Abstract 4673: Genome-scale metabolic models identify gene targets that enhance drug response of drug-resistant breast cancer cells

Abstract

Abstract Adaptive drug resistance poses a significant therapeutic challenge in treatment of breast cancer patients. Metabolic reprogramming in cancer cells is one of the major mechanisms associated with drug resistance. In this study, we aim to identify gene targets that enhance the drug response of drug-resistant breast cancer cells through downregulation. We hypothesized that metabolic perturbation in drug-resistant breast cancer cells could revert their metabolic features to those of drug-sensitive cells. To predict such gene targets, we used a computational model known as a genome-scale metabolic model (GEM). A GEM simulates the entire metabolic reaction fluxes of a cell under varying genetic and/or environmental conditions. We specifically targeted two engineered MCF7 breast cancer cell lines: one resistant to doxorubicin and the other to paclitaxel. First, we generated proteome data from drug-sensitive and drug-resistant MCF7 cell lines, and used them to construct the cell-specific GEMs. Subsequently, single-gene knockout simulation was conducted using these cell-specific GEMs. The initial list of the gene knockout targets was subjected to pathway analysis involving proteome and metabolome data to finalize the gene targets. The final gene targets were expected to lead to metabolic features similar to those of drug-sensitive MCF7 upon the downregulation. In vitro experiments using inhibitors were conducted to validate these predicted gene targets. This study provides a computational approach that can also be applied to other types of drug-resistant cancer cells. Citation Format: Hae Deok Jung, JinA Lim, Han Suk Ryu, Yoosik Kim, Hyun Uk Kim. Genome-scale metabolic models identify gene targets that enhance drug response of drug-resistant breast cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4673.