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阻塞性睡眠呼吸暂停与肺癌之间重叠基因特征的识别:超越药物创新的“一种药物,一种疾病”模式

Identification of Overlapping Genetic Signatures Between Obstructive Sleep Apnea and Lung Cancer: Moving Beyond "One Drug, One Disease" Paradigm of Pharmaceutical Innovation.

作者信息

Dasgupta Sanjukta

机构信息

Department of Biotechnology, Center for Multidisciplinary Research & Innovations, Brainware University, Barasat, India.

出版信息

OMICS. 2025 May;29(5):221-228. doi: 10.1089/omi.2025.0010. Epub 2025 Apr 8.

Abstract

Traditional paradigms of pharmaceutical innovation have long relied on the "one drug, one disease" premise. However, a network mindset in unpacking disease mechanisms can be fruitful to move toward a "one drug, polydisease" paradigm of drug discovery and development. A case in point is obstructive sleep apnea (OSA) and lung cancer, which are two prevalent respiratory disorders that share common risk factors and may potentially exhibit overlapping molecular mechanisms. The putative mechanistic linkages between OSA and lung cancer remain underexplored; however, this study offers new evidence on overlapping genetic signatures between OSA and lung cancer with an in-silico approach. Bioinformatics analysis of the publicly available datasets (GSE135917 and GSE268175) identified 123 upregulated and 13 downregulated genes in OSA and 3175 upregulated and 2272 downregulated genes in lung cancer. A total of four genes (, , , and ) were significantly upregulated with both disorders, highlighting potentially shared genetic and molecular mechanisms. Pathway and cell enrichment analysis indicated that mucin type O-glycan biosynthesis pathway and endothelial cells are strongly associated with these shared genes, lending support for their potential roles in both diseases. Moreover, hsa-miR-34a-5p, hsa-let-7g-5p, and hsa-miR-19a-3p were found to be associated with these common genes. Validation using the GEPIA2 tool confirmed the consistent expression patterns of these four genes in lung cancer. Machine learning analysis highlighted as the most significant biomarker candidate for distinguishing OSA and lung cancer from controls. In summary, this study supports the overarching concept that human diseases can have shared mechanistic pathways in the specific example of OSA and lung cancer. While these findings call for further research and validation, they invite rethinking the current pharmaceutical innovation paradigms to move beyond the "one drug, one disease" concept.

摘要

长期以来,传统的药物创新模式一直依赖于“一种药物,一种疾病”的前提。然而,在剖析疾病机制时采用网络思维模式,对于迈向“一种药物,多种疾病”的药物发现与开发模式可能富有成效。一个恰当的例子是阻塞性睡眠呼吸暂停(OSA)和肺癌,这是两种常见的呼吸系统疾病,它们具有共同的风险因素,并且可能潜在地表现出重叠的分子机制。OSA与肺癌之间假定的机制联系仍未得到充分探索;然而,本研究通过计算机模拟方法提供了关于OSA和肺癌之间重叠基因特征的新证据。对公开可用数据集(GSE135917和GSE268175)的生物信息学分析确定了OSA中123个上调基因和13个下调基因,以及肺癌中3175个上调基因和2272个下调基因。共有四个基因(、、和)在两种疾病中均显著上调,突出了潜在的共同遗传和分子机制。通路和细胞富集分析表明,粘蛋白型O-聚糖生物合成通路和内皮细胞与这些共享基因密切相关,支持了它们在两种疾病中的潜在作用。此外,发现hsa-miR-34a-5p、hsa-let-7g-5p和hsa-miR-19a-3p与这些共同基因相关。使用GEPIA2工具进行的验证证实了这四个基因在肺癌中的一致表达模式。机器学习分析突出显示为区分OSA和肺癌与对照的最显著生物标志物候选物。总之,本研究支持这样一个总体概念,即在OSA和肺癌的具体例子中,人类疾病可以具有共同的机制途径。虽然这些发现需要进一步的研究和验证,但它们促使人们重新思考当前的药物创新模式,以超越“一种药物,一种疾病”的概念。

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