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Molecular Analysis-Directed Individualised Therapy in Ad

广告中分子分析导向的个体化治疗

基本信息

批准号：
6932342
负责人：
GEORGE R., SIMON
金额：
$ 31.24万
依托单位：
H. LEE MOFFITT CANCER CTR & RES INST
依托单位国家：
美国
项目类别：
财政年份：
2004
资助国家：
美国
起止时间：
2004-08-04 至 2008-07-31
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): Advances in the clinical management of patients with non-small-cell lung cancer (NSCLC) have been slow, and the 5-year survival, which is used as a benchmark for putative cure from this disease, is only 14%. Reasons are that most patients present in advanced stages of the disease when response rates (25-35%) to chemotherapy are low and complete and prolonged partial remissions rare, despite the availability of several newer agents. Clearly an innovative and novel therapeutic strategy is needed to improve survival in this disease. Recent advances in the identification of molecular determinants of poor outcome from NSCLC hold the promise for therapeutic decisions based on individual patients' tumor's molecular profile. We hypothesize that we will improve response rates, median, and 1-year survival in patients with advanced NSCLC by treating with chemotherapy selected on the basis of the patient's tumor's molecular profile. Results generated by us and others suggest that the outcome of patients with lung cancer is closely associated with expression of the genes ERCC1 and RRMI. High ERCC1 and RRM1 gene expression predicts for resistance to platinum agents and gemcitabine, respectively. Using ERCC1 and RRM1 as predictive markers for chemotherapy response and survival we designed a phase II clinical study. The goal is to determine the response rates (RR) in newly diagnosed patients with advanced NSCLC who are treated with a chemotherapeutic regimen assigned to them on the basis of ERCC1 expression and RRM1 expression. Prior to treatment we will measure the level of ERCC1 and RRM1 expression in the patient's tumor, on the basis of which the patient will be assigned specific doublet chemotherapy. After treatment, response rates will be assessed as primary endpoint. Additional measures of treatment efficacy are progression free survival (PFS), median survival MS), and 1-yr survival(1-yr S) in patients with advanced NSCLC treated using this rational algorithmic approach. Patients will be followed till death and survival curves will be generated.

描述（由申请人提供）：非小细胞肺癌（NSCLC）患者的临床管理进展缓慢，作为该疾病假定治愈的基准的5年生存率仅为14%。原因是大多数患者出现在疾病的晚期，对化疗的反应率（25-35%）很低，完全和长期的部分缓解很少，尽管有几种较新的药物可用。显然，需要一种创新的治疗策略来提高这种疾病的生存率。在确定非小细胞肺癌预后不良的分子决定因素方面的最新进展，为基于个体患者肿瘤分子特征的治疗决策带来了希望。我们假设，通过根据患者肿瘤的分子特征选择化疗方案，我们将提高晚期NSCLC患者的缓解率、中位数和1年生存率。我们等人的研究结果表明，肺癌患者的预后与ERCC1和RRMI基因的表达密切相关。高ERCC1和RRM1基因表达分别预测对铂类药物和吉西他滨的耐药。使用ERCC1和RRM1作为化疗反应和生存的预测标志物，我们设计了一项II期临床研究。目的是确定新诊断的晚期NSCLC患者在接受基于ERCC1和RRM1表达分配的化疗方案治疗时的缓解率（RR）。治疗前，我们将检测患者肿瘤中ERCC1和RRM1的表达水平，并在此基础上对患者进行特异性的双联化疗。治疗后，反应率将作为主要终点进行评估。使用这种合理算法方法治疗的晚期非小细胞肺癌患者的无进展生存期（PFS）、中位生存期（MS）和1年生存期（1年S）是治疗效果的其他指标。对患者进行随访，直至生成死亡和生存曲线。