Identifying patterns to uncover the importance of biological pathways on known drug repurposing scenarios

• Published in: BMC genomics Vol. 25; no. 1; p. 43
• Main Authors: Otero-Carrasco, Belén, Ugarte Carro, Esther, Prieto-Santamaría, Lucía, Diaz Uzquiano, Marina, Caraça-Valente Hernández, Juan Pedro, Rodríguez-González, Alejandro
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 09-01-2024; BioMed Central; BMC
• Subjects: Alfacalcidol; Analysis; Angiotensin-converting enzyme inhibitors; Breast cancer; Calcifediol; Colorectal cancer; Computational biology; Computational linguistics; Data mining; Data-driven methodology; Disease; DISNET knowledge; Drug Delivery Systems; Drug development; Drug discovery; Drug Repositioning; Drug repurposing; Drug targeting; Drugs; Gene expression; Genes; Language processing; Lipid Metabolism; Metabolism; Methods; Natural language interfaces; Pathway-based; Physiological aspects; R&D; Research & development; Statistics, Nonparametric; Vitamin D; Spain; Drug repurposing; Pathway-based; DISNET knowledge; Data-driven methodology; Computational biology
• ISSN: 1471-2164; 1471-2164
• DOI: 10.1186/s12864-023-09913-1

Drug repurposing plays a significant role in providing effective treatments for certain diseases faster and more cost-effectively. Successful repurposing cases are mostly supported by a classical paradigm that stems from de novo drug development. This paradigm is based on the "one-drug-one-target-one-disease" idea. It consists of designing drugs specifically for a single disease and its drug's gene target. In this article, we investigated the use of biological pathways as potential elements to achieve effective drug repurposing.
Considering a total of 4214 successful cases of drug repurposing, we identified cases in which biological pathways serve as the underlying basis for successful repurposing, referred to as DREBIOP. Once the repurposing cases based on pathways were identified, we studied their inherent patterns by considering the different biological elements associated with this dataset, as well as the pathways involved in these cases. Furthermore, we obtained gene-disease association values to demonstrate the diminished significance of the drug's gene target in these repurposing cases. To achieve this, we compared the values obtained for the DREBIOP set with the overall association values found in DISNET, as well as with the drug's target gene (DREGE) based repurposing cases using the Mann-Whitney U Test.
A collection of drug repurposing cases, known as DREBIOP, was identified as a result. DREBIOP cases exhibit distinct characteristics compared with DREGE cases. Notably, DREBIOP cases are associated with a higher number of biological pathways, with Vitamin D Metabolism and ACE inhibitors being the most prominent pathways. Additionally, it was observed that the association values of GDAs in DREBIOP cases were significantly lower than those in DREGE cases (p-value < 0.05).
Biological pathways assume a pivotal role in drug repurposing cases. This investigation successfully revealed patterns that distinguish drug repurposing instances associated with biological pathways. These identified patterns can be applied to any known repurposing case, enabling the detection of pathway-based repurposing scenarios or the classical paradigm.