Division of Medical Oncology, Department of Medicine University of Washington/Seattle Cancer Care Alliance, G3639, 825 Eastlake Ave, E, Seattle, WA 98109, USA.
Breast Cancer Res Treat. 2010 Feb;119(3):685-99. doi: 10.1007/s10549-009-0651-3.
Neoadjuvant chemotherapy has been shown to be equivalent to post-operative treatment for breast cancer, and allows for assessment of chemotherapy response. In a pilot trial of docetaxel (T) and capecitabine (X) neoadjuvant chemotherapy for Stage II/III BC, we assessed correlation between baseline gene expression and tumor response to treatment, and examined changes in gene expression associated with treatment. Patients received four cycles of TX. Tumor tissue obtained from Mammotome core biopsies pretreatment (BL) and post-cycle 1 (C1) of TX was FLash frozen and stored at -70 degrees C until processing. Gene expression analysis utilized Affymetrix HG-U133 Plus 2.0 GeneChip arrays. Statistical analysis was performed using BRB Array Tools after RMA normalization. Gene ontology (GO) pathway analysis used random variance t tests with a significance level of P\0.005. For gene categories identified byGO pathway analysis as significant, expression levels of individual genes within those pathways were compared between classes using univariate t tests; those genes with significance level of P\0.05 were reported. PAM50 analyses were performed on tumor samples to investigate biologic subtype and risk of relapse (ROR). Using GO pathway analysis, 39 gene categories discriminated between responders and non-responders,most notably genes involved in microtubule assembly and regulation. When comparing pre- and post-chemotherapy specimens, we identified 71 differentially expressed gene categories, including DNA repair and cell proliferation regulation. There were 45 GO pathways in which the change in expression after one cycle of chemotherapy was significantly different among responders and nonresponders. The majority of tumor samples fell into the basal like and luminal B categories. ROR scores decreased in response to chemotherapy; this change was more evident in samples from patients classified as responders by clinical criteria. GO pathway analysis identified a number of gene categories pertinent to therapeutic response, and may be an informative method for identifying genes important in response to chemotherapy. Larger studies using the methods described here are necessary to fully evaluate gene expression changes in response to chemotherapy.
新辅助化疗已被证明与乳腺癌的术后治疗等效,并可评估化疗反应。在一项Ⅱ/Ⅲ期乳腺癌多西他赛(T)联合卡培他滨(X)新辅助化疗的试验中,我们评估了基线基因表达与肿瘤对治疗的反应之间的相关性,并研究了与治疗相关的基因表达变化。患者接受了四个周期的 TX 治疗。在 TX 治疗前(BL)和第 1 个周期后(C1)进行 Mammotome 核心活检,获得肿瘤组织,将其迅速冷冻并储存在-70℃,直至处理。使用 Affymetrix HG-U133 Plus 2.0 GeneChip 微阵列进行基因表达分析。BRB Array Tools 进行统计分析,采用 RMA 标准化后进行随机方差 t 检验。GO 途径分析采用具有显著水平 P\0.005 的随机方差 t 检验。GO 途径分析确定的基因类别,如果显著,则使用单变量 t 检验比较这些途径中各基因的表达水平;报告 P\0.05 的基因。对肿瘤样本进行 PAM50 分析,以研究生物学亚型和复发风险(ROR)。使用 GO 途径分析,我们区分了应答者和非应答者的 39 个基因类别,最显著的是涉及微管组装和调节的基因。在比较化疗前后标本时,我们发现了 71 个差异表达的基因类别,包括 DNA 修复和细胞增殖调节。在应答者和非应答者中,有 45 个 GO 途径的化疗一个周期后的表达变化明显不同。大多数肿瘤样本属于基底样和管腔 B 型。ROR 评分随着化疗而降低;在临床标准下分类为应答者的患者样本中,这种变化更为明显。GO 途径分析确定了一些与治疗反应相关的基因类别,这可能是一种识别对化疗反应重要的基因的有效方法。使用此处描述的方法进行更大规模的研究对于全面评估化疗反应中的基因表达变化是必要的。