Department of Breast Surgery, Fudan University Shanghai Cancer Center, 270 Dong An Road, Shanghai, China.
Cancer Chemother Pharmacol. 2012 Nov;70(5):637-44. doi: 10.1007/s00280-012-1949-0. Epub 2012 Aug 19.
Neoadjuvant chemotherapy for advanced breast cancer may improve the radicality for a subset of patients, but others may suffer from severe adverse drug reactions without any benefit. To predict the responses to chemotherapy, we performed a phase II trial of neoadjuvant chemotherapy using a weekly PCb [paclitaxel (Taxol) plus carboplatin] regimen for stage II/III breast cancer and assessed the correlation between baseline gene expression and the tumor response to treatment.
A total of 61 patients with stage II-III breast cancer were included and administered four cycles of preoperative PCb. We performed a gene expression analysis using Affymetrix HG-U133 Plus 2.0 GeneChip arrays in 31 breast cancer tissues. Differentially expressed genes (DEGs) were identified by the significance analysis of microarrays (SAM) program using a false discovery rate of 0.05. The Functional Annotation Tool in the DAVID Bioinformatics Resources was used to perform the gene functional enrichment analysis. The other 30 patients (15 pCR and 15 non-pCR patients) were available as an independent validation set to test the selected DEGs by quantitative real-time PCR analysis (qRT-PCR).
By analyzing six pathological complete response (pCR) patients and 25 patients with non-pCR, 300 probes (231 genes) were identified as differentially expressed between pCR and residual disease by the SAM program when the fold change was >2. The gene functional enrichment analysis revealed 15 prominent gene categories that were different between pCR and non-pCR patients, most notably the genes involved in the peroxisome proliferator-activated receptor (PPAR), DNA repair and ER signal pathways and in the immune-related gene cluster. The qRT-PCR analysis results for the genes in the PPAR pathway (LPL, SORBS1, PLTP, SCD5, MMP1 and CSTA) in independent validation set were consistent with the results from the microarray data analysis.
In the present study, we identified a number of gene categories pertinent to the therapeutic response. We believe that the PPAR pathway may be an important predictor of genes that are involved in the chemotherapy response.
新辅助化疗可使部分晚期乳腺癌患者获得根治性疗效，但部分患者可能因严重药物不良反应而无法获益。为了预测化疗反应，我们对Ⅱ/Ⅲ期乳腺癌患者进行了新辅助每周 PCb（紫杉醇[Taxol]加卡铂）方案化疗的Ⅱ期临床试验，并评估了基线基因表达与肿瘤治疗反应之间的相关性。
共纳入 61 例Ⅱ-Ⅲ期乳腺癌患者，接受术前 4 周期 PCb 治疗。我们对 31 例乳腺癌组织进行 Affymetrix HG-U133 Plus 2.0 GeneChip 微阵列基因表达分析。采用假发现率（FDR）为 0.05 的 SAM 程序识别差异表达基因（DEGs）。利用 DAVID 生物信息学资源的功能注释工具进行基因功能富集分析。其余 30 例患者（15 例 pCR 患者和 15 例非 pCR 患者）作为独立验证集，采用实时荧光定量 PCR 分析（qRT-PCR）检测选定的 DEGs。
通过对 6 例完全病理缓解（pCR）患者和 25 例非 pCR 患者的分析，SAM 程序确定当 fold change>2 时，pCR 与残留疾病之间有 300 个探针（231 个基因）存在差异表达。基因功能富集分析显示，pCR 与非 pCR 患者之间有 15 个明显不同的基因类别，最显著的是与过氧化物酶体增殖物激活受体（PPAR）、DNA 修复和 ER 信号通路以及免疫相关基因簇相关的基因。独立验证集 PPAR 通路基因（LPL、SORBS1、PLTP、SCD5、MMP1 和 CSTA）的 qRT-PCR 分析结果与微阵列数据分析结果一致。
本研究确定了一些与治疗反应相关的基因类别。我们认为 PPAR 通路可能是参与化疗反应的重要预测基因。
