SABITA Institute/ (MODAS)
Istanbul Medipol University, Istanbul, Türkiye

https://sabita.medipol.edu.tr/index.php/portfolio-item/sarah-barakat/

Oxygen in the Equation: Rethinking Drug Screening Through a Proteomics Lens and Beyond

Abstract:
Oxygen is a critical determinant of cellular physiology, governing metabolic activity, signal transduction, and gene regulatory processes. In vivo, oxygen availability is tightly regulated and varies across tissues, typically within a physiological range of 1% to 6% in most tissues. However, most in vitro cell culture systems are maintained under atmospheric oxygen levels (~18–21%). These supraphysiological oxygen levels perturb metabolic flux, disrupt redox balance, and induce extensive transcriptional and translational reprogramming, factors that significantly influence cellular sensitivity to pharmacological agents. As a result, drug screening conducted under non-physiological oxygen tensions may fail to capture oxygen-dependent mechanisms of drug efficacy or resistance, thereby compromising the translational relevance of such in vitro assays. Transcriptomic and proteomic studies have consistently shown that even moderate changes in oxygen tension can drive substantial alterations in pathways associated with hypoxia-inducible signaling, energy metabolism, oxidative stress response, and protein homeostasis. Furthermore, integrated multi-omics analyses frequently reveal discordance between transcript abundance and protein expression under varying oxygen conditions. This observation highlights the need to interrogate both molecular layers in order to obtain an accurate view of functional responses. These effects are highly cell type–specific and context-dependent. To resolve this complexity, computational approaches, including machine learning, are increasingly utilized to extract biologically meaningful patterns from high-dimensional omics datasets, enabling the identification of oxygen-sensitive molecular signatures and a more comprehensive understanding of oxygen-dependent regulation of drug responses.