KAIST Develops Methodology to Resensitize Drug-Resistant Cancer Cells

A domestic research team has devised a methodology to make cancer cells that have developed resistance to drugs (anticancer agents) respond to treatment again. Drug resistance in cancer cells is a major obstacle to cancer therapy. Traditionally, the main approach to this problem has been to find new targets to eliminate cancer cells. However, this method carries the risk of inducing even stronger resistance. In contrast, the methodology developed by the research team is drawing attention because it can automatically predict key genes that can resensitize drug-resistant cancer cells to anticancer agents.

(From left) Hyunwook Kim, Professor of Bio and Chemical Engineering, Haeduk Jung, PhD candidate, Jina Lim, PhD candidate, Yusik Kim, Professor. Provided by KAIST

On July 7, KAIST announced that a research team led by Hyunwook Kim and Yusik Kim, professors in the Department of Bio and Chemical Engineering, has developed a methodology based on a 'metabolic network model' that can enhance drug responsiveness in breast cancer cells resistant to anticancer agents by regulating cellular metabolism and predicting gene targets.

The research team focused on the major role of metabolic alterations in cancer cells in the formation of drug resistance. They integrated proteome data from MCF7 breast cancer cell lines resistant to doxorubicin and paclitaxel, respectively, to construct cell-specific metabolic network models.

They also performed 'gene knockout simulations' for all metabolic genes and analyzed the results. Gene knockout simulation allows researchers to calculate and predict changes in biological networks by virtually removing specific genes.

Through these simulations, the team confirmed that suppressing the proteins of certain genes could induce drug-resistant cancer cells, which previously showed little response to anticancer agents, to respond to the drugs again.

Previously, the team identified the GOT1 gene as a target in doxorubicin-resistant cells, the GPI gene in paclitaxel-resistant cells, and the SLC1A5 gene as a common target for both drugs.

The research team explained that they were able to experimentally verify that suppressing the proteins of these selected genes caused the drug-resistant cancer cells to respond to anticancer agents again.

In particular, the team found that the effect of increased drug sensitivity was consistently observed when the same genes were suppressed in other breast cancer cells resistant to the same anticancer agents.

Hyunwook Kim, who led the research, stated, "This study is significant in that it demonstrated the ability to predict key genes that can resensitize drug-resistant cancer cells to treatment using only computer simulations and minimal experimental data. This methodology can be widely applied to discover new therapeutic targets for various types of cancer and metabolism-related intractable diseases."

This research was supported by the Ministry of Science and ICT, the Electronics and Telecommunications Research Institute of Korea, and the National Research Foundation of Korea.

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