乳腺癌新辅助化疗疗效的基因表达谱分析

目的 分析乳腺癌新辅助化疗前活检组织的基因表达谱数据,筛选与T/FAC(多西他赛、氟尿嘧啶、多柔比星和环磷酰胺)或T/FEC(多西他赛、氟尿嘧啶、表柔比星和环磷酰胺)新辅助化疗方案治疗有效性显著相关的基因.方法 从国际上已发表的相关文献中检索并获取乳腺癌基因表达谱数据,按照统一的新辅助化疗方式进行数据筛选,最终保留4个符合要求的数据集,共844个样本.其中样本按照化疗效果分为病理完全缓解(pCR)和残留浸润性癌(RD)两类.分析两组样本差异表达的基因,探讨其表达水平的变化与化疗疗效的相关性. 结果 通过分析,我们分别在4个数据集中找出显著差异的基因(校正P<0.05),按照表达水平的高低,分为pCR组相比RD组高表达的基因和低表达的基因两组.最后,将4个数据的结果整合,得到在4个数据集中同时高表达或低表达的基因,分别为34和42个.基于交集的差异表达基因,对样本进行无监督聚类,发现pCR和RD两组倾向性地分别富集在两类(一致性检验,P<0.05).结论 分析得到的76个差异表达基因与乳腺癌新辅助化疗疗效有关,可能成为新的化疗疗效预测标志物.

Gene expression analysis of neoadjuvant chemotherapy efficacy in human breast cancers

Objective To analyze gene expression profiles of biopsy specimens from breast cancer patients who were treated with neoadjuvant chemotherapy(NAC) after biopsies, and to identify the genes which are closely associated with the efficacy of neoadjuvant chemotherapy with T/FAC [docetaxel(Taxotere), 5-fluorouracil, doxorubicin and cyclophosphamide] or T/FEC (Taxotere, 5-fluorouracil, epirubicin and cyclophosphamide) regimen.Methods We retrieved and collected gene expression profiles from publicly available databases.Four datasets, a total of 844 samples, were finally retained because all the patients had received a uniform neoadjuvant chemotherapy regimen.Response to neoadjuvant chemotherapy was categorized as a pathological complete response (pCR) or residual invasive cancer (RD).The differentially expressed genes (adjusted P-value<0.05) and therapeutic efficacy were analyzed and explored.Results After differential analysis, genes whose expressions were higher or lower in pCR group than in RD group were identified in each of the four datasets, respectively.There were 34 and 42 genes which were simultaneously more highly expressed or more lowly expressed in pCR group than in RD group in the four datasets.The unsupervised clustering, based on the 76 intersection genes, showed that the pCR specimens tended to form one cluster and the RD tended to form the other.Conclusion The seventy-six differentially expressed genes are associated with the efficacy of neoadjuvant chemotherapy and are likely to be novel predictive biomarkers for the efficacy of neoadjuvant chemotherapy.