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一个基于代谢相关基因的预后模型,用于卵巢癌患者

Dong Jian¹, Zhai Lianghao¹, Gao Yunge¹

¹Department of Gynecology and Obstetrics, Xijing Hospital, Fourth Military Medical University, 710032, Shaanxi Xi'an, China.

Doklady. Biochemistry and biophysics

|August 15, 2023

概括

使用代谢相关基因 (MAG) 的新预后模型可以预测卵巢癌 (OC) 患者的结果. 该模型识别了高风险和低风险群体,有助于为OC提供个性化治疗策略.

科学领域:

在瘤学瘤学.
遗传学是一个遗传学.
分子生物学分子生物学

背景情况:

代谢相关基因 (MAGs) 在瘤进展和生理调节中起着至关重要的作用.
了解MAG在卵巢癌 (OC) 中的作用对于改善患者预后至关重要.

研究的目的:

为了研究MAG和卵巢癌 (OC) 预后之间的关系.
基于MAGs,开发OC患者预测结果的预测模型.

主要方法:

从癌症基因组图谱 (TCGA) 数据库中提取了与代谢相关的基因.
使用单变量COX和LASSO回归模型建立基于MAG的动态风险模型.
在临床OC样本中验证了MAG表达.

主要成果:

一个3-MAG签名 (PTGIS,AOC3,IDO1) 是使用Lasso-Cox回归来构建的.
根据签名,OC患者被分为高风险和低风险组.
与高风险组相比,低风险组的整体存活率明显更好.
贝瓦西祖马布治疗没有改善低风险组的预后.

结论:

基于MAG的预后模型成功地为OC开发.
该模型显示了预测OC患者预后的潜力.
这种预后模型可以指导OC患者的个性化治疗决策.

关键词:

贝瓦西祖马布 (bevacizumab) 是一种药物.与新陈代谢相关的基因卵巢癌是发生在卵巢中的癌症.预测预后预测预测风险因素的风险因素是什么

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