Molecular Inverse Comorbidity between Alzheimer’s disease and Lung Cancer: new insights from Matrix Factorization

Greco, Alessandro; Valle, Jon Sanchez; Pancaldi, Vera; Baudot, Anaı̈s; Barillot, Emmanuel; Caselle, Michele; Valencia, Alfonso; Zinovyev, Andrei; Cantini, Laura

doi:10.1101/643890

Cited by 10 publications

(4 citation statements)

References 61 publications

(62 reference statements)

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“…Cancer incidence [25], particularly lung cancer [26], seems to be lower in AD and in other central neurodegenerative diseases. Several observations from animal models, transcriptomic meta-analyses, and matrix factorization studies underline the existence of molecular substrates supporting the hypothesis of an inverse comorbidity relationship between AD and lung cancer [27-29].…”

Section: Introductionmentioning

confidence: 99%

Chronic Respiratory Diseases and Neurodegenerative Disorders: A Primer for the Practicing Clinician

Falsetti¹,

Viticchi²,

Zaccone³

et al. 2021

Med Princ Pract

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Chronic respiratory disorders represent a world epidemic. Their incidence and prevalence in the world population is increasing, and especially among elderly subjects, they are commonly associated with other pathologies, often generating a status of high clinical complexity. Neurology, internal medicine, and pneumology specialists should be aware of the common background of these disorders in order to treat correctly the patient’s comorbid state and optimize the treatment considering potential overlaps. In this review, we aimed to focus on the relationships between chronic respiratory disorders and chronic neurodegenerative diseases at different levels; we review the shared risk factors and the interactions between disorders, the indications to explore respiratory function in neurodegenerative diseases, pathology-pathology and drug-pathology interactions in patients affected by both chronic neurologic and respiratory diseases.

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Section: Introductionmentioning

confidence: 99%

Chronic Respiratory Diseases and Neurodegenerative Disorders: A Primer for the Practicing Clinician

Falsetti¹,

Viticchi²,

Zaccone³

et al. 2021

Med Princ Pract

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“…This suggests that a propensity towards one family of diseases may decrease the risk for the other. As an example, AD patients are less prone to develop lung cancer [24][25][26][27], and a history of smoking related cancers has a protective impact against AD [15]. Also for amyotrophic lateral sclerosis (ALS) a decreased frequency of cancer is observed after disease onset [28], although a cancer diagnosis does not affect the occurrence of ALS [29,30].…”

Section: Epidemiological Studies Associate Neurodegeneration and Cancermentioning

confidence: 99%

Tau: At the Interface Between Neurodegeneration and Cancer?

Papin¹,

Paganetti²

2020

Preprint

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For its microtubule-binding properties, the expression level of the neurodegeneration-associated protein Tau is pondered as a potential modifier of cancer resistance to chemotherapy since decades. Indeed, Tau binds microtubules at the same site as taxanes, a class of chemotherapeutic drugs designed to stabilize the microtubule network in order to stall cell division and to induce tumor cell death. Whilst independent studies report the association between low Tau expression and superior taxane response, the data were refused by a meta-analysis, suggesting interference of other parameters. Unpredictably, Tau expression level was identified as a prognostic cancer marker, whereby its positive or negative predictive value for survival depended on the cancer type. With recent experimental evidence linking Tau to P53 signaling, DNA stability and protection and to the implication of Tau in cancer is strengthened. The identification of a role of Tau at the interface between two major aging-related disorder families, neurodegeneration and cancer, offers clues for the epidemiological observation inversely correlating these disorders. Elucidating how Tau is mechanistically implicated in cellular pathways common to these devastating illnesses may extend the Tau-targeting therapeutic opportunities to cancer.

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“…For example, several epidemiologic studies [6][7][8] have demonstrated a risk reduction for Alzheimer's disease after a cancer diagnosis (including lung cancer) [9][10][11]. Moreover, transcriptomic studies [12][13][14] have indicated that the genes upregulated in Alzheimer's disease and downregulated in cancer, as well as the genes downregulated in Alzheimer's disease and upregulated in cancer were signifcantly overlapped. In addition, expression deregulation in opposite directions was observed at the level of pathways in Alzheimer's disease and cancer [15].…”

Section: Introductionmentioning

confidence: 99%

Autoencoder Networks Decipher the Association between Lung Cancer and Alzheimer’s Disease

Gao

Tang

et al. 2022

Computational Intelligence and Neuroscience

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Lung cancer is the most common malignancy and is responsible for the largest cancer-related mortality worldwide. Alzheimer’s disease is a degenerative neurological disease that burdens healthcare worldwide. While the two diseases are distinct, several transcriptomic studies have demonstrated they are linked. However, no concordant conclusion on how they are associated has been drawn. Since these studies utilized conventional bioinformatics methods, such as the differentially expressed gene (DEG) analysis, it is naturally expected that the proportion of DEGs having either the same or inverse directions in lung cancer and Alzheimer’s disease is substantial. This raises the inconsistency. Therefore, a novel bioinformatics method capable of determining the direction of association is desirable. In this study, the moderated t-tests were first used to identify DEGs that are shared by the two diseases. For the shared DEGs, separate autoencoder (AE) networks were trained to extract a one-dimensional representation (pseudogene) for each disease. Based on these pseudogenes, the association direction between lung cancer and Alzheimer’s disease was inferred. AE networks based on 266 shared DEGs revealed a comorbidity relationship between Alzheimer’s disease and lung cancer. Specifically, Spearman’s correlation coefficient between the predicted values using the two AE networks for the Alzheimer’s disease test set was 0.825 and for the lung cancer test set was 0.316. Novel bioinformatics methods such as an AE network may help decipher how distinct diseases are associated by providing the refined representations of dysregulated genes.

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Molecular Inverse Comorbidity between Alzheimer’s disease and Lung Cancer: new insights from Matrix Factorization

Cited by 10 publications

References 61 publications

Chronic Respiratory Diseases and Neurodegenerative Disorders: A Primer for the Practicing Clinician

Chronic Respiratory Diseases and Neurodegenerative Disorders: A Primer for the Practicing Clinician

Tau: At the Interface Between Neurodegeneration and Cancer?

Autoencoder Networks Decipher the Association between Lung Cancer and Alzheimer’s Disease

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