Chen Yang, Xie Lizhi, Tang Wei, Xiao Qin, Liu Li, Xie Tianwen, Huang Yan, Wang Qifeng, Yu Keda, Gu Yajia, Peng Weijun
Department of Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.
Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
Cancer Med. 2025 Sep;14(17):e71172. doi: 10.1002/cam4.71172.
Oncotype DX 21-gene assays are recommended for evaluating distant recurrence and guiding decisions on the use of adjuvant therapy in ER+/HER2- breast cancers. However, it cannot be widely applied due to the high cost and time consumption.
To identify MRI radiomics signatures within tumor and peritumoral tissues associated with the 21-gene recurrence score (RS) and explore their value in predicting 5-year recurrence in young women with ER+/HER2- breast cancer.
Two datasets were analyzed; all the enrolled patients were diagnosed with ER+/HER2- breast cancers and underwent preoperative breast MRIs. The radiogenomic development dataset, with RS data obtained from April 2017 to March 2019, was used to identify optimal RS-signatures based on tumoral, peritumoral, and dilation radiomics features as well as clinical-imaging characteristics with the support vector machine method. The prognosis dataset, in which patients aged 18 to 40 years received breast surgery followed by adjuvant chemotherapy from 2012 to 2016, was used to evaluate the prognostic implication of the proposed optimal RS-signatures by measuring 5-year disease-free survival (DFS) with the Cox proportional hazards model.
159 patients (111 in the training and 48 in the validation groups) and 111 young patients (a mean follow-up time of 49.6 months and a 5-year DFS of 83.8%) were enrolled in these datasets, respectively. Areas under the receiver operating characteristic curve (AUCs) of the three optimal RS-signatures were 0.74 (95% CI: 0.59-0.87), 0.75 (95% CI: 0.61-0.88) and 0.74 (95% CI: 0.59-0.87) respectively. In the prognosis dataset, there were significant differences in survival between the patients in the predicted high-risk and low-risk groups categorized by the above three signatures, and the predicted recurrence risks were independent factors for DFS.
The radiomic signatures within the tumor and peritumoral region exhibited potential to guide decisions on the use of chemotherapy and predict survival.
Oncotype DX 21基因检测推荐用于评估雌激素受体阳性（ER+）/人表皮生长因子受体2阴性（HER2-）乳腺癌的远处复发情况，并指导辅助治疗的决策。然而，由于成本高和耗时，它无法广泛应用。
识别肿瘤及瘤周组织内与21基因复发评分（RS）相关的MRI影像组学特征，并探讨其在预测ER+/HER2-年轻乳腺癌患者5年复发情况中的价值。
分析两个数据集；所有入组患者均被诊断为ER+/HER2-乳腺癌，并接受了术前乳腺MRI检查。放射基因组学开发数据集（其RS数据获取时间为2017年4月至2019年3月）用于基于肿瘤、瘤周及扩张影像组学特征以及临床影像特征，采用支持向量机方法识别最佳RS特征。预后数据集（其中18至40岁的患者在2012年至2016年接受了乳腺手术及辅助化疗）用于通过Cox比例风险模型测量5年无病生存率（DFS），以评估所提出的最佳RS特征的预后意义。
这些数据集中分别纳入了159例患者（训练组111例，验证组48例）和111例年轻患者（平均随访时间49.6个月，5年DFS为83.8%）。三个最佳RS特征的受试者工作特征曲线下面积（AUC）分别为0.74（95%可信区间：0.59 - 0.87）、0.75（95%可信区间：0.61 - 0.88）和0.74（95%可信区间：0.59 - 0.87）。在预后数据集中，根据上述三个特征分类的预测高风险组和低风险组患者的生存率存在显著差异，且预测的复发风险是DFS的独立因素。
肿瘤及瘤周区域的影像组学特征在指导化疗决策和预测生存方面具有潜力。
