Schematic representation of the research results: the research team identified...
Schematic representation of the research results: the research team identified key molecular regulatory pathways to avoid high plasticity formed by abnormal EMT of cancer cells and reverse it to an epithelial cell state through systems biology research. From this analysis, a reprogramming molecular target that can reverse the state of mesenchymal cells with acquired invasiveness and drug resistance to the state of epithelial cells with restored drug responsiveness was discovered.

Image source: KAIST

News • Systems biology

Lung cancer: new discovery could remove metastatic traits

A research team from the Korea Advanced Institute of Science and Technology (KAIST) led by Professor Kwang-Hyun Cho from the Department of Bio and Brain Engineering succeeded in using systems biology research to change the properties of carcinogenic cells in the lungs and eliminate both drug resistance and their ability to proliferate out to other areas of the body.

Professor Kwang-Hyun Cho's research team simulated various cancer cell states in the Epithelial-to-Mesenchymal Transition (EMT) of lung cancer cells, between epithelial cells without metastatic ability and mesenchymal cells with metastatic ability. A mathematical model of molecular network was established, and key regulators that could reverse the state of invasive and drug resistant mesenchymal cells back to the epithelial state were discovered through computer simulation analysis and molecular cell experiments. In particular, this process succeeded in properly reverting the mesenchymal lung cancer cells to a state where they were sensitive to chemotherapy treatment while avoiding the unstable EMT hybrid cell state in the middle process, which had remained a difficult problem. 

The results of this research were published as an online paper in the international journal “Cancer Research” published by the American Association for Cancer Research (AACR).

From left: Ph.D. Student Namhee Kim (first author), Dr. Chae Young Hwang...
From left: Ph.D. Student Namhee Kim (first author), Dr. Chae Young Hwang (co-first author), and Professor Kwang-Hyun Cho of the Laboratory for Systems Biology and Bio-inspired Engineering

Image source: KAIST

Cells in an EMT hybrid state, which are caused by incomplete transitions during the EMT process in cancer cells, have the characteristics of both epithelial cells and mesenchymal cells, and are known to have high drug resistance and metastatic potential by acquiring high stem cell capacity. In particular, EMT is further enhanced through factors such as transforming growth factor-beta (TGF-β) secreted from the tumor microenvironment (TME) and, as a result, various cell states with high plasticity appear. Due to the complexity of EMT, it has been very difficult to completely reverse the transitional process of the mesenchymal cancer cells to an epithelial cell state in which metastatic ability and drug resistance are eliminated while avoiding the EMT hybrid cell state with high metastatic ability and drug resistance. 

Professor Kwang-Hyun Cho's research team established a mathematical model of the gene regulation network that governs the complex process of EMT, and then applied large-scale computer simulation analysis and complex system network control technology to identify and verify 'p53', 'SMAD4', and 'ERK1' and 'ERK 2' (collectively ERKs) through molecular cell experiments as the three key molecular targets that can transform lung cancer cells in the mesenchymal cell state, reversed back to an epithelial cell state that no longer demonstrates the ability to metastasize, while avoiding the EMT hybrid cell state. 

In particular, by analyzing the molecular regulatory mechanism of the complex EMT process at the system level, the key pathways were identified that were linked to the positive feedback that plays an important role in completely returning cancer cells to an epithelial cell state in which metastatic ability and drug resistance are removed. This discovery is significant in that it proved that mesenchymal cells can be reverted to the state of epithelial cells under conditions where TGF-β stimulation are present, like they are in the actual environment where cancer tissue forms in the human body. 

Abnormal EMT in cancer cells leads to various malignant traits such as the migration and invasion of cancer cells, changes in responsiveness to chemotherapy treatment, enhanced stem cell function, and the dissemination of cancer. In particular, the acquisition of the metastatic ability of cancer cells is a key determinant factor for the prognosis of cancer patients. The EMT reversal technology in lung cancer cells developed in this research is a new anti-cancer treatment strategy that reprograms cancer cells to eliminate their high plasticity and metastatic potential and increase their responsiveness to chemotherapy. 

Professor Kwang-Hyun Cho said, "By succeeding in reversing the state of lung cancer cells that acquired high metastatic traits and resistance to drugs and reverting them to a treatable epithelial cell state with renewed sensitivity to chemotherapy, the research findings propose a new strategy for treatments that can improve the prognosis of cancer patients.” 

Professor Kwang-Hyun Cho's research team was the first to present the principle of reversal treatment to revert cancer cells to normal cells, following through with the announcement of the results of their study that reverted colon cancer cells to normal colon cells in January of 2020, and also presenting successful re-programming research where the most malignant basal type breast cancer cells turned into less-malignant luminal type breast cancer cells that were treatable with hormonal therapies in January of 2022. This latest research result is the third in the development of reversal technology where lung cancer cells that had acquired metastatic traits returned to a state in which their metastatic ability was removed and drug sensitivity was enhanced. 

Source: Korea Advanced Institute of Science and Technology


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