Abstract
Patients with thyroid cancer (TC) exhibit significant co-morbidity with other diseases and are at high risk of death. TC has a strong association with the following neurodegenerative and chronic diseases: Parkinsons disease (PD), osteoporosis (OP), chronic kidney disease (CKD), chronic heart failure (CHF), Type 1 diabetes (T1D) and Type 2 diabetes (T2D). In this study, we use a systems biology approach to explore the comorbidity of TC with above-mentioned diseases in order to improve the quality and life expectancy of TC patients. In this study, we used and analysed microarray datasets related to TC, PD, OP, CKD, CHF, T1D and T2D diseases to identify the association of TC with the above-mentioned diseases. We built a relationship network between TC and other diseases and identified implicated gene expression ontology, dysregulated pathways and involved protein–protein interaction network (PPI) by using multilayer network topology and neighbourhood-based benchmarking methods. We obtained 598 differentially expressed genes (DEG) (133 were down-regulated and 465 were up-regulated) with \(P<=\).05 and \(|logFC|>= 1\) for TC. We observed that TC shares 16, 12, 82, 19, 5 and 5 DEGs with PD, OP, CKD, CHF, T1D and T2D, respectively. We leveraged various network-based methodologies to analyse and investigate the genetic relationship of TC with PD, OP, CKD, CHF, T1D and T2D diseases. We found that CKD is strongly associated with TC in terms of common genes and also identified hub genes and important pathways which could be helpful for further studies to identify new biomarkers and pathological processes underlying TC.
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Ali Hossain, M. et al. (2020). Identification of Genetic Links of Thyroid Cancer to the Neurodegenerative and Chronic Diseases Progression: Insights from Systems Biology Approach. In: Uddin, M.S., Bansal, J.C. (eds) Proceedings of International Joint Conference on Computational Intelligence. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-3607-6_21
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DOI: https://doi.org/10.1007/978-981-15-3607-6_21
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