文章:
乳腺癌转移:标志物和模型
Breast cancer metastasis: markers and models
原文发布日期:2005-08-01
DOI: 10.1038/nrc1670
类型: Review Article
开放获取: 否
要点:
- Current prognostic criteria only poorly predict the metastasis risk for an individual breast cancer patient. Therefore, many women receive cytotoxic chemotherapy unnecessarily.
- Gene-expression signatures of human primary breast tumours predict more accurately than current prognostic criteria which patients are destined to relapse and ultimately die of metastatic breast cancer, and should therefore receive adjuvant therapy.
- New molecular insights challenge the traditional model of metastasis, and indicate that the metastatic capacity of breast tumours is an inherent feature, and not necessarily a late, acquired phenotype.
- Local breast cancer might have a 'non-metastatic, good-prognosis' stem cell of origin; metastasizing systemic breast cancer might have a 'metastatic, poor-prognosis' stem cell of origin.
要点翻译:
- 目前的预后标准难以准确预测个体乳腺癌患者的转移风险,因此许多女性不必要地接受了细胞毒性化疗。
- 与现有预后标准相比,人类原发性乳腺癌的基因表达特征能更精准地预测哪些患者将出现复发并最终死于转移性乳腺癌,从而明确应接受辅助治疗的人群。
- 新的分子研究视角对传统转移模型提出挑战,指出乳腺癌的转移能力是其固有特征,而未必是晚期获得的表现型。
- 局部乳腺癌可能起源于"非转移性、预后良好"的干细胞;而具有转移能力的全身性乳腺癌则可能源自"转移性、预后不良"的干细胞。
英文摘要:
Breast cancer starts as a local disease, but it can metastasize to the lymph nodes and distant organs. At primary diagnosis, prognostic markers are used to assess whether the transition to systemic disease is likely to have occurred. The prevailing model of metastasis reflects this view — it suggests that metastatic capacity is a late, acquired event in tumorigenesis. Others have proposed the idea that breast cancer is intrinsically a systemic disease. New molecular technologies, such as DNA microarrays, support the idea that metastatic capacity might be an inherent feature of breast tumours. These data have important implications for prognosis predicition and our understanding of metastasis.
摘要翻译:
乳腺癌最初表现为局部疾病,但可转移至淋巴结及远处器官。原发诊断时,需借助预后标志物评估其是否已向系统性疾病转化。现行转移模型认为转移能力是肿瘤发生晚期才获得的事件;也有人提出乳腺癌本质即为系统性疾病。新兴分子技术(如DNA微阵列)支持转移能力可能是乳腺肿瘤固有特征的观点。这些数据对预后预测及转移机制理解具有重大意义。
原文链接:
Breast cancer metastasis: markers and models