the critical interpretation of ongoing advances. This review provides a comprehensive overview of the contemporary global landscape of breast cancer, integrating developments in diagnosis, risk stratification, and therapeutic innovation.
We examine the emerging technologies that are redefining tumor characterization, including digital pathology, artificial intelligence-assisted morphological and molecular analyses, and advanced molecular profiling approaches that increasingly inform prognostic and predictive assessment.
We further discuss how these diagnostic frameworks are translating into therapeutic advances, with emphasis on immunotherapy, antibody-drug conjugates, mutation-directed targeted agents, therapeutic vaccines, and bispecific antibodies. Collectively, these developments highlight key translational research priorities, support evidence-based clinical decision-making, and explicitly acknowledge disparities in access and implementation between high-income settings and low- and middle-income countries (LMICs).
在 PubMed 查看 → 出版商原文(DOI) 全文 PDF(PMC)· 可下载 治疗专题与资料阅读指南 资料来源与翻译说明 报告译文或资料问题 →
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