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

Amirhossein Nayeri Rad, Golnaz Shams, Roberto A. Avelar, Mohammad Hossein Morowvat, Younes Ghasemi

Informatics in Medicine Unlocked · 2022 · ▲ 5 citations

Abstract

Cellular senescence(definition), 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.

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Provenance

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OpenAlex
DOI
10.1016/j.imu.2022.100920
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2026-08-03 MST

Cite this

APA
Rad, A.N., Shams, G., Avelar, R.A., Morowvat, M.H., &amp; Ghasemi, Y. (2022). Potential senotherapeutic candidates and their combinations derived from transcriptional connectivity and network measures. <em>Informatics in Medicine Unlocked</em>. https://doi.org/10.1016/j.imu.2022.100920
Vancouver
Rad AN, Shams G, Avelar RA, Morowvat MH, Ghasemi Y. Potential senotherapeutic candidates and their combinations derived from transcriptional connectivity and network measures. Informatics in Medicine Unlocked. 2022. doi:10.1016/j.imu.2022.100920.
BibTeX
@article{amirhossein2022Potent, title = {Potential senotherapeutic candidates and their combinations derived from transcriptional connectivity and network measures}, author = {Amirhossein Nayeri Rad and Golnaz Shams and Roberto A. Avelar and Mohammad Hossein Morowvat and Younes Ghasemi}, journal = {Informatics in Medicine Unlocked}, year = {2022}, doi = {10.1016/j.imu.2022.100920}, }

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