Potential senotherapeutic candidates and their combinations derived from transcriptional connectivity and network measures

Nayeri Rad, Amirhossein ORCID: 0000-0003-4958-0109, Shams, Golnaz, Avelar, Roberto A ORCID: 0000-0003-4997-9953, Morowvat, Mohammad Hossein ORCID: 0000-0003-4466-3175 and Ghasemi, Younes (2022) Potential senotherapeutic candidates and their combinations derived from transcriptional connectivity and network measures. Informatics in Medicine Unlocked, 30. p. 100920.

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Official URL: http://dx.doi.org/10.1016/j.imu.2022.100920

Abstract

Cellular senescence, a state of permanent cell cycle arrest, is associated with organismal aging and malfunctioning. Various attempts have been made to find a unified gene signature for all senescence models in every cell type. However, with more studies being conducted, none look to be universally shared; instead, it seems that the senescence gene signature is cell-type specific. In the present study, 74 genes commonly expressed in different models of fibroblast senescence, derived from two independent studies were extracted. The shared signature of fibroblast senescence, which was functionally associated with aging, was further regarded as a target module to attenuate the fibroblast senescence phenotype. Utilizing Connectivity Map to discover the inversely connected compounds with this gene signature and analyzing network proximity of the targets of the inversely connected compounds with fibroblast senescence genes, we suggest glutamine, tangeretin, artemisinin, and castanospermine as potential senescence therapeutics. Moreover, to overcome this impaired gene expression system, we suggest the combination of glutamine with one of tangeretin, artemisinin, or castanospermine, that obey the complementary exposure pattern to reach better therapeutic efficacy while manifesting minimal adverse effects.

Item Type:	Article
Divisions:	Faculty of Health and Life Sciences
Depositing User:	Symplectic Admin
Date Deposited:	11 Apr 2022 09:54
Last Modified:	18 Jan 2023 21:05
DOI:	10.1016/j.imu.2022.100920
Open Access URL:	https://www.sciencedirect.com/science/article/pii/...
Related URLs:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3152620