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基于转录组学和实验验证探索乳腺癌中与淋巴管生成相关的预后基因

Exploration of prognostic genes associated with lymphangiogenesis in breast cancer based on transcriptomics and experimental verification.

作者信息

Liu Chen, Zhang Tuo, Luo Fushen, Yang Xiaofeng, Li Yadong, Yi Tonghui, Wu Shuang, Wang Yanbing, Zhu Yueping, Zhao Kun

机构信息

Department of Clinical Laboratory, The Third Affiliated Hospital of Qiqihar Medical University, Qiqihar, Heilongjiang, China.

Department of Radiotherapy, The Third Affiliated Hospital of Qiqihar Medical University, Qiqihar, Heilongjiang, China.

出版信息

PeerJ. 2025 Aug 27;13:e19890. doi: 10.7717/peerj.19890. eCollection 2025.

Abstract

BACKGROUND

Breast cancer (BC), a malignant neoplasm resulting from the uncontrolled proliferation of mammary epithelial cells, is predominantly driven by pathogenic breast cancer gene (BRCA) 1/2 mutations in hereditary cases. Previous studies have implicated lymphangiogenesis in the progression of BC. This research aimed to identify prognostic genes associated with lymphangiogenesis in BC and explore their underlying biological mechanisms.

METHODS

Publicly available datasets were utilized to identify differentially expressed genes (DEGs). Lymphangiogenesis-related genes (LRGs) were sourced from public databases, and candidate genes were determined through the intersection of DEGs and LRGs. Univariate Cox regression analysis and machine learning algorithms were employed to select prognostic genes and develop a prognostic model. Further analyses, including a nomogram, Gene Set Enrichment Analysis (GSEA), immune cell infiltration analysis, and drug sensitivity predictions, were conducted based on the identified prognostic genes. Finally, reverse transcription quantitative polymerase chain reaction (PCR) (RT-qPCR) was performed to evaluate the expression levels of these genes.

RESULTS

By intersecting 9,577 DEGs with 179 LRGs, 109 candidate genes were identified. Ultimately, four prognostic genes-ZIC2, CD24, CEBPD, and CCL19-were selected, and a prognostic model was established. The model demonstrated robust performance upon evaluation and validation, with the nomogram confirming its strong predictive ability. Notably, the prognostic genes were found to influence pathways such as the cell cycle and EGFR ligands, as well as immune cells like activated CD4 T cells. Additionally, drugs like AUY922 and AZ628 showed considerable potential in treating BC. RT-qPCR results for these four genes in clinical samples aligned with the bioinformatics findings.

CONCLUSION

This study identified and validated four prognostic genes-ZIC2, CD24, CEBPD, and CCL19-that are associated with BC and may provide novel targets for diagnostic and therapeutic strategies.

摘要

背景

乳腺癌(BC)是一种由乳腺上皮细胞不受控制地增殖引起的恶性肿瘤,在遗传性病例中主要由致病性乳腺癌基因(BRCA)1/2突变驱动。先前的研究表明淋巴管生成与BC的进展有关。本研究旨在鉴定与BC中淋巴管生成相关的预后基因,并探索其潜在的生物学机制。

方法

利用公开可用的数据集来鉴定差异表达基因(DEG)。淋巴管生成相关基因(LRG)来自公共数据库,并通过DEG与LRG的交集确定候选基因。采用单变量Cox回归分析和机器学习算法来选择预后基因并建立预后模型。基于鉴定出的预后基因进行了进一步分析,包括列线图、基因集富集分析(GSEA)、免疫细胞浸润分析和药物敏感性预测。最后,进行逆转录定量聚合酶链反应(PCR)(RT-qPCR)以评估这些基因的表达水平。

结果

通过将9577个DEG与179个LRG相交,鉴定出109个候选基因。最终,选择了四个预后基因——ZIC2、CD24、CEBPD和CCL19,并建立了预后模型。该模型在评估和验证时表现出强大的性能,列线图证实了其强大的预测能力。值得注意的是,发现预后基因会影响细胞周期和EGFR配体等途径,以及活化的CD4 T细胞等免疫细胞。此外,AUY922和AZ628等药物在治疗BC方面显示出相当大的潜力。临床样本中这四个基因的RT-qPCR结果与生物信息学结果一致。

结论

本研究鉴定并验证了四个与BC相关的预后基因——ZIC2、CD24、CEBPD和CCL19,它们可能为诊断和治疗策略提供新的靶点。

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