Gene expression profile for predicting survival in advanced-stage serous ovarian cancer across two independent datasets.
Gene expression profile for predicting survival in advanced-stage serous ovarian cancer across two independent datasets.
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DOI：
10.1371/journal.pone.0009615
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发表时间：
2010-03-12
期刊：
影响因子：
3.7
通讯作者：
Tanaka K
中科院分区：
文献类型：
--
作者：
Yoshihara K;Tajima A;Yahata T;Kodama S;Fujiwara H;Suzuki M;Onishi Y;Hatae M;Sueyoshi K;Fujiwara H;Kudo Y;Kotera K;Masuzaki H;Tashiro H;Katabuchi H;Inoue I;Tanaka K
晚期卵巢癌患者在初次减瘤手术后通常接受铂类/紫杉烷为基础的化疗。然而，个体患者的结局多种多样。因此，单凭临床病理因素不足以预测预后。我们的目的是确定一个无进展生存期（PFS）相关的分子谱预测晚期浆液性卵巢癌患者的生存。使用寡核苷酸微阵列分析了110例接受初次手术和铂/紫杉烷化疗的日本患者的晚期浆液性卵巢癌组织。我们通过单变量考克斯模型（p<0.01）选择了88个PFS相关基因，并在使用10倍交叉验证的岭回归考克斯模型调整各个基因的回归系数后，基于88个PFS相关基因生成预后指数。在多变量分析中，与其他临床因素相比，预后指数与PFS时间独立相关[风险比（HR），3.72; 95%置信区间（CI），2.66-5.43; p<0.0001]。在外部数据集中，多变量分析显示该预后指数与PFS时间显著相关（HR，1.54; 95% CI，1.20-1.98; p = 0.0008）。 此外，在两个独立的外部数据集中证实了预后指数和总生存时间之间的相关性（对数秩检验，p = 0.0010和0.0008）。 基于岭回归考克斯风险模型中的88个基因表达谱，我们的指数在预测两个不同数据集的癌症预后方面显示出独立于其他临床因素的预后能力。进一步的研究将是必要的，以提高预测准确性的预后指数对临床应用评估的风险复发晚期浆液性卵巢癌患者。
Advanced-stage ovarian cancer patients are generally treated with platinum/taxane-based chemotherapy after primary debulking surgery. However, there is a wide range of outcomes for individual patients. Therefore, the clinicopathological factors alone are insufficient for predicting prognosis. Our aim is to identify a progression-free survival (PFS)-related molecular profile for predicting survival of patients with advanced-stage serous ovarian cancer. Advanced-stage serous ovarian cancer tissues from 110 Japanese patients who underwent primary surgery and platinum/taxane-based chemotherapy were profiled using oligonucleotide microarrays. We selected 88 PFS-related genes by a univariate Cox model (p<0.01) and generated the prognostic index based on 88 PFS-related genes after adjustment of regression coefficients of the respective genes by ridge regression Cox model using 10-fold cross-validation. The prognostic index was independently associated with PFS time compared to other clinical factors in multivariate analysis [hazard ratio (HR), 3.72; 95% confidence interval (CI), 2.66–5.43; p<0.0001]. In an external dataset, multivariate analysis revealed that this prognostic index was significantly correlated with PFS time (HR, 1.54; 95% CI, 1.20–1.98; p = 0.0008). Furthermore, the correlation between the prognostic index and overall survival time was confirmed in the two independent external datasets (log rank test, p = 0.0010 and 0.0008). The prognostic ability of our index based on the 88-gene expression profile in ridge regression Cox hazard model was shown to be independent of other clinical factors in predicting cancer prognosis across two distinct datasets. Further study will be necessary to improve predictive accuracy of the prognostic index toward clinical application for evaluation of the risk of recurrence in patients with advanced-stage serous ovarian cancer.
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影响因子：
4
作者：
Agarwal, Roshan;Kaye, Stan B.
通讯作者：
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影响因子：
6.2
作者：
Goodman, MT;Howe, HL;Chen, VW
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DOI：
10.1111/j.2517-6161.1995.tb02031.x
发表时间：
1995-01-01
影响因子：
5.8
作者：
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通讯作者：
HOCHBERG, Y
影响因子：
9.8
作者：
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影响因子：
4.7
作者：
McGuire, V;Jesser, CA;Whittemore, AS
通讯作者：
Whittemore, AS