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铜死亡相关长链非编码RNA特征的综合分析及乳腺癌患者的个性化治疗策略

Comprehensive analysis of cuproptosis-related long non-coding RNA signature and personalized therapeutic strategy of breast cancer patients.

作者信息

Guo Qiaonan, Qiu Pengjun, Pan Kelun, Lin Jianqing

机构信息

Department of Breast and Thyroid Surgery, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, China.

出版信息

Front Oncol. 2022 Dec 22;12:1081089. doi: 10.3389/fonc.2022.1081089. eCollection 2022.

Abstract

BACKGROUND

Breast cancer (BC) is considered to be one of the primary causes of cancer deaths in women. Cuproptosis was suggested to play an important role in tumor proliferation and tumor immune microenvironment. Therefore, an investigation was conducted to identify the relationship between cuproptosis-related long non-coding RNAs (lncRNAs) and BC prognosis.

METHOD

Based on The Cancer Genome Atlas (TCGA), nine cuproptosis-related lncRNAs were identified by Pearson's analysis and Cox regression analysis to create a cuproptosis-related lncRNA signature. Subsequently, patients with BC were divided into high-risk and low-risk groups. The Kaplan-Meier curves and a time-dependent receiver operating characteristic (ROC) analysis were employed to elucidate the predictive capability of the signature. After that, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted by Gene Set Enrichment Analysis (GSEA), and the lncRNA-mRNA co-expression network was established by Cytoscape software. Furthermore, the ESTIMATE score was calculated, and the immune cell type component analysis was conducted. Eventually, immunotherapy response analysis was applied to identify the predictive power of cuproptosis-related lncRNAs to tumor immunotherapy response, including immune checkpoint gene expression levels, tumor mutational burden (TMB), and microsatellite instability (MSI).

RESULTS

Patients with BC in the low-risk groups showed better clinical outcomes. The KEGG pathways in the high-risk groups were mainly enriched in immune response and immune cell activation. Furthermore, the ESTIMATE scores were higher in the low-risk groups, and their immune cell infiltrations were dramatically different from those of the high-risk groups. The low-risk groups were shown to have higher infiltration levels of CD8+ T cells and TMB-high status, resulting in better response to immunotherapies.

CONCLUSION

The findings of this study revealed that the nine-cuproptosis-related lncRNA risk score was an independent prognostic factor for BC. This signature was a potential predictor for BC immunotherapy response. What we found will provide novel insight into immunotherapeutic treatment strategies in BC.

摘要

背景

乳腺癌(BC)被认为是女性癌症死亡的主要原因之一。研究表明,铜死亡在肿瘤增殖和肿瘤免疫微环境中发挥重要作用。因此,本研究旨在确定铜死亡相关长链非编码RNA(lncRNA)与BC预后之间的关系。

方法

基于癌症基因组图谱(TCGA),通过Pearson分析和Cox回归分析鉴定出9个铜死亡相关lncRNA,构建铜死亡相关lncRNA特征。随后,将BC患者分为高风险组和低风险组。采用Kaplan-Meier曲线和时间依赖性受试者工作特征(ROC)分析来阐明该特征的预测能力。之后,通过基因集富集分析(GSEA)进行京都基因与基因组百科全书(KEGG)通路分析,并使用Cytoscape软件建立lncRNA-mRNA共表达网络。此外,计算ESTIMATE评分并进行免疫细胞类型成分分析。最后,进行免疫治疗反应分析,以确定铜死亡相关lncRNA对肿瘤免疫治疗反应的预测能力,包括免疫检查点基因表达水平、肿瘤突变负荷(TMB)和微卫星不稳定性(MSI)。

结果

低风险组的BC患者显示出更好的临床结局。高风险组的KEGG通路主要富集于免疫反应和免疫细胞激活。此外,低风险组的ESTIMATE评分更高,其免疫细胞浸润与高风险组显著不同。低风险组显示出较高的CD8+T细胞浸润水平和TMB高状态,对免疫治疗的反应更好。

结论

本研究结果表明,9个铜死亡相关lncRNA风险评分是BC的独立预后因素。该特征是BC免疫治疗反应的潜在预测指标。我们的发现将为BC的免疫治疗策略提供新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6db9/9815178/e3449e36fdd7/fonc-12-1081089-g001.jpg

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