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识别用于预测三阴性乳腺癌早期复发风险和免疫细胞浸润程度的基因表达特征

英文原题:Identification of a Gene Expression Signature to Predict the Risk of Early Recurrence and the Degree of Immune Cell Infiltration in Triple-negative Breast Cancer.

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Identification of a Gene Expression Signature to Predict the Risk of Early Recurrence and the Degree of Immune Cell Infiltration in Triple-negative Breast Cancer.

PubMed 2024/05/01(内容时间) Cancer Genomics Proteomics Q2 · IF 2.6(JCR 2025)

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研究概要

本文报道的基因可能是有效的生物标志物,用于识别将从免疫治疗中获益和不会获益的 TNBC 患者,并且可能是开发未来治疗策略(包括免疫治疗)特别重要的基因。

研究思路结论见上方概要

三阴性乳腺癌(TNBC)患者与其他亚型相比,诊断后3年内复发率高,5年内死亡率高。近年来,研究各种新药和联合疗法的临床试验数量有所增加;然而,当前策略仅使少数患者获益。本研究旨在识别能够预测高复发风险患者的具体基因以及早期肿瘤微环境的免疫状态,从而为改善TNBC患者临床结局的潜在治疗靶点提供见解。

我们评估了METABRIC数据集中233例TNBC患者20,603个基因的微阵列mRNA表达的预后意义,并进一步使用GSE96058数据集中143例TNBC患者的RNA-seq mRNA表达数据验证了结果。

在两个数据集中鉴定出的18个差异表达基因(AKNA、ARHGAP30、CA9、CD3D、CD3G、CD6、CXCR6、CYSLTR1、DOCK10、ENO1、FLT3LG、IFNG、IL2RB、LPXN、PRKCB、PVRIG、RASSF5和STAT4)被发现是预测TNBC复发和进展的可靠生物标志物。值得注意的是,低表达与复发和死亡风险增加相关的基因是免疫相关基因,高表达组和低表达组之间肿瘤微环境中免疫细胞浸润水平存在显著差异。

展开英文摘要原文

We evaluated the prognostic significance of microarray mRNA expression of 20,603 genes in 233 TNBC patients from the METABRIC dataset and further validated the results using RNA-seq mRNA expression data in 143 TNBC patients from the GSE96058 dataset.

Eighteen differentially expressed genes (AKNA, ARHGAP30, CA9, CD3D, CD3G, CD6, CXCR6, CYSLTR1, DOCK10, ENO1, FLT3LG, IFNG, IL2RB, LPXN, PRKCB, PVRIG, RASSF5, and STAT4) identified in both datasets were found to be reliable biomarkers for predicting TNBC recurrence and progression. Notably, the genes whose low expression was associated with increased risk of recurrence and death were immune-related genes, with significant differences in levels of immune cell infiltration in the tumor microenvironment between high- and low- expression groups.

Genes reported herein may be effective biomarkers to identify TNBC patients who will and will not benefit from immunotherapy and may be particularly important genes for developing future treatment strategies, including immunotherapy.

论文信息

作者
Sato K、Miura K、Tamori S、Akimoto K
单位
Department of Information Sciences, Faculty of Science and Technology, Tokyo University of Science, Chiba, Japan; keiko@is.noda.tus.ac.jp.Japan
期刊
Cancer genomics & proteomics2024 May-Jun
原文标识
PubMed 38670590 · DOI 10.21873/cgp.20450