LAUSR

Anticancer chemotherapy is an essential part of cancer treatment, but the emergence of resistance due to continued drug usage remains a major hurdle. Among the multiple mechanisms behind the acquisition of drug resistance, metabolic plasticity is receiving increasing attention. Recent proteomic and transcriptomic studies identified metabolic enzymes as potential targets for overcoming the resistance. Yet, these studies mainly focused on differentially expressed genes and overlooked the complexity of the metabolic network, especially its ability to reorganize the metabolic state in response to gene downregulation. Here, we employ the genome-scale metabolic model (GEM) to simulate the metabolic flow and identify candidates that can act as a metabolic switch for drug resistance. Using adriamycin- and paclitaxel-resistant MCF-7 breast cancer cells as model systems, we perform proteomics analysis followed by GEM construction to analyze the differential metabolic flow in the resistant cells. Moreover, we perform GEM simulations after individually knocking out every metabolic enzyme and identify a metabolic switch whose knockout restores the metabolic state of drug-sensitive MCF-7 cells. Notably, downregulating the candidate metabolic switch predicted by our model results in sensitization to the drug. We further show that the cotreatment of adriamycin or paclitaxel with a small chemical inhibitor of the metabolic switch synergistically induces cell death in drug-resistant cells. Collectively, our study demonstrates the application of GEM simulation and subsequent modulation of metabolic state as a strategy to restore drug sensitivity to overcome drug-resistant cancer. Citation Format: JinA Lim, Hae Deok Jung, Kyung-min Lee, Moonhyeon Jeon, Han Suk Ryu, Hyun Uk Kim, Yoosik Kim. Genome-scale metabolic modeling reveals a metabolic switch that restores sensitivity to anticancer chemotherapy in drug-resistant breast cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1737.