卵巢癌中的预后 97 化疗反应基因特征。

The Prognostic 97 Chemoresponse Gene Signature in Ovarian Cancer.

机构信息

Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul, Republic of Korea.

Department of Biochemistry and Molecular Biology, Medical Research Center for Bioreaction to Reactive Oxygen Species and Biomedical Science Institute, School of Medicine, Kyung Hee University, Seoul, Republic of Korea.

出版信息

Sci Rep. 2017 Aug 29;7(1):9689. doi: 10.1038/s41598-017-08766-5.

Abstract

Patient diagnosis and care would be significantly improved by understanding the mechanisms underlying platinum and taxane resistance in ovarian cancer. Here, we aim to establish a gene signature that can identify molecular pathways/transcription factors involved in ovarian cancer progression, poor clinical outcome, and chemotherapy resistance. To validate the robustness of the gene signature, a meta-analysis approach was applied to 1,020 patients from 7 datasets. A 97-gene signature was identified as an independent predictor of patient survival in association with other clinicopathological factors in univariate [hazard ratio (HR): 3.0, 95% Confidence Interval (CI) 1.66-5.44, p = 2.7E-4] and multivariate [HR: 2.88, 95% CI 1.57-5.2, p = 0.001] analyses. Subset analyses demonstrated that the signature could predict patients who would attain complete or partial remission or no-response to first-line chemotherapy. Pathway analyses revealed that the signature was regulated by HIF1α and TP53 and included nine HIF1α-regulated genes, which were highly expressed in non-responders and partial remission patients than in complete remission patients. We present the 97-gene signature as an accurate prognostic predictor of overall survival and chemoresponse. Our signature also provides information on potential candidate target genes for future treatment efforts in ovarian cancer.

摘要

通过了解卵巢癌中铂类和紫杉烷类耐药的机制,患者的诊断和治疗将得到显著改善。在这里,我们旨在建立一个基因特征,可以识别涉及卵巢癌进展、不良临床结局和化疗耐药的分子途径/转录因子。为了验证基因特征的稳健性,我们应用荟萃分析方法对来自 7 个数据集的 1020 名患者进行了分析。鉴定出一个由 97 个基因组成的特征,该特征与其他临床病理因素一起,是患者生存的独立预测因子,在单变量[风险比(HR):3.0,95%置信区间(CI)1.66-5.44,p=2.7E-4]和多变量[HR:2.88,95% CI 1.57-5.2,p=0.001]分析中均如此。亚组分析表明,该特征可预测对一线化疗完全或部分缓解或无反应的患者。通路分析显示,该特征受 HIF1α 和 TP53 调控,包括 9 个 HIF1α 调控的基因,这些基因在非应答者和部分缓解患者中的表达高于完全缓解患者。我们提出的 97 个基因特征是总生存期和化疗反应的准确预后预测因子。我们的特征还提供了有关卵巢癌未来治疗中潜在候选靶基因的信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5ef/5575202/a7a3ac4718f8/41598_2017_8766_Fig1_HTML.jpg

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