中国癌症杂志 ›› 2023, Vol. 33 ›› Issue (5): 484-498.doi: 10.19401/j.cnki.1007-3639.2023.05.009

• 论著 • 上一篇    下一篇

基于免疫微环境特征的曲妥珠单抗与免疫治疗联合应用预测模型

杨闻箫1,2(), 国琳玮3, 凌泓1, 胡欣1,2()   

  1. 1.复旦大学附属肿瘤医院乳腺外科,复旦大学上海医学院肿瘤学系,上海 200032
    2.复旦大学附属肿瘤医院精准肿瘤中心,复旦大学上海医学院肿瘤学系,上海 200032
    3.复旦大学附属肿瘤医院大肠外科,复旦大学上海医学院肿瘤学系,上海 200032
  • 收稿日期:2023-01-31 修回日期:2023-04-26 出版日期:2023-05-30 发布日期:2023-06-16
  • 通信作者: 胡欣(ORCID: 0000-0002-8160-8362),博士,研究员。
  • 作者简介:杨闻箫(ORCID: 0009-0007-0239-4671),硕士。

Characterization of immune microenvironment identifies prognostic and immunotherapy benefit for trastuzumab-based therapy

YANG Wenxiao1,2(), GUO Linwei3, LING Hong1, HU Xin1,2()   

  1. 1. Department of Breast Surgery, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
    2. Precision Cancer Medicine Center, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
    3. Department of Colorectal Surgery, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
  • Received:2023-01-31 Revised:2023-04-26 Published:2023-05-30 Online:2023-06-16
  • Contact: HU Xin

摘要:

背景与目的:人表皮生长因子受体2(human epidermal growth factor receptor 2,HER2)阳性乳腺癌患者的肿瘤免疫微环境(tumor immune microenvironment,TIME)与曲妥珠单抗治疗效果显著相关,提示免疫检查点疗法联合曲妥珠单抗治疗的临床潜力。本研究旨在探索HER2阳性乳腺癌联合治疗的预测因子,筛选联合治疗的潜在获益人群。方法:纳入高通量基因表达(Gene Expression Omnibus,GEO)数据库中509例接受曲妥珠单抗治疗的HER2阳性乳腺癌患者和癌症基因组图谱(The Cancer Genome Atlas,TCGA)数据库中67例HER2阳性乳腺癌患者的转录组与基因组数据,筛选曲妥珠单抗耐药组的差异表达基因进行功能富集分析、蛋白质互作网络构建。结合临床信息通过对数秩检验和多因素COX比例风险回归模型构建预测模型。并利用CIBERSORT反卷积法分析TIME特征,通过肿瘤免疫功能障碍和排斥(tumor immune dysfunction and exclusion,TIDE)评分预测免疫治疗获益。结果:通过分析曲妥珠单抗缓解组和曲妥珠单抗耐药组之间的免疫微环境与基因表达特征,构建了由4个核心基因(GATA6、TRPV6、AMACRZHX2)组成的曲妥珠单抗相关基因预测指数(trastuzumab related genetic prognostic index,TRGPI)。低TRGPI评分的患者的TIME含有更高比例的CD8+ T淋巴细胞和激活的自然杀伤细胞,同时程序性死亡[蛋白]-1(programmed death-1,PD-1)的表达更高,更倾向于从曲妥珠单抗联合免疫治疗中获益。结论:本研究基于TIME重新定义了HER2阳性乳腺癌曲妥珠单抗联合免疫治疗的获益人群,并为临床应用提供了可选的治疗策略。

关键词: 肿瘤免疫微环境, 曲妥珠单抗, 免疫治疗, 人表皮生长因子受体2阳性乳腺癌, 预测模型

Abstract:

Background and Purpose: The tumor immune microenvironment (TIME) of breast cancer with positive human epidermal growth factor receptor 2 (HER2) is significantly related to the efficacy of trastuzumab, indicating the clinical potential of immunocheckpoint therapy combined with trastuzumab. This study aimed to explore the predictors of HER2-positive breast cancer combination therapy and screen the potential beneficiaries of combination therapy. Methods: Transcriptome and genome data of 509 HER2-positive breast cancer samples of patients receiving trastuzumab treatment from Gene Expression Omnibus (GEO) database and 67 HER2-positive breast cancer samples from The Cancer Genome Atlas (TCGA) databases were collected. Trastuzumab-resistant group’s differentially expressed genes were identified and analyzed for functional enrichment and protein-protein interaction. The log-rank test and multivariate COX proportional hazards regression were used with clinical data to create the prediction model. The TIME landscape was characterized using the CIBERSORT. The immunotherapy benefit was valued by the tumor immune dysfunction and exclusion (TIDE) score. Results: The trastuzumab related genetic prognostic index (TRGPI) consisting of four hub genes (GATA6, TRPV6, AMACR, ZHX2) was constructed by analyzing the immune microenvironment and gene expression characteristics between trastuzumab-remission group and trastuzumab-resistance group. Importantly, the results revealed that patients with lower TRPGI were trastuzumab-sensitive and more likely to benefit from immunotherapy because of the increased percentages of CD8+ T cells, active natural killer cells and programmed death-1 (PD-1) expression. Conclusion: This study redefined the benefit population through TIME and provided a selectable strategy of trastuzumab plus immunotherapy for HER2-positive breast cancer.

Key words: Tumor immune microenvironment, Trastuzumab, Immunotherapy, Human epidermal growth factor receptor 2-positive breast cancer, Prediction model

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