A gene signature predicting for survival in suboptimally debulked patients with ovarian cancer.
A gene signature predicting for survival in suboptimally debulked patients with ovarian cancer.
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DOI：
10.1158/0008-5472.can-07-6595
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发表时间：
2008-07-01
期刊：
影响因子：
11.2
通讯作者：
Birrer MJ
中科院分区：
文献类型：
--
作者：
Bonome T;Levine DA;Shih J;Randonovich M;Pise-Masison CA;Bogomolniy F;Ozbun L;Brady J;Barrett JC;Boyd J;Birrer MJ
尽管存在形态学上无法区分的疾病，但晚期卵巢肿瘤患者表现出广泛的生存终点。我们假设基因表达谱可以识别解释这些不同临床结果的预后特征。为了解析与生存相关的基因座，使用 Affymetrix 人 U133A 微阵列完成了 185 个（90 个最佳/95 个次优）原发性卵巢肿瘤的基因表达谱分析。 Cox回归分析确定了与最佳和次优减灭肿瘤组中的生存相关的探针组，P值<0.01。对每个肿瘤队列应用留一法交叉验证，并通过排列测试进行确认。通过将基因特征应用于晚期次优减灭肿瘤表达谱的公开阵列数据库来进行外部验证。预后特征成功地根据次优（P = 0.0179）但不是最佳减瘤（P = 0.144）患者的生存率对肿瘤进行分类。使用独立的肿瘤组验证了次优基因特征（比值比，8.75；P = 0.0146）。为了阐明在减瘤效果不佳的患者中适合治疗干预的信号事件，对前 57 个与生存相关的探针组完成了通路分析。对于减灭效果不佳的患者，预测基因特征的确认支持了临床相关预测因子的存在，以及新的治疗机会的可能性。最终，为次优减灭肿瘤定义的预后分类器可能有助于对这一高危人群的患者预后进行分类和提高。 [癌症研究 2008;68(13):5478–86]
Despite the existence of morphologically indistinguishable disease, patients with advanced ovarian tumors display a broad range of survival end points. We hypothesize that gene expression profiling can identify a prognostic signature accounting for these distinct clinical outcomes. To resolve survival-associated loci, gene expression profiling was completed for an extensive set of 185 (90 optimal/95 suboptimal) primary ovarian tumors using the Affymetrix human U133A microarray. Cox regression analysis identified probe sets associated with survival in optimally and suboptimally debulked tumor sets at a P value of <0.01. Leave-one-out cross-validation was applied to each tumor cohort and confirmed by a permutation test. External validation was conducted by applying the gene signature to a publicly available array database of expression profiles of advanced stage suboptimally debulked tumors. The prognostic signature successfully classified the tumors according to survival for suboptimally (P = 0.0179) but not optimally debulked (P = 0.144) patients. The suboptimal gene signature was validated using the independent set of tumors (odds ratio, 8.75; P = 0.0146). To elucidate signaling events amenable to therapeutic intervention in suboptimally debulked patients, pathway analysis was completed for the top 57 survival-associated probe sets. For suboptimally debulked patients, confirmation of the predictive gene signature supports the existence of a clinically relevant predictor, as well as the possibility of novel therapeutic opportunities. Ultimately, the prognostic classifier defined for suboptimally debulked tumors may aid in the classification and enhancement of patient outcome for this high-risk population. [Cancer Res 2008;68(13):5478–86]