靶向测序的体细胞突变在晚期卵巢透明细胞癌中的风险分层
Somatic mutation of targeted sequencing identifies risk stratification in advanced ovarian clear cell carcinoma
DOI 原文链接
用sci-hub下载
如无法下载，请从 Sci-Hub 选择可用站点尝试。
影响因子:4.1
分区:医学2区 Top / 妇产科学1区 肿瘤学2区
发表日期:2024 Dec
作者:
Shimeng Wan, Yang Gao, Sisi Wu, Hua Wang, Jiyu Tong, Wei Wei, Hang Ren, Danni Yang, Hao He, Hong Ye, Hongbing Cai
DOI:
10.1016/j.ygyno.2024.09.017
摘要
卵巢透明细胞癌（OCCC）是上皮性卵巢癌的一个独特亚型。晚期OCCC表现出预后较差。因此，我们旨在进行精确医学的风险分层。我们对44例FIGO II-IV期OCCC患者进行了大规模的下一代测序（NGS）基因面板分析。随后，利用极端梯度提升（XGBoost）、随机生存森林（RSF）和Cox回归等机器学习算法筛选出与预后相关的特征基因，并构建了一个包括5个基因的风险分层模型。该5基因模型的预测效果通过受试者工作特征（ROC）曲线和决策曲线分析与FIGO分期和残余病灶进行了比较。由机器学习算法筛选出的与预后相关的突变基因，包括MUC16、ATM、NOTCH3、KMT2A和CTNNA1。该5基因模型能有效区分晚期OCCC患者的预后和铂类药物反应，在内外验证队列中均表现出优越的预测能力，优于FIGO分期和残余病灶。MUC16、ATM、NOTCH3、KMT2A和CTNNA1等基因的突变与晚期OCCC的不良预后相关。基于这些基因的风险分层展现出较为理想的预后和铂类药物反应的预测能力，提示其具有作为精准医学新靶点的潜力。
Abstract
Ovarian clear cell carcinoma (OCCC) is a unique subtype of epithelial ovarian cancer. Advanced OCCC display a poor prognosis. Therefore, we aimed to make risk stratification for precise medicine.We performed a large next generation sequencing (NGS) gene panel on 44 patients with OCCC in FIGO stage II-IV. Then, by machine learning algorithms, including extreme gradient boosting (XGBoost), random survival forest (RSF), and Cox regression, we screened for feature genes associated with prognosis and constructed a 5-gene panel for risk stratification. The prediction efficacy of the 5-gene panel was compared with FIGO stage and residual disease by receiver operating characteristic curve and decision curve analysis.The feature mutated genes related to prognosis, selected by machine learning algorithms, include MUC16, ATM, NOTCH3, KMT2A, and CTNNA1. The 5-gene panel can effectively distinguish the prognosis, as well as platinum response, of advanced OCCC in both internal and external cohorts, with the predictive capability superior to FIGO stage and residual disease.Mutations in genes, including MUC16, ATM, NOTCH3, KMT2A, and CTNNA1, were associated with the poor prognosis of advanced OCCC. The risk stratification according to these genes demonstrated acceptable prediction power of prognosis and platinum response, suggesting the potential to be a novel target for precision medicine.