Department of Pathology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; Dartmouth Hitchcock Medical Center and the Norris Cotton Cancer Center, Lebanon, New Hampshire.
Department of Pathology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire; Dartmouth Hitchcock Medical Center and the Norris Cotton Cancer Center, Lebanon, New Hampshire.
Am J Pathol. 2013 Oct;183(4):1075-1083. doi: 10.1016/j.ajpath.2013.07.002. Epub 2013 Aug 3.
Breast cancer is a complex disease characterized by many morphological, clinical, and molecular features. For many years, breast cancer has been classified according to traditional parameters, such as histological type, grade, tumor size, lymph node involvement and vascular invasion, and biomarkers (eg, estrogen receptor, progesterone receptor, and epidermal growth factor receptor 2), which are used in patient management. With emerging imaging techniques (ie, digital mammography, tomosynthesis, ultrasonography, magnetic resonance imaging, nuclear medicine, and genomic techniques, such as real-time RT-PCR and microarrays), breast cancer diagnostics is going through a significant evolution. Imaging technologies have improved breast cancer diagnosis, survival, and treatment by early detection of primary or metastatic lesions, differentiating benign from malignant lesions and promoting intraoperative surgical guidance and postoperative specimen evaluation. Genomic and transcriptomic technologies make the analysis of gene expression signatures and mutation status possible so that tumors may be classified more accurately with respect to diagnosis and prognosis. The -omic era has also made possible the identification of new biomarkers involved in breast cancer development, survival, and invasion that can be gradually incorporated into clinical testing. These advances in both imaging and genomics contribute to more personalized and predictive patient management. We review the progress made in breast cancer diagnosis and management using these new tools.
乳腺癌是一种复杂的疾病,具有许多形态学、临床和分子特征。多年来,乳腺癌一直根据传统参数进行分类,例如组织学类型、分级、肿瘤大小、淋巴结转移和血管侵犯,以及生物标志物(如雌激素受体、孕激素受体和表皮生长因子受体 2),这些参数用于患者管理。随着新兴成像技术(即数字乳腺摄影、断层合成、超声、磁共振成像、核医学以及实时 RT-PCR 和微阵列等基因组技术)的出现,乳腺癌的诊断正在发生重大变革。成像技术通过早期检测原发性或转移性病变、区分良性和恶性病变以及促进术中手术指导和术后标本评估,提高了乳腺癌的诊断、生存率和治疗效果。基因组和转录组技术使得分析基因表达谱和突变状态成为可能,从而可以更准确地对肿瘤进行分类,以进行诊断和预后。组学时代还使得能够鉴定出与乳腺癌发生、生存和侵袭相关的新生物标志物,这些标志物可以逐渐纳入临床检测中。这些在成像和基因组学方面的进展有助于实现更具个性化和预测性的患者管理。我们回顾了使用这些新工具在乳腺癌诊断和管理方面取得的进展。