Identification of Dual-Purpose Therapeutic Targets Implicated in Aging and Glioblastoma Multiforme Using PandaOmics - An AI-Enabled Biological Target Discovery Platform

April 2023 in “ Aging ”

Andrea Olsen, Zachary Harpaz, Christopher X. Ren, Anastasia Shneyderman, Alexander Veviorskiy, Maria Dralkina, Simon Konnov, Olga Shcheglova, Frank W. Pun, Geoffrey Ho Duen Leung, Hoi-Wing Leung, Ivan V. Ozerov, Alex Aliper, Mikhail Korzinkin, Alex Zhavoronkov

Studysummary In this study, the authors used AI-driven methods to identify and prioritize promising therapeutic targets that may address both aging and Glioblastoma Multiforme, proposing CNGA3, GLUD1, and SIRT1 as novel candidates. Our plain-language summary of this paper — not a Tressless recommendation.

This study explores the identification of dual-purpose therapeutic targets for both aging and Glioblastoma Multiforme (GBM) using the AI-enabled PandaOmics platform. By integrating disease-related genes with those important in aging, the researchers developed three strategies for target identification, utilizing correlation analysis, survival data, expression level differences, and existing aging-related gene information. The AI-driven PandaOmics TargetID engine was employed to rank and prioritize potential therapeutic gene targets. The study proposes cyclic nucleotide gated channel subunit alpha 3 (CNGA3), glutamate dehydrogenase 1 (GLUD1), and sirtuin 1 (SIRT1) as promising targets for treating both aging and GBM.

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