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靶向分子治疗对乳腺癌免疫浸润的益处及预测特征的免疫相关基因

英文原题:Benefits of Targeted Molecular Therapy to Immune Infiltration and Immune-Related Genes Predicting Signature in Breast Cancer.

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Benefits of Targeted Molecular Therapy to Immune Infiltration and Immune-Related Genes Predicting Signature in Breast Cancer.

PubMed 2022/03/04(内容时间) Front Oncol Q2 · IF 3.4(JCR 2025)

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研究概要

本研究基于乳腺癌组织中肿瘤相关浸润淋巴细胞,深入探讨了免疫评分,并证明了免疫浸润对曲妥珠单抗治疗的益处。同时,该研究建立了一个新的五免疫相关基因特征,用于预测接受曲妥珠单抗治疗的乳腺癌的 OS 和 BCSS。

研究思路结论见上方概要

本研究旨在探讨影响曲妥珠单抗应答的肿瘤相关浸润淋巴细胞(TILs),并基于免疫相关基因识别潜在的生物标志物,以改善乳腺癌靶向治疗的预后和临床结局。

采用表达数据估计恶性肿瘤中的基质细胞和免疫细胞(ESTIMATE)方法,通过利用乳腺肿瘤样本中的基因表达特征来推断基质细胞和免疫细胞的比例。应用通过估计RNA转录本相对亚群进行细胞类型鉴定(CIBERSORT)算法,利用乳腺癌组织的基因表达谱来表征22种淋巴细胞的细胞组成。从免疫学数据库和分析门户(ImmPort)中收集免疫相关基因。进行单因素和多因素Cox回归分析,以确定与乳腺癌患者较差的总生存期(OS)和乳腺癌特异性生存期(BCSS)相关的显著独立危险因素。基于蛋白质-蛋白质相互作用(PPI)网络分析鉴定枢纽基因。

基于ESTIMATE算法,与相应非肿瘤组织和治疗后肿瘤组织相比,肿瘤组织和治疗前肿瘤组织中的基质评分显著降低,而免疫评分在两组之间未能呈现显著的统计学差异。然而,根据单因素Cox回归分析的结果,免疫评分被鉴定为与乳腺癌患者较差的OS显著相关。随后,基于CIBERSORT算法评估了肿瘤组织中的浸润淋巴细胞。此外,显著性分析从GSE114082数据集中鉴定出1,244个差异表达基因(DEGs),然后在GSE114082和ImmPort数据集之间筛选出91个重叠的免疫相关DEGs。随后,鉴定出10个顶级枢纽基因,其中五个(IGF1、ADIPOQ、PPARG、LEP和NR3C1)与乳腺癌患者对曲妥珠单抗响应中较差的OS和BCSS显著相关。

展开英文摘要原文

This study aimed to investigate the tumor-related infiltrating lymphocytes (TILs) affecting the response of trastuzumab and identify potential biomarkers based on immune-related genes to improve prognosis and clinical outcomes of targeted therapies in breast cancer.

Estimation of stromal and immune cells in malignant tumors using expression data (ESTIMATE) was adopted to infer the fraction of stromal and immune cells through utilizing gene expression signatures in breast tumor samples. Cell-type identification by estimating relative subsets of RNA transcript (CIBERSORT) algorithm was applied to characterize cell composition of 22 lymphocytes from breast cancer tissues using their gene expression profiles. Immune-related genes were collected from the Immunology Database and Analysis (ImmPort). Univariate and multivariate Cox regression analyses were performed to identify the significant independent risk factors associated with poor overall survival (OS) and breast cancer-specific survival (BCSS) of breast cancer patients. Hub genes were identified based on the protein-protein interaction (PPI) network analysis.

Based on the ESTIMATE algorithm, a significant reduction of stromal scores was observed in tumor tissues and pretreated tumor tissues compared with nontumor and posttreated tumor tissues, respectively, while immune scores failed to present notably statistical differences between both groups. However, from the results of the univariate Cox regression analysis, the immune score was identified to be remarkably associated with the poor OS for breast cancer patients. Subsequently, the infiltrating lymphocytes were evaluated in tumor tissues based on the CIBERSORT algorithm. Furthermore, significance analysis identified 1,244 differentially expressed genes (DEGs) from the GSE114082 dataset, and then 91 overlapping immune-related DEGs were screened between GSE114082 and ImmPort datasets. Subsequently, 10 top hub genes were identified and five (IGF1, ADIPOQ, PPARG, LEP, and NR3C1) significantly correlated with worse OS and BCSS on response to trastuzumab in breast cancer patients.

This study provided an insight into the immune score based on the tumor-related infiltrating lymphocytes in breast cancer tissues and demonstrates the benefits of immune infiltration on the treatment of trastuzumab. Meanwhile, the study established a novel five immune-related gene signature to predict the OS and BCSS of breast cancer treated by trastuzumab.

论文信息

作者
Chen F、Fang J
第一作者单位
CEO Office, RemeGen Co. Ltd., Yantai, China.China
通讯作者单位
School of Life Science and Technology, Tongji University, Shanghai, China.China
期刊
Frontiers in oncology2022
原文标识
PubMed 35317079 · DOI 10.3389/fonc.2022.824166