乳腺癌中蛋白聚糖基因表达的综合研究:发现与恶性表型相关的独特蛋白聚糖基因特征。

Proteoglycan research Pub Date : 2025-01-01 Epub Date: 2025-01-08 DOI:10.1002/pgr2.70014
Simone Buraschi, Gabriel Pascal, Federico Liberatore, Renato V Iozzo
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引用次数: 0

摘要

实体肿瘤在肿瘤学中是一个巨大的挑战,需要创新的方法来改善治疗效果。蛋白聚糖是肿瘤微环境中的多面分子,由于其在癌症进展中的不同作用而引起了人们的关注。它们与特定膜受体、生长因子和细胞因子相互作用的独特能力为开发基于重组蛋白聚糖的疗法提供了一条有希望的途径,可以提高癌症治疗的准确性和有效性。在这项研究中,我们对人类乳腺癌中的蛋白多糖基因图谱进行了全面的分析。利用现有的关于乳腺癌基因表达的基因组和临床数据,并使用机器学习模型,我们确定了一个独特的基因表达特征,由肿瘤组织中差异调节的五种蛋白聚糖组成:Syndecan-1和asporin(上调)和decorin, PRELP和podocan(下调)。对乳腺癌数据的进一步查询显示,先前显示在乳腺癌患者和小鼠模型中增加并与不良预后相关的serglycin在绝大多数乳腺癌患者中确实减少了,其水平与肿瘤进展和侵袭呈负相关。这种蛋白聚糖基因标记可以为乳腺癌生物学提供新的诊断能力,并强调需要进一步利用公开可用的数据集来临床前实验结果的临床验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comprehensive investigation of proteoglycan gene expression in breast cancer: Discovery of a unique proteoglycan gene signature linked to the malignant phenotype.

Solid tumors present a formidable challenge in oncology, necessitating innovative approaches to improve therapeutic outcomes. Proteoglycans, multifaceted molecules within the tumor microenvironment, have garnered attention due to their diverse roles in cancer progression. Their unique ability to interact with specific membrane receptors, growth factors, and cytokines provides a promising avenue for the development of recombinant proteoglycan-based therapies that could enhance the precision and efficacy of cancer treatment. In this study, we performed a comprehensive analysis of the proteoglycan gene landscape in human breast carcinomas. Leveraging the available wealth of genomic and clinical data regarding gene expression in breast carcinoma and using a machine learning model, we identified a unique gene expression signature composed of five proteoglycans differentially modulated in the tumor tissue: Syndecan-1 and asporin (upregulated) and decorin, PRELP and podocan (downregulated). Additional query of the breast carcinoma data revealed that serglycin, previously shown to be increased in breast carcinoma patients and mouse models and to correlate with a poor prognosis, was indeed decreased in the vast majority of breast cancer patients and its levels inversely correlated with tumor progression and invasion. This proteoglycan gene signature could provide novel diagnostic capabilities in breast cancer biology and highlights the need for further utilization of publicly available datasets for the clinical validation of preclinical experimental results.

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