Miller William R, Larionov Alexey, Renshaw Lorna, Anderson Thomas J, Walker John R, Krause Andreas, Sing Tobias, Evans Dean B, Dixon J Michael
Breast Research Group, University of Edinburgh, Edinburgh, United Kingdom.
J Clin Oncol. 2009 Mar 20;27(9):1382-7. doi: 10.1200/JCO.2008.16.8849. Epub 2009 Feb 17.
Endocrine agents, such as letrozole, are established in the treatment of hormone-dependent breast cancer. However, response rates are only 50% to 70% in the neoadjuvant setting and lower in advanced disease. Thus there is a need to identify novel markers predicting for response and to understand molecular mechanisms of resistance.
Sequential tumor biopsies were taken before and after 10 to 14 days of neoadjuvant treatment with letrozole in patients with estrogen receptor-rich breast cancer. Expression profiles on high-density microarray chips were then related to clinical responses as assessed from tumor volume measurements after 3 months of treatment.
Of 52 patients, 37 (71%) were classified as having a clinical response to letrozole and 15 being clinically resistant. Bioinformatic analysis identified 205 covariables (69 baseline expression, 45 day 14 expression, and 91 change in expression with treatment) which differentiated between clinical responders and nonresponders. Hierarchical clustering using the variables separated responders and nonresponders into two distinct groups. Ontological assessment indicated that discriminating genes were enriched toward cellular biosynthetic processes. In particular, functional gene assessment showed ribosomal protein probes to have higher baseline expression in tumors responsive to letrozole and increased expression with treatment in nonresponding cases.
To our knowledge, this is the first study to describe genetic covariables and molecular processes discriminating between tumors clinically responsive and resistant to an aromatase inhibitor. The understanding of such molecular phenotypes will be important in optimizing the clinical use of aromatase inhibitors, both in terms of identifying responsive breast cancers and developing new agents to target resistance pathways.
内分泌药物，如来曲唑，已被用于激素依赖性乳腺癌的治疗。然而，在新辅助治疗中，缓解率仅为50%至70%，在晚期疾病中更低。因此，需要识别预测反应的新标志物，并了解耐药的分子机制。
对富含雌激素受体的乳腺癌患者在接受来曲唑新辅助治疗10至14天前后进行序贯肿瘤活检。然后将高密度微阵列芯片上的表达谱与治疗3个月后通过肿瘤体积测量评估的临床反应相关联。
52例患者中，37例（71%）被分类为对来曲唑有临床反应，15例临床耐药。生物信息学分析确定了205个协变量（69个基线表达、45个第14天表达以及91个治疗后表达变化），这些协变量区分了临床反应者和无反应者。使用这些变量进行层次聚类将反应者和无反应者分为两个不同的组。本体评估表明，鉴别基因富集于细胞生物合成过程。特别是，功能基因评估显示核糖体蛋白探针在对来曲唑有反应的肿瘤中基线表达较高，而在无反应的病例中随着治疗表达增加。
据我们所知，这是第一项描述区分对芳香化酶抑制剂有临床反应和耐药的肿瘤的遗传协变量和分子过程的研究。了解这些分子表型对于优化芳香化酶抑制剂的临床应用非常重要，无论是在识别反应性乳腺癌还是开发针对耐药途径的新药物方面。
