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首页> 美国卫生研究院文献>International Journal of Molecular Sciences >Molecular Inverse Comorbidity between Alzheimer’s Disease and Lung Cancer: New Insights from Matrix Factorization
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Molecular Inverse Comorbidity between Alzheimer’s Disease and Lung Cancer: New Insights from Matrix Factorization

机译：阿尔茨海默氏病和肺癌之间的分子逆共病：矩阵分解的新见解

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Matrix factorization (MF) is an established paradigm for large-scale biological data analysis with tremendous potential in computational biology. Here, we challenge MF in depicting the molecular bases of epidemiologically described disease–disease (DD) relationships. As a use case, we focus on the inverse comorbidity association between Alzheimer’s disease (AD) and lung cancer (LC), described as a lower than expected probability of developing LC in AD patients. To this day, the molecular mechanisms underlying DD relationships remain poorly explained and their better characterization might offer unprecedented clinical opportunities. To this goal, we extend our previously designed MF-based framework for the molecular characterization of DD relationships. Considering AD–LC inverse comorbidity as a case study, we highlight multiple molecular mechanisms, among which we confirm the involvement of processes related to the immune system and mitochondrial metabolism. We then distinguish mechanisms specific to LC from those shared with other cancers through a pan-cancer analysis. Additionally, new candidate molecular players, such as estrogen receptor (ER), cadherin 1 (CDH1) and histone deacetylase (HDAC), are pinpointed as factors that might underlie the inverse relationship, opening the way to new investigations. Finally, some lung cancer subtype-specific factors are also detected, also suggesting the existence of heterogeneity across patients in the context of inverse comorbidity.
机译：矩阵分解（MF）是大规模生物学数据分析的既定范例，在计算生物学中具有巨大潜力。在这里，我们在描述流行病学描述的疾病-疾病（DD）关系的分子基础时，对MF提出了挑战。作为一个用例，我们重点关注阿尔茨海默氏病（AD）与肺癌（LC）之间的合并症反向关联，该关联被描述为比AD患者发生LC的可能性要低。直到今天，关于DD关系的分子机制仍知之甚少，其更好的表征可能会提供前所未有的临床机会。为此，我们扩展了先前设计的基于MF的框架，用于DD关系的分子表征。以AD-LC逆共病为案例研究，我们重点介绍了多种分子机制，其中我们确认了与免疫系统和线粒体代谢有关的过程的参与。然后，我们通过泛癌分析将LC特有的机制与其他癌症共有的机制区分开来。此外，新的候选分子参与者，例如雌激素受体（ER），钙黏着蛋白1（CDH1）和组蛋白脱乙酰基酶（HDAC），被确定为可能与这种逆关系有关的因素，为新的研究方法开辟了道路。最后，还检测到一些肺癌亚型特异性因素，这也表明在合并症相反的情况下，患者之间存在异质性。

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