Immediate gene expression changes after the first course of neoadjuvant chemotherapy in patients with primary breast cancer disease
Immediate gene expression changes after the first course of neoadjuvant chemotherapy in patients with primary breast cancer disease
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DOI：
10.1158/1078-0432.ccr-04-1031
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发表时间：
2004-10-01
影响因子：
11.5
通讯作者：
Bojar, H
中科院分区：
文献类型：
--
作者：
Modlich, O;Prisack, HB;Bojar, H
目的：我们的目标是确定基因表达的变化后不久，开始新辅助化疗的原发性breast cancer.Experimental Design：从原发性乳腺癌患者的活检前的任何治疗和24小时后开始的新辅助化疗。来自代表25名患者的配对样本的表达分析用Clontech过滤器阵列进行。使用Affytron GeneChip平台对这25个配对样本的子队列进行了额外分析。所有的成绩单从这两个平台进行查询expressional changes.Results：进行层次聚类分析，我们聚类前和治疗后的样本，从个别患者更接近彼此比从不同的患者的样本。这反映了直接对所用药物作出反应的转录本数量相当少。虽然在治疗期间发生的转录药物反应在个体患者之间不同，但两个基因（p21（WAF 1/CIP 1）和MIC-1）在治疗后样品中上调。这可以通过半定量和实时逆转录PCR来验证。基于Clontech或Affytech平台独立鉴定的约25个基因的部分最小判别分析可以清楚地区分治疗前和治疗后样品。然而，某些基因表达水平的相关性以及由不同平台确定的差异模式和簇的相关性并不总是令人满意。结论：这项研究证明了监测治疗后基因表达变化作为药物药效学指标的潜力。作为一种临床实验室模型，它可以用于识别敏感性和反应性肿瘤患者，并帮助优化序贯治疗的选择，明显提高无复发生存率和总生存率。
Purpose: Our goal was to identify genes undergoing expressional changes shortly after the beginning of neoadjuvant chemotherapy for primary breast cancer.Experimental Design: The biopsies were taken from patients with primary breast cancer prior to any treatment and 24 hours after the beginning of the neoadjuvant chemotherapy. Expression analyses from matched pair samples representing 25 patients were carried out with Clontech filter arrays. A subcohort of those 25 paired samples were additionally analyzed with the Affymetrix GeneChip platform. All of the transcripts from both platforms were queried for expressional changes.Results: Performing hierarchical cluster analysis, we clustered pre- and posttreatment samples from individual patients more closely to each other than the samples taken from different patients. This reflects the rather low number of transcripts responding directly to the drugs used. Although transcriptional drug response occurring during therapy differed between individual patients, two genes (p21(WAF1/CIP1) and MIC-1) were up-regulated in posttreatment samples. This could be validated by semiquantitative and real-time reverse transcription-PCR. Partial least-discriminant analysis based on approximately 25 genes independently identified by either Clontech or Affymetrix platforms could clearly discriminate pre- and posttreatment samples. However, correlation of certain gene expression levels as well as of differential patterns and clusters as determined by a different platform was not always satisfying.Conclusions: This study has demonstrated the potential of monitoring posttreatment changes in gene expression as a measure of the pharmacodynamics of drugs. As a clinical laboratory model, it can be useful to identify patients with sensitive and reactive tumors and to help for optimized choice for sequential therapy and obviously improve relapse-free and overall survival.