Bioinformatics Analysis and Experimental Validation of ASF1B in Breast Tumors

IF 3.1 2区医学 Q2 ONCOLOGY

Cancer Medicine Pub Date : 2025-09-13 DOI:10.1002/cam4.71073

Wenhao Xing, Meng Deng, Wendong Wang, Yueqi Liu, Xuefang Mi, Huixia Li, Xin Ge

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Abstract

Objective

To investigate the association between ASF1B expression and pathological characteristics of breast cancer, and to further explore its role in tumor progression and the immune microenvironment, thereby evaluating its potential as a therapeutic target.

Methods

ASF1B expression in breast cancer was analyzed using the GEPIA2 and BEST databases. Its association with patient prognosis was assessed using Kaplan–Meier survival analysis. Protein co-expression networks were constructed using GeneMANIA. The correlation between ASF1B expression and immune cell infiltration was evaluated through the TIMER platform. Experimental validation was performed using qPCR and immunohistochemistry (IHC) on 67 breast cancer tissue samples.

Results

ASF1B expression was significantly elevated in breast cancer tissues compared to normal tissues (p < 0.05). High ASF1B expression was associated with reduced overall and recurrence-free survival (p < 0.05). Protein interaction analysis revealed that ASF1B was strongly linked to proteins involved in DNA replication, cell cycle progression, and chromatin remodeling. Immune analysis indicated positive correlations with B cells, neutrophils, and dendritic cells and a negative correlation with macrophage infiltration (p < 0.05). Clinical data further showed that high ASF1B expression was significantly associated with HER2-positive breast cancer (p = 0.026).

Conclusion

ASF1B is highly expressed in breast cancer and correlates with poor prognosis and immune cell infiltration. It may serve as a potential prognostic biomarker and therapeutic target in breast cancer.

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乳腺肿瘤中ASF1B的生物信息学分析及实验验证

目的探讨ASF1B表达与乳腺癌病理特征的关系，进一步探讨其在肿瘤进展和免疫微环境中的作用，从而评价其作为治疗靶点的潜力。方法采用GEPIA2和BEST数据库对乳腺癌组织中ASF1B的表达进行分析。使用Kaplan-Meier生存分析评估其与患者预后的关系。利用GeneMANIA构建蛋白共表达网络。通过TIMER平台评估ASF1B表达与免疫细胞浸润的相关性。采用qPCR和免疫组化（IHC）对67例乳腺癌组织样本进行实验验证。结果ASF1B在乳腺癌组织中的表达明显高于正常组织（p < 0.05）。ASF1B高表达与总生存率和无复发生存率降低相关（p < 0.05）。蛋白质相互作用分析显示，ASF1B与DNA复制、细胞周期进程和染色质重塑相关的蛋白质密切相关。免疫分析显示与B细胞、中性粒细胞和树突状细胞呈正相关，与巨噬细胞浸润呈负相关（p < 0.05）。临床资料进一步显示，ASF1B高表达与her2阳性乳腺癌有显著相关性（p = 0.026）。结论ASF1B在乳腺癌中高表达，与预后不良及免疫细胞浸润相关。它可能作为乳腺癌的潜在预后生物标志物和治疗靶点。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cancer Medicine ONCOLOGY-

CiteScore

5.50

自引率

2.50%

发文量

907

审稿时长

19 weeks

期刊介绍： Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas: Clinical Cancer Research Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations Cancer Biology: Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery. Cancer Prevention: Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach. Bioinformatics: Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers. Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.