Ma Jiayi, Wang Yaohui, Wu Ziping, Zhou Liheng, Lin Yanping, Xu Shuguang, Zhang Jie, Lu Jingsong, Yin Wenjin
Department of Breast Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
iScience. 2025 May 9;28(6):112620. doi: 10.1016/j.isci.2025.112620. eCollection 2025 Jun 20.
The association of immuno-inflammatory parameters, especially RBC balanced signatures, with survival outcomes and adverse events still require investigation for advanced breast cancer (ABC) patients receiving cyclin-dependent kinase 4/6 inhibitor (CDKI). Herein, RBC balanced immuno-inflammatory (RBC-IMM) score was developed and capable of predicting progression-free survival (PFS) events ( < 0.001), death ( < 0.001) and grade 3/4 leukopenia ( = 0.010). RBC-IMM score also predicted PFS more accurately than classical-IMM score (AUC = 0.766 and 0.596 respectively, = 0.005). Besides, clinico+RBC_index exhibited superior performance to clinico_index for 18-month PFS through machine learning (training set: AUC = 0.830 and 0.764 respectively; testing set: AUC = 0.894 and 0.715 respectively). Additionally, liquid chromatography-tandem mass spectrometry identified phosphatidylcholine notably involved in RBC-CDKI interaction, contributing to the construction of clinico+PtdCho_index with better PFS prediction than clinico_index (AUC = 0.854 and 0.733 respectively). These findings indicate that RBC-IMM related parameters have the advantage of identifying benefit and safety in CDKI-treated ABC patients over classical indicators.
免疫炎症参数,尤其是红细胞平衡特征,与接受细胞周期蛋白依赖性激酶4/6抑制剂(CDKI)治疗的晚期乳腺癌(ABC)患者的生存结果和不良事件之间的关联仍需研究。在此,我们开发了红细胞平衡免疫炎症(RBC-IMM)评分,该评分能够预测无进展生存(PFS)事件(<0.001)、死亡(<0.001)和3/4级白细胞减少症(=0.010)。RBC-IMM评分预测PFS的准确性也高于经典免疫炎症评分(AUC分别为0.766和0.596,=0.005)。此外,通过机器学习,临床+RBC指数在预测18个月PFS方面表现优于临床指数(训练集:AUC分别为0.830和0.764;测试集:AUC分别为0.894和0.715)。此外,液相色谱-串联质谱法鉴定出磷脂酰胆碱显著参与红细胞-CDKI相互作用,有助于构建临床+磷脂酰胆碱指数,其预测PFS的能力优于临床指数(AUC分别为0.854和0.733)。这些发现表明,与红细胞免疫炎症相关的参数在识别接受CDKI治疗的ABC患者的获益和安全性方面比传统指标更具优势。