Oncogenes can create metabolic vulnerabilities in cancer cells. We tested how AKT (herein referring to AKT1) 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 rely on oxidative phosphorylation for energy generation. However, the negative effects of AKT were temporary, 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-expressing cells that were dying in galactose culture had upregulated glutathione metabolism. Proteomic profiling revealed that AKT-expressing cells dying in galactose also 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 exclusively in cells expressing AKT. Furthermore, ROS were required for galactoseinduced death of AKT-expressing cells. We then confirmed that galactose-induced ROS-mediated cell death in breast cancer cells with upregulated AKT signaling. These results demonstrate that AKT but not MYC restricts the flexibility of cancer cells to use oxidative phosphorylation. This article has an associated First Person interview with the first author of the paper.

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.

Motivation: Targeted therapeutics have the potential for efficacy against tumors with minimal effects on normal tissues. However, predicting effective drugs from molecular signatures remains a challenge. Here, we present Drug Mechanism Enrichment Analysis (DMEA), a method that uses a transcriptomic signature to predict drug mechanism(s) of action to which a tumor cell may be sensitive or resistant. The method derives its power by aggregating data from many drugs with a shared mechanism of action. Results: We first tested the sensitivity of DMEA using synthetic data. We next validated that DMEA recapitulated known sensitivities to HMGCR, EGFR, and RAF inhibitors while also identifying drug mechanisms for resistant cancers. Finally, we predicted tissue-dependent drug sensitivity for tumors with high and low expression of the cystine/glutamate antiporter xCT. Collectively, DMEA is a novel bioinformatic tool that uses molecular signatures to predict targeted therapeutics sharing a common mechanism of action. Availability and implementation: DMEA is freely available to download as an R package at: https://github.com/BelindaBGarana/DMEA.