1430 Modeling the onset of senescence associated secretory phenotype predicts therapeutic targets

Abstract

During cellular senescence cells undergo permanent cell cycle arrest, and this protects from malignant transformation. Though important to control cancerous neoplasia, the same mechanisms may fundamentally drive aging and age-related disorders. Senescent cells in many instances release a battery of soluble factors, collectively termed as senescence associated secretory phenotype (SASP). Depending on histogenetic origin of cells, SASP can vary in components and composition. Of note, SASP spreads senescence within tissues and organs and promotes several age associated disorders, including skin aging and impairment of chronic wound healing. Employing already published gene interaction data, we developed a Boolean network model-based gene regulatory network of SASP. We have simulated the network with the aim to inhibit SASP during DNA damage induced senescence. This simulation allowed us to predict different in-silico gene knockouts those can prevent damaging effects of key SASP-factors. The most promising in-silico knockout candidates originating from this simulation was NF-κB Essential Modulator (NEMO) or IKK-γ. Using in vitro experiments in murine dermal fibroblasts, we confirmed the importance of NEMO to successfully inhibit key SASP following DNA-damage. Therefore, we experimentally strengthened the speculated regulatory role of NF-κB signaling in the onset as well as maintenance of SASP using in-silico and in-vitro approaches. These data, thus, give access to potential therapeutic targets for SASP-associated aging diseases.