Gene expression pathway analysis to predict response to neoadjuvant docetaxel and capecitabine for breast cancer.
Gene expression pathway analysis to predict response to neoadjuvant docetaxel and capecitabine for breast cancer.
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DOI：
10.1007/s10549-009-0651-3
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发表时间：
2010-03
影响因子：
3.8
通讯作者：
Zujewski JA
中科院分区：
文献类型：
--
作者：
Korde LA;Lusa L;McShane L;Lebowitz PF;Lukes L;Camphausen K;Parker JS;Swain SM;Hunter K;Zujewski JA
新辅助化疗已被证明对乳腺癌与术后治疗等效，并且能够评估化疗反应。在一项针对II/III期乳腺癌的多西他赛（T）和卡培他滨（X）新辅助化疗的试点试验中，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治疗。从麦默通™核心活检获取的肿瘤组织在TX治疗前（BL）和第1周期后（C1）被迅速冷冻并储存在 -70°C直至处理。基因表达分析使用了Affymetrix HG - U133 Plus 2.0基因芯片阵列。在进行RMA标准化后，使用BRB Array Tools进行统计分析。基因本体论（GO）通路分析使用随机方差t检验，显著水平为P < 0.005。对于通过GO通路分析确定为显著的基因类别，使用单变量t检验比较这些通路内单个基因在不同类别之间的表达水平；报告那些显著水平为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）。通过GO通路分析，39个基因类别可区分应答者和非应答者，最显著的是涉及微管组装和调节的基因。在比较化疗前后的标本时，我们确定了71个差异表达的基因类别，包括DNA修复和细胞增殖调节。在45个GO通路中，化疗1个周期后表达的变化在应答者和非应答者之间存在显著差异。大多数肿瘤样本属于基底样和腔面B类别。ROR评分因化疗而降低；这种变化在根据临床标准被归类为应答者的患者样本中更为明显。GO通路分析确定了许多与治疗反应相关的基因类别，并且可能是一种用于识别对化疗反应重要的基因的有信息价值的方法。有必要使用此处描述的方法进行更大规模的研究，以全面评估化疗反应中的基因表达变化。
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 Gene-Chip 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.
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影响因子：
5.7
作者：
Mano, Yuria;Takahashi, Koji;Daigo, Yataro
通讯作者：
Daigo, Yataro
影响因子：
11.5
作者：
Lebowitz, PF;Eng-Wong, J;Zujewski, J
通讯作者：
Zujewski, J
DOI：
10.1073/pnas.191388598
发表时间：
2001-09-25
影响因子：
11.1
作者：
Gonçalves, A;Braguer, D;Jordan, MA
通讯作者：
Jordan, MA
影响因子：
45.3
作者：
Parker, Joel S.;Mullins, Michael;Bernard, Philip S.
通讯作者：
Bernard, Philip S.
影响因子：
4.2
作者：
Chuthapisith, Suebwong;Eremin, Jennifer M.;Eremin, Oleg
通讯作者：
Eremin, Oleg