Identification and Validation of Novel Metastasis-Related Immune Gene Signature in Breast Cancer

IF 3.3 4区 医学 Q2 ONCOLOGY Breast Cancer : Targets and Therapy Pub Date : 2024-04-01 DOI:10.2147/BCTT.S448642
Shen Ma, Ran Hao, Yi-Wei Lu, Hui-Po Wang, Jie Hu, Yi-Xin Qi
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Abstract

Background Distant metastasis remains the leading cause of death among patients with breast cancer (BRCA). The process of cancer metastasis involves multiple mechanisms, including compromised immune system. However, not all genes involved in immune function have been comprehensively identified. Methods Firstly 1623 BRCA samples, including transcriptome sequencing and clinical information, were acquired from Gene Expression Omnibus (GSE102818, GSE45255, GSE86166) and The Cancer Genome Atlas-BRCA (TCGA-BRCA) dataset. Subsequently, weighted gene co-expression network analysis (WGCNA) was performed using the GSE102818 dataset to identify the most relevant module to the metastasis of BRCA. Besides, ConsensusClusterPlus was applied to divide TCGA-BRCA patients into two subgroups (G1 and G2). In the meantime, the least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a metastasis-related immune genes (MRIGs)_score to predict the metastasis and progression of cancer. Importantly, the expression of vital genes was validated through reverse transcription quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC). Results The expression pattern of 76 MRIGs screened by WGCNA divided TCGA-BRCA patients into two subgroups (G1 and G2), and the prognosis of G1 group was worse. Also, G1 exhibited a higher mRNA expression level based on stemness index score and Tumor Immune Dysfunction and Exclusion score. In addition, higher MRIGs_score represented the higher probability of progression in BRCA patients. It was worth mentioning that the patients in the G1 group had a high MRIGs_score than those in the G2 group. Importantly, the results of RT-qPCR and IHC demonstrated that fasciculation and elongation protein zeta 1 (FEZ1) and insulin-like growth factor 2 receptor (IGF2R) were risk factors, while interleukin (IL)-1 receptor antagonist (IL1RN) was a protective factor. Conclusion Our study revealed a prognostic model composed of eight immune related genes that could predict the metastasis and progression of BRCA. Higher score represented higher metastasis probability. Besides, the consistency of key genes in BRCA tissue and bioinformatics analysis results from mRNA and protein levels was verified.
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乳腺癌转移相关免疫基因新特征的鉴定与验证
背景远处转移仍然是乳腺癌(BRCA)患者死亡的主要原因。癌症转移过程涉及多种机制,包括免疫系统受损。然而,并非所有参与免疫功能的基因都已被全面鉴定。方法 首先从基因表达总库(GSE102818、GSE45255、GSE86166)和癌症基因组图谱-BRCA(TCGA-BRCA)数据集中获取了1623个BRCA样本,包括转录组测序和临床信息。随后,利用 GSE102818 数据集进行了加权基因共表达网络分析(WGCNA),以确定与 BRCA 转移最相关的模块。此外,还应用 ConsensusClusterPlus 将 TCGA-BRCA 患者分为两个亚组(G1 和 G2)。同时,利用最小绝对收缩和选择算子(LASSO)回归分析构建了转移相关免疫基因(MRIGs)_评分,以预测癌症的转移和进展。重要的是,重要基因的表达通过反转录定量聚合酶链反应(RT-qPCR)和免疫组化(IHC)进行了验证。结果 WGCNA 筛选出的 76 个 MRIGs 的表达模式将 TCGA-BRCA 患者分为两个亚组(G1 和 G2),G1 组的预后较差。同时,根据干性指数评分和肿瘤免疫功能障碍与排斥评分,G1 组的 mRNA 表达水平更高。此外,MRIGs_score越高,代表BRCA患者病情恶化的概率越高。值得一提的是,G1 组患者的 MRIGs_score 比 G2 组高。重要的是,RT-qPCR 和 IHC 的结果表明,束状和伸长蛋白 zeta 1(FEZ1)和胰岛素样生长因子 2 受体(IGF2R)是风险因素,而白细胞介素(IL)-1 受体拮抗剂(IL1RN)是保护因素。结论 我们的研究揭示了一个由八个免疫相关基因组成的预后模型,该模型可预测 BRCA 的转移和进展。得分越高,代表转移的可能性越大。此外,研究还验证了 BRCA 组织中关键基因的一致性以及 mRNA 和蛋白质水平的生物信息学分析结果。
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来源期刊
CiteScore
4.10
自引率
0.00%
发文量
40
审稿时长
16 weeks
期刊最新文献
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