Department of Engineering Technology, University of Houston, Sugar Land, TX 77479, USA.
Int J Mol Sci. 2024 May 16;25(10):5439. doi: 10.3390/ijms25105439.
Breast cancer, when advancing to a metastatic stage, involves the liver, impacting over 50% of cases and significantly diminishing survival rates. Presently, a lack of tailored therapeutic protocols for breast cancer liver metastasis (BCLM) underscores the need for a deeper understanding of molecular patterns governing this complication. Therefore, by analyzing differentially expressed genes (DEGs) between primary breast tumors and BCLM lesions, we aimed to shed light on the diversities of this process. This research investigated breast cancer liver metastasis relapse by employing a comprehensive approach that integrated data filtering, gene ontology and KEGG pathway analysis, overall survival analysis, identification of the alteration in the DEGs, visualization of the protein-protein interaction network, Signor 2.0, identification of positively correlated genes, immune cell infiltration analysis, genetic alternation analysis, copy number variant analysis, gene-to-mRNA interaction, transcription factor analysis, molecular docking, and identification of potential treatment targets. This study's integrative approach unveiled metabolic reprogramming, suggesting altered and expression as key in breast cancer metastasis recurrence.
乳腺癌进展为转移阶段时,会累及肝脏,超过 50%的病例会受到影响,且显著降低生存率。目前,针对乳腺癌肝转移(BCLM)缺乏定制的治疗方案,这凸显了深入了解控制这种并发症的分子模式的必要性。因此,通过分析原发性乳腺癌肿瘤和 BCLM 病变之间差异表达的基因(DEGs),我们旨在揭示这一过程的多样性。本研究通过综合方法调查了乳腺癌肝转移复发,该方法综合了数据过滤、基因本体和 KEGG 通路分析、总生存分析、差异表达基因的改变识别、蛋白质-蛋白质相互作用网络可视化、Signor 2.0、正相关基因识别、免疫细胞浸润分析、遗传改变分析、拷贝数变异分析、基因到 mRNA 相互作用、转录因子分析、分子对接以及潜在治疗靶点的识别。本研究的综合方法揭示了代谢重编程,表明 和 的表达改变是乳腺癌转移复发的关键。