乳腺癌是环境因素和遗传因素之间多种相互作用的结果。传统上,根据组织病理学和临床特征治疗乳腺癌。像人类基因组微阵列这样的DNA技术现在已经部分整合到临床实践中,并用于开发新的“个性化药物”和“药物遗传学”,以提高癌症药物的效率和安全性。我们研究了四种已建立的治疗方法-ER导管乳腺癌-对差异基因表达的影响。治疗包括单药他莫昔芬,两剂多西他赛和卡培他滨,或联合三剂CAF(环磷酰胺,阿霉素,和氟尿嘧啶)和CMF(环磷酰胺,甲氨蝶呤,和氟尿嘧啶)。Genevestigator8.1.0用于比较浸润性导管癌患者的五个数据集,未经治疗或用选定的药物治疗,来自健康控制的人。我们确定了74个差异表达基因涉及三个途径,即,凋亡(外在和内在),氧化信号,和PI3K/Akt信令。处理影响了凋亡基因的表达(TNFRSF10B[TRAIL],FAS,CASS3/6/7/8,PMAIP1[NOXA],BNIP3L,BNIP3、BCL2A1和BCL2),氧化应激相关基因(NOX4,XDH,MAOA,GSR,GPX3和SOD3),和PI3K/Akt通路基因(ERBB2[HER2])。乳腺癌治疗是复杂的,患者的药物反应和疗效各不相同。这就需要确定新的生物标志物来预测药物反应。利用现有数据和新技术。GSR,NOX4、CASP3和ERBB2是预测原发性ER+导管乳腺癌治疗反应的潜在生物标志物。
Breast cancer arises as a result of multiple interactions between environmental and genetic factors. Conventionally, breast cancer is treated based on histopathological and clinical features. DNA technologies like the human genome microarray are now partially integrated into clinical practice and are used for developing new \"personalized medicines\" and \"pharmacogenetics\" for improving the efficiency and safety of cancer medications. We investigated the effects of four established therapies-for ER+ ductal breast cancer-on the differential gene expression. The therapies included single agent tamoxifen, two-agent docetaxel and capecitabine, or combined three-agents CAF (cyclophosphamide, doxorubicin, and fluorouracil) and CMF (cyclophosphamide, methotrexate, and fluorouracil). Genevestigator 8.1.0 was used to compare five datasets from patients with infiltrating ductal carcinoma, untreated or treated with selected drugs, to those from the healthy control. We identified 74 differentially expressed genes involved in three pathways, i.e., apoptosis (extrinsic and intrinsic), oxidative signaling, and PI3K/Akt signaling. The treatments affected the expression of apoptotic genes (TNFRSF10B [TRAIL], FAS, CASP3/6/7/8, PMAIP1 [NOXA], BNIP3L, BNIP3, BCL2A1, and BCL2), the oxidative stress-related genes (NOX4, XDH, MAOA, GSR, GPX3, and SOD3), and the PI3K/Akt pathway gene (ERBB2 [HER2]). Breast cancer treatments are complex with varying drug responses and efficacy among patients. This necessitates identifying novel biomarkers for predicting the drug response, using available data and new technologies. GSR, NOX4, CASP3, and ERBB2 are potential biomarkers for predicting the treatment response in primary ER+ ductal breast carcinoma.