Predictive model for neoadjuvant chemotherapy combined with targeted therapy in HER2⁃positive breast cancer based on immune⁃related genes

CHEN Mengting; CHEN Fangfang; ZHANG Jingwei

doi:10.14188/j.1671-8852.2024.0721

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Predictive model for neoadjuvant chemotherapy combined with targeted therapy in HER2⁃positive breast cancer based on immune⁃related genes

更新时间：2026-11-05

- Predictive model for neoadjuvant chemotherapy combined with targeted therapy in HER2⁃positive breast cancer based on immune⁃related genes
- Medical Journal of Wuhan University Vol. 46, Issue 11, Pages: 1429-1435(2025)
- 作者机构：
  
  武汉大学中南医院甲状腺乳腺外科湖北武汉 430071
- 作者简介：
- 基金信息：
- DOI：10.14188/j.1671-8852.2024.0721
  CLC： R737.9
- Published：25 November 2025
- 稿件说明：
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陈梦婷,陈芳芳,张京伟.基于免疫相关基因的HER2阳性乳腺癌新辅助化疗联合靶向治疗疗效预测模型[J].武汉大学学报（医学版）,2025,46(11):1429-1435.

CHEN Mengting,CHEN Fangfang,ZHANG Jingwei.Predictive model for neoadjuvant chemotherapy combined with targeted therapy in HER2⁃positive breast cancer based on immune⁃related genes[J].Medical Journal of Wuhan University,2025,46(11):1429-1435.
陈梦婷,陈芳芳,张京伟.基于免疫相关基因的HER2阳性乳腺癌新辅助化疗联合靶向治疗疗效预测模型[J].武汉大学学报（医学版）,2025,46(11):1429-1435. DOI： 10.14188/j.1671-8852.2024.0721.

CHEN Mengting,CHEN Fangfang,ZHANG Jingwei.Predictive model for neoadjuvant chemotherapy combined with targeted therapy in HER2⁃positive breast cancer based on immune⁃related genes[J].Medical Journal of Wuhan University,2025,46(11):1429-1435. DOI： 10.14188/j.1671-8852.2024.0721.

摘要

目的

构建基于免疫相关基因的预测模型，评估HER2阳性乳腺癌患者新辅助化疗联合靶向治疗的疗效，并探讨与免疫微环境的关系。

方法

从GEO数据库获取新辅助化疗联合靶向治疗HER2阳性乳腺癌样本数据，结合差异基因、WGCNA挖掘的免疫相关基因模块、ImmPort数据库的免疫基因集，通过LASSO回归构建预测模型，评估不同风险组的免疫微环境和免疫治疗潜力。

结果

筛选出APOD、CCL18、CCR7、CXCL13、GDF15、IGHM、S100A8、SERPINA3八个关键基因构建的预测模型在训练集和验证集上表现出良好的预测效能，低风险组患者免疫活性较高，显示更大的免疫治疗潜力。

结论

该预测模型能够有效预测HER2阳性乳腺癌新辅助治疗效果，且免疫微环境在治疗中起重要作用。

Abstract

Objective

To construct a predictive model based on immune⁃related genes to assess the efficacy of neoadjuvant chemotherapy combined with targeted therapy in HER2⁃positive breast cancer patients and explore its association with the immune microenvironment.

Methods

The data of HER2⁃positive breast cancer samples receiving neoadjuvant chemotherapy combined with targeted therapy were obtained from the GEO database. Differentially expressed genes

immune⁃related gene modules identified by WGCNA

and immune gene sets from the ImmPort database were integrated

and a predictive model was constructed using LASSO regression. The immune microenvironment and immunotherapy potential were evaluated in different risk groups.

Results

Eight key genes (APOD

CCL18

CCR7

CXCL13

GDF15

IGHM

S100A8

SERPINA3) were selected to construct the predictive model

which showed good predictive performance in both the training and validation sets. The low⁃risk group exhibited higher immune activity and greater immune therapy potential.

Conclusion

This predictive model can effectively predict the efficacy of neoadjuvant therapy in HER2⁃positive breast cancer

and the immune microenvironment plays an important role in the treatment.

关键词

Keywords

references

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Related Institution

Dept. of Thyroid and Breast Surgery， Zhongnan Hospital of Wuhan University

Department of Gastroenterology, Wuhan Wuchang Hospital

School of Medicine, Medical College, Wuhan University of Science and Technology

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Department of Surgical Oncology, Shaanxi Provincial People's Hospital

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