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用于预测乳腺癌的缺氧相关4-长链非编码RNA模型的构建与验证

Construction and Verification of a Hypoxia-Related 4-lncRNA Model for Prediction of Breast Cancer.

作者信息

Zhao Ye, Liu Lixiao, Zhao Jinduo, Du Xuedan, Yu Qiongjie, Wu Jinting, Wang Bin, Ou Rongying

机构信息

Department of Obstetrics and Gynecology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China.

Department of Chemoradiation Oncology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China.

出版信息

Int J Gen Med. 2021 Aug 17;14:4605-4617. doi: 10.2147/IJGM.S322007. eCollection 2021.

Abstract

INTRODUCTION

Breast cancer is the most common form of cancer worldwide and a serious threat to women. Hypoxia is thought to be associated with poor prognosis of patients with cancer. Long non-coding RNAs are differentially expressed during tumorigenesis and can serve as unambiguous molecular biomarkers for the prognosis of breast cancer.

METHODS

Here, we accessed the data from The Cancer Genome Atlas for model construction and performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses to identify biological functions. Four prognostic hypoxia-related lncRNAs identified by univariate, LASSO, and multivariate Cox regression analyses were used to develop a prognostic risk-related signature. Kaplan-Meier and receiver operating characteristic curve analyses were performed, and independent prognostic factor analysis and correlation analysis with clinical characteristics were utilized to evaluate the specificity and sensitivity of the signature. Survival analysis and receiver operating characteristic curve analyses of the validation cohort were operated to corroborate the robustness of the model.

RESULTS

Our results demonstrate the development of a reliable prognostic gene signature comprising four long non-coding RNAs (AL031316.1, AC004585.1, LINC01235, and ACTA2-AS1). The signature displayed irreplaceable prognostic power for overall survival in patients with breast cancer in both the training and validation cohorts. Furthermore, immune cell infiltration analysis revealed that B cells, CD4 T cells, CD8 T cells, neutrophils, and dendritic cells were significantly different between the high-risk and low-risk groups. The high-risk and low-risk groups could be precisely distinguished using the risk signature to predict patient outcomes.

DISCUSSION

In summary, our study proves that hypoxia-related long non-coding RNAs serve as accurate indicators of poor prognosis and short overall survival, and are likely to act as potential targets for future cancer therapy.

摘要

引言

乳腺癌是全球最常见的癌症形式,对女性构成严重威胁。缺氧被认为与癌症患者的不良预后相关。长链非编码RNA在肿瘤发生过程中差异表达,可作为乳腺癌预后明确的分子生物标志物。

方法

在此,我们从癌症基因组图谱获取数据用于模型构建,并进行基因本体论和京都基因与基因组百科全书分析以识别生物学功能。通过单变量、套索和多变量Cox回归分析确定的四种与缺氧相关的预后lncRNA用于开发预后风险相关特征。进行了Kaplan-Meier分析和受试者工作特征曲线分析,并利用独立预后因素分析以及与临床特征的相关性分析来评估该特征的特异性和敏感性。对验证队列进行生存分析和受试者工作特征曲线分析以证实模型的稳健性。

结果

我们的结果表明开发了一种可靠的预后基因特征,其由四种长链非编码RNA(AL031316.1、AC004585.1、LINC01235和ACTA2-AS1)组成。该特征在训练队列和验证队列中均显示出对乳腺癌患者总生存具有不可替代的预后能力。此外,免疫细胞浸润分析显示,高风险组和低风险组之间的B细胞、CD4 T细胞、CD8 T细胞、中性粒细胞和树突状细胞存在显著差异。使用风险特征可以精确区分高风险组和低风险组以预测患者预后。

讨论

总之,我们的研究证明与缺氧相关的长链非编码RNA是不良预后和总生存时间短的准确指标,并且可能成为未来癌症治疗的潜在靶点。

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