Construction and Validation of a Novel Glycometabolism-Related Gene Signature Predicting Survival in Patients With Ovarian Cancer.
Construction and Validation of a Novel Glycometabolism-Related Gene Signature Predicting Survival in Patients With Ovarian Cancer.
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DOI：
10.3389/fgene.2020.585259
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发表时间：
2020
影响因子：
3.7
通讯作者：
Yan X
中科院分区：
文献类型：
--
作者：
Liu L;Cai L;Liu C;Yu S;Li B;Pan L;Zhao J;Zhao Y;Li W;Yan X
在所有致死性妇科恶性肿瘤中，卵巢癌的死亡率最高。本研究的目的是建立一个稳定和个性化的糖代谢相关的预后指标来预测卵巢癌患者的总生存期。卵巢癌患者的基因表达谱和临床信息来源于四个公共GEO数据集，分为训练组和测试组。选择与预后显著相关的糖代谢相关基因。建立风险评分模型并进行验证，评价其预测价值。我们发现了5个与预后显著相关的基因，并建立了5 - mrna特征。在训练集和验证集中，5 - mrna特征显著地将患者分为低危组和高危组。生存分析显示，该模型获得的高风险评分与不良生存结局显著相关，可作为卵巢癌患者的独立预测指标。此外，5 - mrna标记可以预测不同亚组卵巢癌患者的总生存期。综上所述，我们成功构建了一个预测卵巢癌患者预后的模型，为卵巢癌术后治疗策略提供了新的见解，促进了个体化治疗，并为免疫治疗提供了潜在的新靶点。
Among all fatal gynecological malignant tumors, ovarian cancer has the highest mortality rate. The purpose of this study was to develop a stable and personalized glycometabolism-related prognostic signature to predict the overall survival of ovarian cancer patients. The gene expression profiles and clinical information of ovarian cancer patients were derived from four public GEO datasets, which were divided into training and testing cohorts. Glycometabolism-related genes significantly associated with prognosis were selected. A risk score model was established and validated to evaluate its predictive value. We found 5 genes significantly related to prognosis and established a five-mRNA signature. The five-mRNA signature significantly divided patients into a low-risk group and a high-risk group in the training set and validation set. Survival analysis showed that high risk scores obtained by the model were significantly correlated with adverse survival outcomes and could be regarded as an independent predictor for patients with ovarian cancer. In addition, the five-mRNA signature can predict the overall survival of ovarian cancer patients in different subgroups. In summary, we successfully constructed a model that can predict the prognosis of patients with ovarian cancer, which provides new insights into postoperative treatment strategies, promotes individualized therapy, and provides potential new targets for immunotherapy.
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