The signature of SARS-CoV-2-related genes predicts the immune therapeutic response and prognosis in breast cancer.

IF 2.1 4区 医学 Q3 GENETICS & HEREDITY BMC Medical Genomics Pub Date : 2024-10-31 DOI:10.1186/s12920-024-02032-0
Ruizhi Fu, Yequn Chen, Jiajing Zhao, Xiaojun Xie
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Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an exceptionally contagious single-stranded RNA virus with a strong positive contagion. The COVID-19 pandemic refers to the swift worldwide dissemination of SARS-CoV-2 infection, which began in late 2019. The COVID-19 epidemic has disrupted many cancer treatments. A few reports indicate that the prevalence of SARS-CoV-2 has disrupted the treatment of breast cancer patients (BCs). However, the role of SARS-CoV-2 in the occurrence and prognosis of BC has not been elucidated. Here, we applied bioinformatics to construct a prognostic signature of SARS-CoV-2-related genes (SCRGs). Specifically, weighted gene co-expression network analysis (WGCNA) was utilized to extract co-expressed genes of differentially expressed genes (DEGs) in breast cancer and SCRGs. Then, we utilized the least absolute shrinkage and selection operator (LASSO) algorithm and univariate regression analysis to screen out three hub genes (DCTPP1, CLIP4 and ANO6) and constructed a risk score model. We further analyzed tumor immune invasion, HLA-related genes, immune checkpoint inhibitors (ICIs), and sensitivity to anticancer drugs in different SARS-CoV-2 related risk subgroups. In addition, we have developed a nomination map to expand clinical applicability. The results of our study indicate that BCs with a high-risk score are linked to negative outcomes, lower immune scores, and reduced responsiveness to anticancer medications. This suggests that the SARS-CoV-2 related signature could be used to guide prognosis assessment and treatment decisions for BCs.

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SARS-CoV-2相关基因的特征可预测乳腺癌的免疫治疗反应和预后。
严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2)是一种传染性极强的单链 RNA 病毒,具有很强的阳性传染性。COVID-19大流行指的是SARS-CoV-2感染从2019年末开始在全球范围内迅速传播。COVID-19 的流行扰乱了许多癌症治疗。一些报告指出,SARS-CoV-2 的流行扰乱了乳腺癌患者(BCs)的治疗。然而,SARS-CoV-2 在乳腺癌的发生和预后中的作用尚未阐明。在此,我们应用生物信息学构建了SARS-CoV-2相关基因(SCRGs)的预后特征。具体来说,我们利用加权基因共表达网络分析(WGCNA)来提取乳腺癌和SCRGs中差异表达基因(DEGs)的共表达基因。然后,我们利用最小绝对收缩和选择算子(LASSO)算法和单变量回归分析筛选出三个枢纽基因(DCTPP1、CLIP4和ANO6),并构建了风险评分模型。我们进一步分析了不同SARS-CoV-2相关风险亚组的肿瘤免疫侵袭、HLA相关基因、免疫检查点抑制剂(ICIs)以及对抗癌药物的敏感性。此外,我们还绘制了一张提名图,以扩大临床适用性。我们的研究结果表明,高风险评分的 BCs 与负面结果、较低的免疫评分和对抗癌药物的反应性降低有关。这表明,SARS-CoV-2 相关特征可用于指导 BCs 的预后评估和治疗决策。
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来源期刊
BMC Medical Genomics
BMC Medical Genomics 医学-遗传学
CiteScore
3.90
自引率
0.00%
发文量
243
审稿时长
3.5 months
期刊介绍: BMC Medical Genomics is an open access journal publishing original peer-reviewed research articles in all aspects of functional genomics, genome structure, genome-scale population genetics, epigenomics, proteomics, systems analysis, and pharmacogenomics in relation to human health and disease.
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