Gene expression profiles of poor-prognosis primary breast cancer correlate with survival
Gene expression profiles of poor-prognosis primary breast cancer correlate with survival
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DOI：
10.1093/hmg/11.8.863
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发表时间：
2002-04-15
影响因子：
3.5
通讯作者：
Houlgatte, R
中科院分区：
文献类型：
--
作者：
Bertucci, F;Nasser, V;Houlgatte, R
乳腺癌的广泛异质性使肿瘤侵袭性的精确评估变得复杂，使治疗决策变得困难，并且在某些情况下治疗不合适。因此，接受辅助化疗的患者的长期无转移生存率仅为60%。有一个真正的需要，以确定参数，可以准确地预测这种治疗的有效性，为每一个病人。使用cDNA阵列，我们分析了55名接受蒽环类药物辅助化疗的预后不良乳腺癌患者的肿瘤样本。基因表达监测应用于一组约1000个候选癌症基因。表达谱的差异提供了疾病临床异质性的分子证据。首先，我们证实了先前研究中确定的23个基因预测集区分与不同生存期相关的肿瘤的能力。第二，使用从前一个衍生的精炼的基因集，我们区分，在55个临床同质肿瘤，3类具有显着不同的临床结果：5年总生存率和无转移生存率分别为100%和75%的第一类，65%和56%的第二和40%和20%的第三。这种区别是由两组编码具有不同功能的蛋白质（包括雌激素受体（ER））的基因的差异表达造成的。另一个发现是两个ER阳性肿瘤亚组的生存率不同。这些结果表明，基因表达谱可以预测临床结果，并导致更精确的乳腺肿瘤分类。此外，对转基因的鉴定可能会加速新的特异性和替代疗法的开发，从而允许更合理地定制治疗，这些治疗可能更有效，毒性更低。
The extensive heterogeneity of breast cancer complicates the precise assessment of tumour aggressiveness, making therapeutic decisions difficult and treatments inappropriate in some cases. Consequently, the long-term metastasis-free survival rate of patients receiving adjuvant chemotherapy is only 60%. There is a genuine need to identify parameters that might accurately predict the effectiveness of this treatment for each patient. Using cDNA arrays, we profiled tumour samples from 55 women with poor-prognosis breast cancer treated with adjuvant anthracycline-based chemotherapy. Gene expression monitoring was applied to a set of about 1000 candidate cancer genes. Differences in expression profiles provided molecular evidence of the clinical heterogeneity of disease. First, we confirmed the capacity of a 23-gene predictor set, identified in a previous study, to distinguish between tumours associated with different survival. Second, using a refined gene set derived from the previous one, we distinguished, among the 55 clinically homogeneous tumours, three classes with significantly different clinical outcome: 5-year overall survival and metastasis-free survival rates were respectively 100% and 75% in the first class, 65% and 56% in the second and 40% and 20% in the third. This discrimination resulted from the differential expression of two clusters of genes encoding proteins with diverse functions, including the estrogen receptor (ER). Another finding was the identification of two ER-positive tumour subgroups with different survival. These results indicate that gene expression profiling can predict clinical outcome and lead to a more precise classification of breast tumours. Furthermore, the characterization of discriminator genes might accelerate the development of new specific and alternative therapies, allowing more rationally tailored treatments that are potentially more efficient and less toxic.