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Gene expression pathway analysis to predict response to neoadjuvant docetaxel and capecitabine for breast cancer

机译:基因表达途径分析预测对乳腺癌新辅助多西他赛和卡培他滨的反应

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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°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 by GO 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 non-responders. 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. Keywords Neoadjuvant - Gene expression - Chemotherapy response - Microtubules - DNA repair - PAM50
机译:新辅助化疗已被证明等同于乳腺癌的术后治疗,并可以评估化疗反应。在多西他赛(T)和卡培他滨(X)BC / II期新辅助化疗的试验性试验中,我们评估了基线基因表达与肿瘤对治疗反应之间的相关性,并检查了与治疗相关的基因表达变化。患者接受了四个周期的TX。将得自Mammotome™核心活检标本的预处理(BL)和TX的周期1(C1)后获得的肿瘤组织进行快速冷冻,并保存在-70°C直至处理。基因表达分析利用了Affymetrix HG-U133 Plus 2.0 GeneChip阵列。在RMA归一化之后,使用BRB Array Tools进行统计分析。基因本体论(GO)途径分析使用随机方差t检验,显着性水平为P <0.005。对于通过GO通路分析确定为重要的基因类别,使用单变量t检验比较了这些通路内各个基因的表达水平。报告了那些显着性水平为P <0.05的基因。对肿瘤样品进行PAM50分析,以研究生物学亚型和复发风险(ROR)。使用GO途径分析,可以区分响应者和非响应者的39个基因类别,最主要的是涉及微管组装和调控的基因。当比较化疗前后的样本时,我们确定了71种差异表达的基因类别,包括DNA修复和细胞增殖调控。在45个GO途径中,一疗程化疗后的表达变化在反应者和非反应者之间存在显着差异。大部分肿瘤样本属于基底样和管腔B类。 ROR评分因化疗而降低;在根据临床标准归类为反应者的患者样本中,这种变化更为明显。 GO通路分析确定了许多与治疗反应有关的基因类别,可能是鉴定对化学疗法重要的基因的信息方法。使用此处描述的方法进行的大量研究对于充分评估基因表达对化疗的反应变化是必要的。新辅助剂-基因表达-化疗反应-微管-DNA修复-PAM50

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