A generalized non-linear model predicting efficacy of neoadjuvant therapy in HER2+ breast cancer

预测HER2阳性乳腺癌新辅助治疗疗效的广义非线性模型

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作者:Yusong Wang,Xiaoyan Liu,Keda Yu,Shouping Xu,Pengfei Qiu,Xinwen Zhang,Mozhi Wang,Yingying Xu

Abstract

Neoadjuvant therapy (NAT) is currently recommended to patients with human epidermal growth factor receptor 2-positive breast cancer (HER2+ BC) that typically exhibit a poor prognosis. The tumor immune microenvironment profoundly affects the efficacy of NAT. However, the correlation between tumor-infiltrating lymphocytes or their specific subpopulations and the response to NAT in HER2+ BC remains largely unknown. In our study, the immune infiltration status of 295 patients was classified as "immune-rich" or "immune-poor" phenotypes. The "immune-rich" phenotype was significantly positively related to pathological complete response (pCR). Ten genes were correlated with both pCR and the immune phenotype based on the results of spline and logistic regression. We constructed a generalized non-linear model combining linear and non-linear gene effects and successfully validated its predictive power using an internal and external validation set (AUC = 0.819, 0.797; respectively) and a clinical set (accuracy = 0.75).

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