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活性氧物种评分系统预测卵巢癌患者对顺铂的敏感性和预后。

A reactive oxygen species scoring system predicts cisplatin sensitivity and prognosis in ovarian cancer patients.

机构信息

Cancer Biology Research Center (Key laboratory of Chinese Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.

Department of Gynecology and Obstetrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.

出版信息

BMC Cancer. 2019 Nov 8;19(1):1061. doi: 10.1186/s12885-019-6288-7.

DOI:10.1186/s12885-019-6288-7
PMID:31703584
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6839150/
Abstract

BACKGROUND

To reveal roles of reactive oxygen species (ROS) status in chemotherapy resistance and to develop a ROS scoring system for prognosis prediction in ovarian cancer.

METHODS

We tested the sensitizing effects of ROS elevating drugs to cisplatin (cDDP) in ovarian cancer both in vitro and in vivo. A ROS scoring system was developed using The Cancer Genome Atlas (TCGA) database of ovarian cancer. The associations between ROS scores and overall survival (OS) were analyzed in TCGA, Tothill dataset, and our in-house dataset (TJ dataset).

RESULTS

ROS-inducing drugs increased cisplatin-induced ovarian cancer cell injury in vitro and in vivo. ROS scoring system was established using 25 ROS-related genes. Patients were divided into low (scores 0-12) and high (scores 13-25) score groups. Improved patient survival was associated with higher scores (TCGA dataset hazard ratio (HR) = 0.43, P < 0.001; Tothill dataset HR = 0.65, P = 0.022; TJ dataset HR = 0.40, P = 0.003). The score was also significantly associated with OS in multiple datasets (TCGA dataset r = 0.574, P = 0.032; Thothill dataset r = 0.266, P = 0.049; TJ dataset r = 0.632, P = 0.001) and with cisplatin sensitivity in ovarian cancer cell lines (r = 0.799, P = 0.016) when used as a continuous variable. The scoring system showed better prognostic performance than other clinical factors by receiver operating characteristic (ROC) curves (TCGA dataset area under the curve (AUC) = 0.71 v.s. 0.65, Tothill dataset AUC = 0.73 v.s. 0.67, TJ dataset AUC = 0.74 v.s. 0.66).

CONCLUSIONS

ROS status is associated with chemotherapy resistance. ROS score system might be a prognostic biomarker in predicting the survival benefit from ovarian cancer patients.

摘要

背景

揭示活性氧(ROS)状态在化疗耐药中的作用,并开发一种用于预测卵巢癌预后的 ROS 评分系统。

方法

我们在体外和体内测试了 ROS 升高药物对顺铂(cDDP)的增敏作用。使用卵巢癌的癌症基因组图谱(TCGA)数据库开发了 ROS 评分系统。在 TCGA、Tothill 数据集和我们的内部数据集(TJ 数据集)中分析了 ROS 评分与总生存期(OS)之间的关联。

结果

ROS 诱导药物增加了体外和体内顺铂诱导的卵巢癌细胞损伤。使用 25 个 ROS 相关基因建立了 ROS 评分系统。患者被分为低(评分 0-12)和高(评分 13-25)评分组。较高的评分与患者生存改善相关(TCGA 数据集风险比(HR)=0.43,P<0.001;Tothill 数据集 HR=0.65,P=0.022;TJ 数据集 HR=0.40,P=0.003)。该评分在多个数据集(TCGA 数据集 r=0.574,P=0.032;Tothill 数据集 r=0.266,P=0.049;TJ 数据集 r=0.632,P=0.001)中与 OS 显著相关,并且在作为连续变量使用时与卵巢癌细胞系的顺铂敏感性相关(r=0.799,P=0.016)。评分系统通过接收者操作特征(ROC)曲线显示出比其他临床因素更好的预后性能(TCGA 数据集 AUC=0.71 v.s. 0.65,Tothill 数据集 AUC=0.73 v.s. 0.67,TJ 数据集 AUC=0.74 v.s. 0.66)。

结论

ROS 状态与化疗耐药有关。ROS 评分系统可能是预测卵巢癌患者生存获益的预后生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fc3/6839150/b4763304c7bb/12885_2019_6288_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fc3/6839150/6d66816bdf08/12885_2019_6288_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fc3/6839150/c6db9ae105f0/12885_2019_6288_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fc3/6839150/1624c25df395/12885_2019_6288_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fc3/6839150/cba7824d3d24/12885_2019_6288_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fc3/6839150/b4763304c7bb/12885_2019_6288_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fc3/6839150/6d66816bdf08/12885_2019_6288_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fc3/6839150/c6db9ae105f0/12885_2019_6288_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fc3/6839150/1624c25df395/12885_2019_6288_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fc3/6839150/cba7824d3d24/12885_2019_6288_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fc3/6839150/b4763304c7bb/12885_2019_6288_Fig5_HTML.jpg

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