AKT but not MYC promotes reactive oxygen species-mediated cell death in oxidative culture

Abstract

Running title: AKT promotes oxidative stress in galactose culture AKT promotes oxidative stress in galactose culture 2 ABSTRACT Oncogenes can generate metabolic vulnerabilities in cancer cells. Here, we tested how AKT and MYC affect the ability of cells to shift between respiration and glycolysis.Using immortalized mammary epithelial cells, we discovered that constitutively active AKT but not MYC induced cell death in galactose culture, where cells must rely on oxidative phosphorylation for energy generation. However, the negative effects of AKT were short-lived, and AKT-expressing cells recommenced growth after ~15 days in galactose. To identify the mechanisms regulating AKT-mediated cell death, we used metabolomics and found that AKT cells dying in galactose upregulated glutathione metabolism. Next, using proteomics, we discovered that AKT-expressing cells dying in galactose upregulated nonsense-mediated mRNA decay, a marker of sensitivity to oxidative stress. We therefore measured levels of reactive oxygen species (ROS) and discovered that galactose induced ROS in cells expressing AKT but not MYC. Additionally, ROS were required for the galactose-induced death of AKT-expressing cells. We then tested whether these findings could be replicated in breast cancer cell lines with constitutively active AKT signaling. Indeed, we found that galactose induced rapid cell death in breast cancer cell lines and that ROS were required for galactose-induced cell death. Together, our results demonstrate that AKT but not MYC induces a metabolic vulnerability in cancer cells, namely the restricted flexibility to use oxidative phosphorylation. Implications:The discovery that AKT but not MYC restricts the ability to utilize oxidative phosphorylation highlights that therapeutics targeting tumor metabolism must be tailored to the individual genetic profile of tumors.

Linguistic Analysis of the bioRxiv Preprint Landscape

“…Examining the top five and bottom five preprints within the systems biology field reinforces PC1 ‘s dichotomous theme (Table 2). Preprints with the highest values [64,65,66,67,68] included software packages, machine learning analyses, and other computational biology manuscripts, while preprints with the lowest values [69,70,71,72,73] were focused on cellular signaling and protein activity. We provide the rest of our 50 generated PCs in our online repository (see Software and Data Availability).…”