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KAIST Presents a Breakthrough in Overcoming Drug Resistance in Cancer – Hope for Treating Intractable Diseases like Diabetes
<(From the left) Prof. Hyun Uk Kim, Ph.D candiate Hae Deok Jung, Ph.D candidate Jina Lim, Prof.Yoosik Kim from the Department of Chemical and Biomolecular Engineering>
One of the biggest obstacles in cancer treatment is drug resistance in cancer cells. Conventional efforts have focused on identifying new drug targets to eliminate these resistant cells, but such approaches can often lead to even stronger resistance. Now, researchers at KAIST have developed a computational framework to predict key metabolic genes that can re-sensitize resistant cancer cells to treatment. This technique holds promise not only for a variety of cancer therapies but also for treating metabolic diseases such as diabetes.
On the 7th of July, KAIST (President Kwang Hyung Lee) announced that a research team led by Professors Hyun Uk Kim and Yoosik Kim from the Department of Chemical and Biomolecular Engineering had developed a computational framework that predicts metabolic gene targets to re-sensitize drug-resistant breast cancer cells. This was achieved using a metabolic network model capable of simulating human metabolism.
Focusing on metabolic alterations—key characteristics in the formation of drug resistance—the researchers developed a metabolism-based approach to identify gene targets that could enhance drug responsiveness by regulating the metabolism of drug-resistant breast cancer cells.
< Computational framework that can identify metabolic gene targets to revert the metabolic state of the drug-resistant cells to that of the drug-sensitive parental cells>
The team first constructed cell-specific metabolic network models by integrating proteomic data obtained from two different types of drug-resistant MCF7 breast cancer cell lines: one resistant to doxorubicin and the other to paclitaxel. They then performed gene knockout simulations* on all of the metabolic genes and analyzed the results.
*Gene knockout simulation: A computational method to predict changes in a biological network by virtually removing specific genes.
As a result, they discovered that suppressing certain genes could make previously resistant cancer cells responsive to anticancer drugs again. Specifically, they identified GOT1 as a target in doxorubicin-resistant cells, GPI in paclitaxel-resistant cells, and SLC1A5 as a common target for both drugs.
The predictions were experimentally validated by suppressing proteins encoded by these genes, which led to the re-sensitization of the drug-resistant cancer cells.
Furthermore, consistent re-sensitization effects were also observed when the same proteins were inhibited in other types of breast cancer cells that had developed resistance to the same drugs.
Professor Yoosik Kim remarked, “Cellular metabolism plays a crucial role in various intractable diseases including infectious and degenerative conditions. This new technology, which predicts metabolic regulation switches, can serve as a foundational tool not only for treating drug-resistant breast cancer but also for a wide range of diseases that currently lack effective therapies.”
Professor Hyun Uk Kim, who led the study, emphasized, “The significance of this research lies in our ability to accurately predict key metabolic genes that can make resistant cancer cells responsive to treatment again—using only computer simulations and minimal experimental data. This framework can be widely applied to discover new therapeutic targets in various cancers and metabolic diseases.”
The study, in which Ph.D. candidates JinA Lim and Hae Deok Jung from KAIST participated as co-first authors, was published online on June 25 in Proceedings of the National Academy of Sciences (PNAS), a leading multidisciplinary journal that covers top-tier research in life sciences, physics, engineering, and social sciences.
※ Title: Genome-scale knockout simulation and clustering analysis of drug-resistant breast cancer cells reveal drug sensitization targets ※ DOI: https://doi.org/10.1073/pnas.2425384122 ※ Authors: JinA Lim (KAIST, co-first author), Hae Deok Jung (KAIST, co-first author), Han Suk Ryu (Seoul National University Hospital, corresponding author), Yoosik Kim (KAIST, corresponding author), Hyun Uk Kim (KAIST, corresponding author), and five others.
This research was supported by the Ministry of Science and ICT through the National Research Foundation of Korea, and the Electronics and Telecommunications Research Institute (ETRI).
2025.07.08 View 5947 -
KAIST Develops Healthcare Device Tracking Chronic Diabetic Wounds
A KAIST research team has developed an effective wireless system that monitors the wound healing process by tracking the spatiotemporal temperature changes and heat transfer characteristics of damaged areas such as diabetic wounds.
On the 5th of March, KAIST (represented by President Kwang Hyung Lee) announced that the research team led by Professor Kyeongha Kwon from KAIST’s School of Electrical Engineering, in association with Chung-Ang University professor Hanjun Ryu, developed digital healthcare technology that tracks the wound healing process in real time, which allows appropriate treatments to be administered.
< Figure 1. Schematic illustrations and diagrams of real-time wound monitoring systems. >
The skin serves as a barrier protecting the body from harmful substances, therefore damage to the skin may cause severe health risks to patients in need of intensive care. Especially in the case of diabetic patients, chronic wounds are easily formed due to complications in normal blood circulation and the wound healing process. In the United States alone, hundreds of billions of dollars of medical costs stem from regenerating the skin from such wounds. While various methods exist to promote wound healing, personalized management is essential depending on the condition of each patient's wounds.
Accordingly, the research team tracked the heating response within the wound by utilizing the differences in temperature between the damaged area and the surrounding healthy skin. They then measured heat transfer characteristics to observe moisture changes near the skin surface, ultimately establishing a basis for understanding the formation process of scar tissue. The team conducted experiments using diabetic mice models regarding the delay in wound healing under pathological conditions, and it was demonstrated that the collected data accurately tracks the wound healing process and the formation of scar tissue.
To minimize the tissue damage that may occur in the process of removing the tracking device after healing, the system integrates biodegradable sensor modules capable of natural decomposition within the body. These biodegradable modules disintegrate within the body after use, thus reducing the risk of additional discomfort or tissue damage upon device removal. Furthermore, the device could one day be used for monitoring inside the wound area as there is no need for removal.
Professor Kyeongha Kwon, who led the research, anticipates that continuous monitoring of wound temperature and heat transfer characteristics will enable medical professionals to more accurately assess the status of diabetic patients' wounds and provide appropriate treatment. He further predicted that the implementation of biodegradable sensors allows for the safe decomposition of the device after wound healing without the need for removal, making live monitoring possible not only in hospitals but also at home.
The research team plans to integrate antimicrobial materials into this device, aiming to expand its technological capabilities to enable the observation and prevention of inflammatory responses, bacterial infections, and other complications. The goal is to provide a multi-purpose wound monitoring platform capable of real-time antimicrobial monitoring in hospitals or homes by detecting changes in temperature and heat transfer characteristics indicative of infection levels.
< Image 1. Image of the bioresorbable temperature sensor >
The results of this study were published on February 19th in the international journal Advanced Healthcare Materials and selected as the inside back cover article, titled "Materials and Device Designs for Wireless Monitoring of Temperature and Thermal Transport Properties of Wound Beds during Healing."
This research was conducted with support from the Basic Research Program, the Regional Innovation Center Program, and the BK21 Program.
2024.03.11 View 14183 -
Breastfeeding Helps Prevent Mothers from Developing Diabetes after Childbirth
A team of South Korean researchers found that lactation can lower the incidence and reduce the risk of maternal postpartum diabetes. The researchers identified that lactation increases the mass and function of pancreatic beta cells through serotonin production. The team suggested that sustained improvements in pancreatic beta cells, which can last for years even after the cessation of lactation, improve mothers’ metabolic health in addition to providing health benefits for infants.
Pregnancy imposes a substantial metabolic burden on women through weight gain and increased insulin resistance. Various other factors, including a history of gestational diabetes, maternal age, and obesity, further affect women’s risk of progressing to diabetes after delivery, and the risk of postpartum diabetes increases more in women who have had gestational diabetes and/or repeated deliveries.
Diabetes-related complications include damage to blood vessels, which can lead to cardiovascular and cerebrovascular diseases such as heart attack and stroke, and problems with the nerves, eyes, kidneys, and many more. Since diabetes can pose a serious threat to mothers’ metabolic health, the management of maternal metabolic risk factors is important, especially in the peripartum period. Previous epidemiological studies have reported that lactation reduces the risk of postpartum diabetes, but the mechanisms underlying this benefit have remained elusive.
The study, published in Science Translational Medicine on April 29, explains the biology underpinning this observation on the beneficial effects of lactation. Professor Hail Kim from the Graduate School of Medical Science and Engineering at KAIST led and jointly conducted the study in conjunction with researchers from the Seoul National University Bundang Hospital (SNUBH) and Chungnam National University (CNU) in Korea, and the University of California, San Francisco (UCSF) in the US.
In their study, the team observed that the milk-secreting hormone ‘prolactin’ in lactating mothers not only promotes milk production, but also plays a major role in stimulating insulin-secreting pancreatic beta cells that regulate blood glucose in the body.
The researchers also found that ‘serotonin’, known as a chemical that contributes to wellbeing and happiness, is produced in pancreatic beta cells during lactation. Serotonin in pancreatic beta cells act as an antioxidant and reduce oxidative stress, making mothers’ beta cells healthier. Serotonin also induces the proliferation of beta cells, thereby increasing the beta cell mass and helping maintain proper glucose levels.
The research team conducted follow-up examinations on a total of 174 postpartum women, 85 lactated and 99 non-lactated, at two months postpartum and annually thereafter for at least three years. The results demonstrated that mothers who had undergone lactation improved pancreatic beta cell mass and function, and showed improved glucose homeostasis with approximately 20mg/dL lower glucose levels, thereby reducing the risk of postpartum diabetes in women. Surprisingly, this beneficial effect was maintained after the cessation of lactation, for more than three years after delivery.
Professor Kim said, “We are happy to prove that lactation benefits female metabolic health by improving beta cell mass and function as well as glycemic control.”
“Our future studies on the modulation of the molecular serotonergic pathway in accordance with the management of maternal metabolic risk factors may lead to new therapeutics to help prevent mothers from developing metabolic disorders,” he added.
This work was supported by grants from the National Research Foundation (NRF) and the National Research Council of Science and Technology (NST) of Korea, the National Institutes of Health (NIH), the Larry L. Hillblom Foundation, and the Health Fellowship Foundation.
Image credit: Professor Hail Kim, KAIST
Image usage restrictions: News organizations may use or redistribute this image, with proper attribution, as part of news coverage of this paper only.
Publication:
Moon, J. H et al. (2020) ‘Lactation improves pancreatic β cell mass and function through serotonin production.’ Science Translational Medicine, 12, eaay0455. Available online at https://doi.org/10.1126/scitranslmed.aay0455
Profile: Hail Kim, MD, PhD
hailkim@kaist.edu
Associate Professor
Graduate School of Medical Science and Engineering (GSMSE)
Korea Advanced Institute of Science and Technology (KAIST)
Profile: Hak Chul Jang, MD, PhD
janghak@snu.ac.kr
Professor
Division of Endocrinology and Metabolism
Seoul National University Bundang Hospital (SNUBH)
President
Korean Diabetes Association
Profile: Joon Ho Moon, MD, PhD
moonjoonho@gmail.com
Clinical Fellow
Division of Endocrinology and Metabolism
SNUBH
Profile: Hyeongseok Kim, MD, PhD
hskim85kor@gmail.com
Assistant Professor
Chungnam National University (CNU)
Profile: Professor Michael S. German, MD
Michael.German@ucsf.edu
Professor
Diabetes Center
University of California, San Francisco (UCSF)
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2020.04.29 View 30231