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Chemosensitivity prediction in esophageal squamous cell carcinoma: Novel marker genes and efficacy-prediction formulae using their expression data

机译:食管鳞癌的化学敏感性预测:新的标记基因和功效预测公式,基于它们的表达数据

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Esophageal cancer is a highly lethal disease and the optimal therapy remains unclear. Since adjuvant chemotherapy gives a better chance of survival, we attempted to develop a chemosensitivity prediction model to improve individual responses to therapy. Comprehensive gene expression analyses (cDNA and oligonucleotide microarrays) and MTT assay of 8 drugs in 20 KYSE squamous cell carcinoma cell lines were performed to distinguish candidate marker genes whose expression levels reproducibly correlated with cellular drug sensitivities. After confirmation with real-time RT-PCR, we performed multiple regression analyses to develop drug-sensitivity prediction formulae using the quantified expression data of selected marker genes. Using the same sets of genes, we also constructed prediction models for individual clinical responses to 5-FU-based chemotherapy using 18 cases. We selected 5 better marker genes, known as drug sensitivity determinants, identified 9 novel predictive genes for 4 of 8 anticancer drugs [5-FU, CDDP, DOX, and CPT-11 (SN-38)], and developed highly predictive formulae of in vitro sensitivities to the 4 drugs and clinical responses to 5-FU-based adjuvant chemotherapies in terms of overall and disease-free survivals. Our selected genes are likely to be effective drug-sensitivity markers and formulae using the 9 novel genes would provide advantages in prediction.
机译:食道癌是一种高度致死性疾病,尚不清楚最佳治疗方法。由于辅助化疗可提供更好的生存机会,因此我们尝试建立化学敏感性预测模型以改善个体对治疗的反应。进行了全面的基因表达分析(cDNA和寡核苷酸微阵列)和20种KYSE鳞状细胞癌细胞系中8种药物的MTT分析,以区分其表达水平与细胞药物敏感性相关的候选标记基因。在通过实时RT-PCR确认后,我们使用所选标​​记物基因的定量表达数据进行了多元回归分析,以开发出药物敏感性预测公式。使用相同的基因集,我们还使用18例病例构建了针对基于5-FU的化疗的个体临床反应的预测模型。我们选择了5个更好的标记基因,称为药物敏感性决定子,为8种抗癌药物中的4种鉴定了9个新的预测基因[5-FU,CDDP,DOX和CPT-11(SN-38)],并开发了高度预测性的在总体和无病生存方面,对这4种药物的体外敏感性以及对基于5-FU的辅助化疗的临床反应。我们选择的基因可能是有效的药物敏感性标记物,使用9个新基因的公式将在预测中提供优势。

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