Gene expression profiles to predict ovarian cancer chemo-response in the elderly

描述（由申请人提供）：上皮性卵巢癌是最致命的妇科恶性肿瘤，超过一半的卵巢癌新发病例发生在65岁以上的女性中。尽管老年卵巢癌患者的总体预后比年轻女性差，但这种差异的确切分子基础仍不清楚。我们从76例晚期浆液性卵巢癌的分析中获得了初步的微阵列数据，这表明有可能确定老年和年轻女性之间上皮性卵巢癌差异的离散全球基因表达模式。进一步我们的初步研究结果表明，它可能是有可能预测老年和年轻妇女的化疗反应。目前建议的目标是扩展我们的初步研究结果，以提高对老年妇女晚期上皮性卵巢癌分子基础的理解，并确定可能预测化疗反应的基因表达谱，以便将来的治疗可以针对个体患者。我们计划对64例老年和年轻妇女的晚期浆液性卵巢癌进行微阵列基因表达分析。该分析的数据将与先前在初步研究中排列的76个样本的数据相结合，以提供总共140个样本（70个来自老年女性，70个来自年轻女性）。将比较老年（>65岁）和年轻（<65岁）女性癌症的基因表达模式，以鉴定可能导致两组之间生存差异的基因。此外，对于两个年龄组，将比较对辅助铂/紫杉烷化疗完全缓解与不完全缓解的患者癌症之间的基因表达模式。贝叶斯回归分析将用于开发预测模型，该模型将在留一交叉验证研究中进行测试。将比较预测每个年龄组（老年人和年轻人）缓解的特征。预测老年女性化疗反应的基因谱的表征将促进基因表达谱导向疗法的开发，这将有助于老年人群的临床决策。因此，预测特征将使治疗能够针对老年患者，从而提高治疗疗效和反应率，减少不必要的毒性，重要的是，提高卵巢癌老年患者的生活质量。

DESCRIPTION (provided by applicant): Epithelial ovarian cancer is the most lethal gynecologic malignancy, and more than half of all new cases of ovarian cancer arise in women over age 65. Although elderly women with ovarian cancer have been shown to have a poorer overall prognosis compared to younger women, the exact molecular basis of this difference remains unclear. We have preliminary microarray data from analysis of 76 advanced serous ovarian cancers suggesting that it may be possible to identify discrete global gene expression patterns that underlie differences in epithelial ovarian cancer between elderly and younger women. Further our preliminary findings suggest that it may be possible to predict response to chemotherapy in elderly and younger women. The goal of the current proposal is to extend our preliminary findings to improve understanding of the molecular underpinnings of advanced stage epithelial ovarian cancer in elderly women and to identify gene expression profiles that may predict chemo-response, such that future therapy may be tailored to individual patients. We plan to perform microarray gene expression analysis of 64 advanced stage serous ovarian cancers from elderly and younger women. Data from this analysis will be combined with data from 76 samples previously arrayed in preliminary studies to provide a total of 140 samples (70 from elderly women and 70 from younger women). Gene expression patterns will be compared between cancers from elderly (>65 yrs age) and younger (<65 yrs age) women to identify genes that may underlie the difference survival between the 2 groups. Additionally, for both age groups, gene expression patterns will be compared between cancers from patients that demonstrated a complete- versus an incomplete-response to adjuvant platinum/taxane chemotherapy. Bayesian regression analysis will be used to develop predictive models which will be tested in leave-one-out cross validation studies. The profiles that predict response in each age group (elderly and younger) will be compared. Characterization of gene profiles that predict chemo- response in elderly women will facilitate the development of gene expression profile-directed therapies that will aid clinical-decision making in the aging population. As such, predictive profiles will enable therapies to be tailored to elderly patients, and thus improve treatment efficacy and response rates, decrease unnecessary toxicities, and importantly, enhance quality of life for aging patients with ovarian cancer.