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KAIST Develops a Way to Combat Cancer Cachexia, the Wasting Syndrome That Debilitates Patients
A new path has opened toward stopping cancer-associated cachexia, a devastating complication that gradually wastes patients away. A KAIST research team has developed an RNA-based therapeutic strategy that blocks a brain signal to prevent muscle loss and extend survival.
KAIST (President Choongsik Bae) announced on the 2nd of August that a joint research team led by Professor Minho Shong and Professor Jinkuk Kim from the Graduate School of Medical Science and Engineering, together with the KAIST faculty startup THOR Therapeutics (CEO Minho Shong), identified a new therapeutic principle for cancer cachexia.
Cancer cachexia affects 50 to 80 percent of all cancer patients, making it one of the most common complications of the disease. As cancer cells disrupt the body's metabolism, patients continue to lose weight and muscle mass even when eating sufficiently, leading to severe physical decline. This is a major reason chemotherapy often becomes less effective and treatment is discontinued, ultimately lowering survival rates. Existing drugs, however, have been limited to temporarily boosting appetite and have failed to fundamentally address the underlying muscle loss and metabolic dysfunction.
The research team focused on the idea that the root cause of cancer cachexia lies not in the body, but in the brain. The team noted that when GDF15 (Growth Differentiation Factor 15)—a signaling protein secreted in large amounts as cancer progresses—binds to GFRAL, a receptor protein in the brainstem, it triggers a signal instructing the body to stop eating and instead break down stored muscle and fat, driving progressive physical decline.
To block this process, the team worked with Professor Kim's group to develop a therapeutic using antisense oligonucleotides (ASO)—an RNA-based gene therapy technologies that selectively suppresses the activity of a specific gene—to prevent GFRAL from being produced in the first place.
In effect, the treatment switches off the receiver of the signal that cancer cells send instructing the body to waste away. By blocking GFRAL production at the RNA stage—the intermediate step in which genetic information is converted into protein—the therapy shuts down the cachexia-inducing signal at its source.
The team administered the treatment to mice in which cancer cachexia had already progressed. The result was a substantial reduction in muscle and fat loss, along with the restoration of the metabolic function that had previously broken down. Notably, even though treatment began after the disease had advanced significantly, survival at the study's endpoint (around day 50) was markedly higher in the treated group—90 percent—compared with just 20 percent in the untreated group, demonstrating the therapy's potential for treating cancer cachexia.
Unlike existing treatments that only stimulate appetite, this study is significant in that it blocks the underlying signal driving the wasting process itself. The therapy improved both muscle loss and metabolic dysfunction, and researchers expect that it could eventually be used alongside existing cancer treatments as a next-generation adjuvant therapy to improve patients' quality of life, treatment effectiveness, and survival rates.
"While existing therapies have only temporarily boosted appetite, this study is significant in that it directly targeted a key receptor in the brainstem at the RNA level to suppress the root cause of cancer cachexia," said Professor Song. He added that the team's goal is to move forward with follow-up preclinical research and drug manufacturing as well as quality-control systems without delay, begin clinical development in cancer patients by 2030, and develop the therapy into a treatment that improves patients' quality of life and survival rates.
Dr. Hyunjung Hong from the Graduate School of Medical Science and Engineering, Dr. Minhee Lee from THOR Therapeutics, and Dr. Minsung Park from the Graduate School of Medical Science and Engineering participated as co-first authors, with Professor Song and Professor Kim serving as co-corresponding authors. The findings were published in the international journal Cell Reports Medicine on July 27.
Paper title: Therapeutic Gfral silencing via antisense oligonucleotides ameliorates cancer-associated cachexia and extends survival in tumor-bearing mice
DOI : https://doi.org/10.1016/j.xcrm.2026.102939
This research was supported by the National Research Foundation of Korea, the Korea Health Industry Development Institute, and the Ministry of SMEs and Startups.
2026.08.03 View 358 -
KAIST Makes Cancer Cells Send Out Their Own Danger Signal — Delivering Immunotherapy and Gene Therapy in a Single Nanoparticle Platform
Cancer cells survive by hiding from the immune system's surveillance. A KAIST research team has developed a new anticancer platform that makes cancer cells send out their own danger signal—prompting immune cells to attack—while simultaneously delivering gene therapy. The approach is expected to offer a new treatment strategy that combines cancer immunotherapy and gene therapy in a single nanoparticle.
Immunogenic cell death (ICD) is a process in which dying cancer cells send danger signals to nearby immune cells, prompting them to attack. A polypeptide is a polymer made of a long chain of amino acids.
KAIST (President Choongsik Bae) announced on 28th of July that a team led by Professor Yeu-Chun Kim from the Department of Chemical and Biomolecular Engineering has developed a "helical polypeptide nanoparticle" platform that induces severe stress inside cancer cells to trigger immunogenic cell death, while also delivering a range of gene therapeutics into the cells.
The body's immune cells effectively eliminate external invaders such as viruses and bacteria, but cancer cells evade immune surveillance through a variety of immune-escape strategies. This failure of immune cells to recognize cancer cells as a threat has long been one of the biggest limitations in cancer treatment.
Recently, researchers have been actively exploring the use of nanoparticles to deliver drugs and genes to cancer cells and activate immune responses. However, it has not been clearly established which properties of nanomaterials actually induce cellular stress and activate antitumor immune responses.
By comparing and analyzing a range of nanoparticles, the team confirmed that not just the chemical composition, but the helical, coiled shape of the nanomaterial is a key factor determining therapeutic efficacy. In particular, when a positively charged quaternary amine—a chemical structure that binds readily to cell membranes—was combined with a helical structure, the particle could penetrate the cell membrane like a screw and enter cancer cells with ease. By contrast, particles with the same chemical composition but lacking the helical coil barely entered cells at all and failed to induce an immune response.
The helical nanoparticles developed by the team preferentially seek out and penetrate cancer cells, which have different membrane electrical properties from normal cells. Once inside, the particles disrupt the membranes of mitochondria—the cell's energy-producing organelles—and other organelles, subjecting the cancer cell to severe stress.
Under this extreme stress, the dying cancer cell releases damage-associated molecular patterns (DAMPs)—distress signals indicating "a dangerous cell is here"—into the surrounding environment. Immune cells that detect these signals recognize the previously hidden cancer cell as a threat and begin their attack. In effect, the cancer cell is made to broadcast its own location to the immune system.
The nanoparticle does more than trigger an immune response—it also functions as a carrier for gene therapeutics. Messenger RNA (mRNA), which carries the genetic information for protein synthesis, and small interfering RNA (siRNA), which suppresses the expression of specific genes, are both typically difficult to deliver into cells. The team's nanoparticles, however, delivered these molecules effectively into the cytoplasm.
The researchers also introduced guanidinium, a chemical functional group that binds strongly to genetic material, at an optimized ratio, enabling the particles to remain stable in the bloodstream while delivering gene therapeutics effectively.
In mouse models of melanoma and colorectal cancer, the team loaded the helical nanoparticles with siRNA targeting PD-L1 (Programmed Death-Ligand 1), an immune-evasion protein, and administered them. Tumor growth was suppressed by approximately 70–80%, and a marked increase was observed in cytotoxic T cells—which directly attack cancer cells—infiltrating the tumor, indicating a substantial boost in antitumor immune response.
"This study presents a new anticancer platform in which the nanomaterial does more than simply deliver a therapeutic agent—it drives cancer cells to trigger their own immune response," said Professor Yeu-Chun Kim. He added that the platform is expected to contribute to the development of next-generation treatments combining cancer immunotherapy and gene therapy.
Dr. Susam Lee, the paper's first author, added, "We showed that it is not just the composition of the nanomaterial but the helical structure itself that is the key factor determining therapeutic efficacy." He said he hopes the findings will serve as a new benchmark for designing next-generation immuno-oncology nanomaterials.
The study was published online in Biomaterials, a leading international journal in the field of biomaterials, on May 28, 2026.
Paper title: Helical quaternary amine polypeptide programs membrane stress to drive immunogenic cell death and cytosolic gene delivery for cancer immunotherapy
DOI: 10.1016/j.biomaterials.2026.124337
This work was supported by the National Research Foundation of Korea (NRF) grants funded by the Korean government (MSIT), the Biomedical Global Talent Nurturing Program of the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (RS-2025-25459605 to Susam Lee) and the Korea Basic Science Institute (National research Facilities and Equipment Center).
2026.07.28 View 770 -
KAIST identifies a molecular “switch” that activates cell growth signaling, suggesting a potential basis for next-generation anticancer therapy
Cells carry their own growth switches. When enough nutrients—amino acids in particular—are available, cells flip this switch on and begin to grow. Researchers at KAIST and Yonsei University have now uncovered the molecular mechanism by which amino acid signals activate this cellular growth switch. The findings are expected to open a new avenue for anticancer therapies that target abnormal growth signaling in tumor cells.
KAIST (President Choongsik Bae) announced on July 26 that a research team led by Professors Hee-Sung Park and Jin Young Kang from the Department of Chemistry, working with Professor Sunghoon Kim's team from Yonsei University, has identified a molecular mechanism that links amino acid stimulation to mTORC1-dependent growth signaling.
Cells continually monitor whether enough amino acids—the basic building blocks of proteins—are available in their surroundings, and adjust their growth, protein synthesis, and energy use accordingly. Central to this process is mTORC1 (mammalian Target of Rapamycin Complex 1), a protein complex that functions as the cell's growth switch.
mTORC1 promotes cell growth, protein synthesis, and metabolism when nutrients and energy are abundant. But when mTORC1 becomes excessively active, cells can grow and proliferate beyond what is needed—a pattern of dysregulation observed in numerous cancers. For this reason, mTORC1 has long been considered a prime target for anticancer drug development. Exactly how cells detect external nutrient cues and translate them into mTORC1 activation, however, has remained incompletely understood.
The research team focused on the multi-tRNA synthetase complex (MSC), a large protein assembly composed of multiple aminoacyl-tRNA synthetases and scaffold proteins. While aminoacyl-tRNA synthetases are best known for their essential role in protein synthesis – attaching specific amino acids to their cognate tRNAs – the team showed that, in response to amino acid stimulation the MSC releases LARS1, thereby linking nutrient availability to growth signaling.
The key player within the MSC turned out to be a protein called LARS1 (leucyl-tRNA synthetase 1), an enzyme that attaches leucine to its corresponding tRNA and also functions as an intracellular leucine sensor. When cells receive a signal that nutrients are sufficient, LARS1 undergoes phosphorylation—a modification in which a small chemical tag is attached to a protein, altering its function or binding behavior.
The relationship can be pictured this way: the MSC is a control center where multiple proteins wait on standby, and LARS1 is the field agent dispatched to flip on the growth switch. When nutrients become abundant, LARS1 receives a phosphorylation "deployment signal," dissociates from IARS1, the protein that anchors LARS1 to the MSC, and is thereby released from the complex. The freed LARS1 then goes on to activate mTORC1.
In other words, when nutrients are scarce, LARS1 stays bound within the MSC and the growth signal remains off. Once nutrients become sufficient, LARS1 is released from the MSC and switches on mTORC1.
To investigate the structural basis of this process, the team used cryo-electron microscopy (cryo-EM), a technique that visualizes protein complexes in three dimensions in near-atomic resolution by rapidly freezing samples at extremely low temperatures. This allowed the researchers to determine how LARS1 and IARS1 bind to each other and to structurally explain how phosphorylation could disrupt their interaction.
The results showed that LARS1 and IARS1 are normally bound tightly, but amino acid stimulation induces the phosphorylation of LARS1, weakening its interaction with IARS1. This allows LARS1 to dissociate from the MSC and activate mTORC1.
The researchers also engineered phosphomimetic LARS1 variants—mutant proteins designed to imitate the phosphorylated state—and found that these variants substantially enhanced mTORC1 activity. This confirmed that the phosphorylation of LARS1 functions as the key molecular switch converting a nutrient signal into a cell growth signal.
The significance of this study lies in mapping, in concrete molecular detail, how cells sense amino acids and use that information to activate their growth switch. In particular, the study revealed that, upon receiving nutrient signals, the MSC—a complex involved in protein synthesis—releases its constituent protein LARS1, which then activates cellular growth signaling.
Some existing anticancer drugs work by directly inhibiting mTORC1, the cell's growth switch. However, because mTORC1 is also required for normal cellular growth and metabolism, its direct inhibition may also affect normal cells.
The research team expects that further identifying the kinase responsible for phosphorylating LARS1, along with its regulatory mechanism, could enable a more precise anticancer strategy—one that intercepts the growth signal further upstream, before it reaches mTORC1, rather than blocking mTORC1 itself.
The study was co-first-authored by Youjin Kim and Joo-Chan Kim from KAIST's Department of Chemistry and was published online in Nature Communications on June 11.
Paper title: Cryo-EM structure of the LARS1:IARS1 complex reveals a nutrient-responsive switch controlling mTORC1 signaling
DOI: https://doi.org/10.1038/s41467-026-74085-x
This work was supported by the National Research Foundation of Korea (grant nos. RS-2026-25482352 to H.S.P., RS-2024-00344154 to J.Y.K., and NRF-2021R1A3B1076605 to S.K.) and PNCC (grant no. 160183).
2026.07.27 View 803 -
A Single Blood Sample May Improve the Prediction of Colorectal Cancer Recurrence and Progression, KAIST Study Finds
A single preoperative blood sample may help improve the prediction of recurrence or metastasis in patients with colorectal cancer. A joint research team from KAIST, Gangnam Severance Hospital, and Asan Medical Center has shown that, as colorectal cancer advances, the network of relationships among circulating amino acids (a kind of metabolic map) undergoes systematic remodeling. Building on this finding, the researchers developed an analytical method that showed higher predictive performance than a CEA-only model and models based solely on individual amino acid levels.
KAIST (President Choongsik Bae) announced on July 22 that a joint research team led by Professor Ji Min Lee from the Graduate School of Medical Science and Engineering and Professor Hyunwoo Kim from the Department of Chemistry, in collaboration with researchers at Gangnam Severance Hospital and Asan Medical Center, has developed a new framework for analyzing networks of circulating amino acids, which reflect the body’s metabolic state. Using this framework, the team showed that the circulating amino acid network undergoes stage-dependent remodeling that reflects systemic metabolic reprogramming. The team then used these network-derived features to develop a new analytical strategy for predicting recurrence or metastasis.
Cancer cells require large amounts of nutrients to grow and proliferate. Amino acids are not only the building blocks of proteins but also essential for energy production and DNA synthesis, making them critical to cancer cell survival and growth. Colorectal cancer, in particular, is characterized by pronounced changes in amino acid metabolism.
These changes are not confined to tumor tissue; they also appear in the bloodstream. As a result, blood amino acids have drawn attention as an important metabolic biomarker reflecting the body's overall metabolic state. Until now, however, research has focused mainly on the concentrations of individual amino acids, leaving the question of how amino acids are interconnected and change together largely unexplored.
The team used fluorine-19 nuclear magnetic resonance (¹⁹F NMR) spectroscopy to simultaneously quantify 18 circulating amino acids in a small serum sample. By analyzing not only the relative abundance of each amino acid but also the relationships among them as a network, the researchers showed that the circulating amino acid network is progressively remodeled as colorectal cancer advances.
The researchers interpreted this remodeling as evidence of systemic metabolic reprogramming (broad changes in metabolism associated with tumor progression).
As colorectal cancer progressed, the proportion of branched-chain amino acids (BCAAs) such as valine and leucine, which play key roles in muscle and energy metabolism, decreased, while the proportion of glycine and serine, which cancer cells need to synthesize DNA and proliferate rapidly, increased. This shift suggests that systemic amino acid utilization changes with advancing disease.
Glycine proved particularly notable. Although glycine is actively used by rapidly proliferating cancer cells, its relative abundance in the blood increased rather than decreased. The team also observed the emergence of a glycine-centered interaction pattern, providing further evidence of systemic metabolic remodeling during colorectal cancer progression.
The team then applied the pairwise amino acid interaction features into machine-learning models designed to identify patients with recurrence or metastasis.
In nested cross-validation, the correlation-based model showed higher predictive performance than a CEA-only model, while the combined model incorporating CEA, individual amino acid levels, and interaction-derived features achieved the highest overall performance. It also outperformed a model based solely on individual amino acid levels.
The findings suggest that examining how amino acids interact and change together, rather than considering their levels alone, provides a more informative picture of cancer progression. The study is the first to show that the interaction network among circulating amino acids could serve as a blood-based metabolic biomarker.
"We hope this will lead to new precision medicine technologies that can predict recurrence risk more accurately using a blood sample alone and help establish personalized treatment strategies," said Professor Ji Min Lee.
The research began with an interdisciplinary idea proposed through KAIST’s Master’s and PhD Venture Research Program. Graduate students in medical science and chemistry jointly conceived an interdisciplinary approach to studying cancer progression through networks of circulating amino acids. The proposal was selected for support and ultimately led to publication in the internationally renowned journal Advanced Science.
"This research embodies the spirit of KAIST by showing how students’ creative ideas and interdisciplinary collaboration can open new possibilities,” said KAIST President Choongsik Bae. He added that KAIST will continue to foster an environment in which students and researchers can freely pursue challenges across disciplinary boundaries and support creative interdisciplinary research that produces innovative technologies contributing to public health and quality of life.
The study's co-first authors are Ji-Yeon Lee, a student in the integrated master’s and doctoral program at the Graduate School of Medical Science and Engineering, and Dr. Jumi Kim, a postdoctoral researcher in the Department of Chemistry. Professors Ji Min Lee and Hyunwoo Kim of KAIST and Professor Eun Jung Park, affiliated with Gangnam Severance Hospital and Asan Medical Center, served as co-corresponding authors. The findings were published online in Advanced Science, which has a Journal Impact Factor of 14.1, on June 9, 2026.
Paper title: Circulating Amino Acid Network Remodeling Reveals Systemic Metabolic Reprogramming Predictive of Colorectal Cancer Recurrence and Metastasis
DOI: 10.1002/advs.76044
This research was supported by the Samsung Research Funding & Incubation Center of Samsung Electronics, the National Research Foundation of Korea, a Faculty Research Grant from the Department of Surgery at Asan Medical Center, and grants from the Asan Institute for Life Sciences, among others.
2026.07.22 View 791 -
KAIST Identifies New Therapeutic Target by Revealing How Cancer ‘Hijacks’ the Blueprint for Blood Vessel Development
Anti-angiogenic therapies targeting VEGF have been widely used in cancer treatment, yet their long-term efficacy remains limited. Tumor vascular endothelial cells (TECs) exhibit high adaptive plasticity, enabling them to resist treatment and sustain tumor growth, but the molecular mechanism underlying this plasticity has remained poorly understood.
KAIST, led by President Kwang Hyung Lee, announced that a joint research team led by Professor Inkyung Jung (Department of Biological Sciences), Professor Ji Min Lee (Graduate School of Medical Science and Engineering), and Professor Gou Young Koh (Institute for Basic Science) has now uncovered the answer. By integrating cross-cancer single-cell transcriptomic and epigenomic atlases across eight solid tumor types with multiomic profiles, including 3D chromatin contact maps, of human embryonic stem cell (hESC)-derived vascular endothelial cell differentiation, the team demonstrated that TECs reactivate a gene regulatory program normally confined to the late progenitor stage of vascular development. Much like reusing an old blueprint rather than drawing up a new one, tumors co-opt this pre-existing developmental program to fuel blood vessel growth.
The team’s integrative framework combined single-cell RNA-seq and ATAC-seq across multiple tumor types with H3K27ac ChIP-seq, Hi-C-based 3D chromatin mapping across a dense time series of hESC-to-EC differentiation. This approach resolved the EC-progenitor specific regulatory program that defines the shared pro-angiogenic program between late EC progenitors and TECs.
Within this framework, integrin receptor (ITGAV) emerged as a functional mediator specifically upregulated in both late EC progenitors and TECs. Cell-to-cell interaction analysis identified multiple key ligands from tumor micro enviroment (TME) that reactivate the progenitor-associated gene regulatory program. Pharmacologic inhibition attenuated endothelial migration, invasion, and tube formation in vitro, and significantly reduced tumor vascularization and growth in a colorectal cancer xenograft model in vivo.
Professor Inkyung Jung noted that this study reframes how we understand tumor angiogenesis: tumors do not invent new mechanisms, but exploit regulatory programs already embedded in normal vascular development. This insight offers a new conceptual basis for why anti-VEGF therapies face limitations, and points toward targeting the underlying regulatory architecture of endothelial plasticity as a complementary anti-angiogenic strategy.
The study was co-first authored by Dr. Andrew J. Lee, Dr. Sunwoo Min, Ph.D. student Su Chan Park; and Dr. Mei-Yu Qiu. Professors Inkyung Jung, Ji Min Lee, and Gou Young Koh served as corresponding authors. The findings were published on June 8 in Cancer Research [IF = 22.3].
※ Paper title: "A Co-opted Developmental Gene Regulatory Program in Endothelial Progenitors Promotes Tumor Angiogenic Phenotypes"
※ DOI: 10.1158/0008-5472.CAN-25-5094
※ Authors: Andrew J. Lee (KAIST, first author), Sunwoo Min (KAIST, co-first), Su Chan Park (KAIST, co-first), Mei-Yu Qiu (IBS, co-first), Gou Young Koh (IBS, co-corresponding), Ji Min Lee (KAIST, co-corresponding), Inkyung Jung (KAIST, corresponding)
This research was supported by the National Research Foundation of Korea and the Institute for Basic Science.
2026.07.01 View 918 -
Octopus-Inspired 3D Micro-LEDs Pave the Way for Selective Pancreatic Cancer Therapy
<(From Left) Professor Keon Jae Lee, Professor Tae-Hyuk Kwon, Ph.D candidate Min Seo Kim, Dr. Jae Hee Lee, Dr. Chae Gyu Lee>
-KAIST and UNIST Researchers Develop Shape-Morphing Device to Overcome Pancreatic Tumor Microenvironment Barriers
Conventional pancreatic cancer treatments face a critical hurdle due to the dense tumor microenvironment (TME). This biological barrier surrounds the tumor, severely limiting the infiltration of chemotherapy agents and immune cells. While photodynamic therapy (PDT) offers a promising alternative, existing external light sources, such as lasers, fail to penetrate deep tissues effectively and pose risks of thermal damage and inflammation to healthy organs
To address these challenges, Professor Keon Jae Lee’s team at KAIST, in collaboration with Professor Tae-Hyuk Kwon at UNIST, developed an implantable, shape-morphing 3D micro-LED device capable of effectively delivering light to deep tissues. The key technology lies in the device’s flexible, octopus-like architecture, which allows it to wrap around the entire pancreatic tumor. This mechanical compliance ensures uniform light delivery to the tumor despite the tumor’s physiological expansion or contraction, enabling continuous, low intensity photostimulation that precisely targets cancer cells while preserving normal tissue.
In in-vivo experiments involving mouse models, the device demonstrated remarkable therapeutic efficacy. Within just three days, tumor fibrous tissue was reduced by 64%, and the pancreatic tissue successfully reverted to normal tissue, overcoming the limitations of conventional PDT.
Prof. Keon Jae Lee said, "This research presents a new therapeutic paradigm by directly disrupting the tumor microenvironment, the primary obstacle in pancreatic cancer treatment." He added, "We aim to expand this technology into a smart platform integrated with artificial intelligence (AI) for real-time tumor monitoring and personalized treatment. We are currently seeking partners to advance clinical trials and commercialization for human application."
<Overall concept of 3D Shape-morphing micro-LEDs (SMLEDs). The 3D long-term, low-intensity photodynamic therapy (PDT) system attaches to the pancreatic surface, ensuring stable and continuous light delivery. Initially maintaining a 2D structure, the system morphs into a 3D structure upon implantation to conform to the shape of the pancreas. In in vivo experiments, the device maintained stable adhesion without detachment for four weeks and reduced the pancreatic tumor size by 64%.>
Professor Tae-Hyuk Kwon commented, "While phototherapy is effective for selective cancer treatment, conventional technologies have been limited by the challenges of delivering light to deep tissues and developing suitable photosensitizers." He added, "Building on this breakthrough, we aim to expand effective immune-based therapeutic strategies for targeting intractable cancers."
<Cover Image. The 3D long-term, low-intensity photodynamic therapy (PDT) system, developed by Professor Keon Jae Lee's team at the Department of Materials Science and Engineering at KAIST, was featured as the cover article of the international journal Advanced Materials>
The result, titled "Deeply Implantable, Shape-Morphing, 3D MicroLEDs for Pancreatic Cancer Therapy," was featured as the cover article in Advanced Materials (Volume 37) on December 10, 2025.
2025.12.11 View 3438 -
KAIST, Cancer Cell Nuclear Hypertrophy May Suppress Spread
<(From Left) Ph.D candidate Saemyeong Hong, Dr. Changgon Kim, Professor Joon Kim, Professor Ji Hun Kim>
In tissue biopsies, cancer cells are frequently observed to have nuclei (the cell's genetic information storage) larger than normal. Until now, this was considered a sign that the cancer was worsening, but the exact cause and effect had not been elucidated. In this study, the KAIST research team found that cancer cell nuclear hypertrophy is not a cause of malignancy but a temporary response to replication stress, and that it can, in fact, suppress metastasis. This discovery is expected to lead to the development of new diagnostic and therapeutic strategies for cancer and metastasis inhibition.
KAIST (President Kwang Hyung Lee) announced on the September 26th that a research team led by Professor Joon Kim of the Graduate School of Medical Science and Engineering, in collaboration with the research teams of Professor Ji Hun Kim and Professor You-Me Kim, discovered the molecular reason why the nucleus enlarges in cancer cells. This achievement provides an important clue for understanding nuclear hypertrophy, a phenomenon frequently observed in pathological examinations but whose direct cause and relationship with cancer development were unclear.
The research team confirmed that DNA replication stress (the burden and error signal that occurs when a cell copies its DNA), which is common in cancer cells, causes the 'actin' protein inside the nucleus to aggregate (polymerize), which is the direct cause of the nuclear enlargement.
<Mechanisms Inducing Nuclear Enlargement in Cancer Cells and Its Impact on Cellular Physiology>
This result suggests that the change in cancer cell nuclear size may not simply be a "trait evolved by the cancer cell for its benefit." Rather, it suggests that it is a temporary, makeshift response to stress, and that it may impose constraints on the cancer cell's potential for metastasis.
Therefore, future research needs to explore whether changes in nuclear size can become a target for cancer treatment or a clue related to the suppression of metastasis. That is, nuclear hypertrophy may be a temporary response to replication stress and should not necessarily be seen as indicating the malignancy of the cancer.
This conclusion was substantiated through: (1) Gene Function Screening (inhibiting thousands of genes sequentially to find the key genes involved in nuclear size regulation); (2) Transcriptome Analysis (confirming which gene programs are activated when the nucleus enlarges); (3) 3D Genome Structure Analysis (Hi-C), which revealed that nuclear hypertrophy is not just a size change but is connected to changes in DNA folding and gene arrangement; and (4) Mouse Xenograft Models (confirming that cancer cells with enlarged nuclei actually have reduced motility and metastatic ability).
Professor Joon Kim of the Graduate School of Medical Science and Engineering said, "We confirmed that DNA replication stress disrupts the nuclear size balance, explaining the underlying mechanism of long-standing pathological observations," adding, "The possibility of utilizing nuclear structural changes as a new indicator for cancer diagnosis and metastasis prediction has now opened up."
Dr. Changgon Kim (currently a Hematology and Oncology specialist at Korea University Anam Hospital) and Saemyeong Hong, a PhD candidate from the KAIST Graduate School of Medical Science and Engineering, participated as co-first authors in this study. The results were published online in the international journal PNAS (Proceedings of the National Academy of Sciences of the United States of America) on September 9th.
※ Paper Title: Replication stress-induced nuclear hypertrophy alters chromatin topology and impacts cancer cell fitness ※ DOI: https://doi.org/10.1073/pnas.2424709122
Meanwhile, this research was supported by the Mid-career Researcher Program and the Engineering Research Center (ERC) program of the National Research Foundation of Korea.
2025.09.29 View 3307 -
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 7253 -
KAIST Develops Virtual Staining Technology for 3D Histopathology
Moving beyond traditional methods of observing thinly sliced and stained cancer tissues, a collaborative international research team led by KAIST has successfully developed a groundbreaking technology. This innovation uses advanced optical techniques combined with an artificial intelligence-based deep learning algorithm to create realistic, virtually stained 3D images of cancer tissue without the need for serial sectioning nor staining. This breakthrough is anticipated to pave the way for next-generation non-invasive pathological diagnosis.
< Photo 1. (From left) Juyeon Park (Ph.D. Candidate, Department of Physics), Professor YongKeun Park (Department of Physics) (Top left) Professor Su-Jin Shin (Gangnam Severance Hospital), Professor Tae Hyun Hwang (Vanderbilt University School of Medicine) >
KAIST (President Kwang Hyung Lee) announced on the 26th that a research team led by Professor YongKeun Park of the Department of Physics, in collaboration with Professor Su-Jin Shin's team at Yonsei University Gangnam Severance Hospital, Professor Tae Hyun Hwang's team at Mayo Clinic, and Tomocube's AI research team, has developed an innovative technology capable of vividly displaying the 3D structure of cancer tissues without separate staining.
For over 200 years, conventional pathology has relied on observing cancer tissues under a microscope, a method that only shows specific cross-sections of the 3D cancer tissue. This has limited the ability to understand the three-dimensional connections and spatial arrangements between cells.
To overcome this, the research team utilized holotomography (HT), an advanced optical technology, to measure the 3D refractive index information of tissues. They then integrated an AI-based deep learning algorithm to successfully generate virtual H&E* images.* H&E (Hematoxylin & Eosin): The most widely used staining method for observing pathological tissues. Hematoxylin stains cell nuclei blue, and eosin stains cytoplasm pink.
The research team quantitatively demonstrated that the images generated by this technology are highly similar to actual stained tissue images. Furthermore, the technology exhibited consistent performance across various organs and tissues, proving its versatility and reliability as a next-generation pathological analysis tool.
< Figure 1. Comparison of conventional 3D tissue pathology procedure and the 3D virtual H&E staining technology proposed in this study. The traditional method requires preparing and staining dozens of tissue slides, while the proposed technology can reduce the number of slides by up to 10 times and quickly generate H&E images without the staining process. >
Moreover, by validating the feasibility of this technology through joint research with hospitals and research institutions in Korea and the United States, utilizing Tomocube's holotomography equipment, the team demonstrated its potential for full-scale adoption in real-world pathological research settings.
Professor YongKeun Park stated, "This research marks a major advancement by transitioning pathological analysis from conventional 2D methods to comprehensive 3D imaging. It will greatly enhance biomedical research and clinical diagnostics, particularly in understanding cancer tumor boundaries and the intricate spatial arrangements of cells within tumor microenvironments."
< Figure 2. Results of AI-based 3D virtual H&E staining and quantitative analysis of pathological tissue. The virtually stained images enabled 3D reconstruction of key pathological features such as cell nuclei and glandular lumens. Based on this, various quantitative indicators, including cell nuclear distribution, volume, and surface area, could be extracted. >
This research, with Juyeon Park, a student of the Integrated Master’s and Ph.D. Program at KAIST, as the first author, was published online in the prestigious journal Nature Communications on May 22.
(Paper title: Revealing 3D microanatomical structures of unlabeled thick cancer tissues using holotomography and virtual H&E staining.
[https://doi.org/10.1038/s41467-025-59820-0]
This study was supported by the Leader Researcher Program of the National Research Foundation of Korea, the Global Industry Technology Cooperation Center Project of the Korea Institute for Advancement of Technology, and the Korea Health Industry Development Institute.
2025.05.26 View 13571 -
KAIST Discovers Molecular Switch that Reverses Cancerous Transformation at the Critical Moment of Transition
< (From left) PhD student Seoyoon D. Jeong, (bottom) Professor Kwang-Hyun Cho, (top) Dr. Dongkwan Shin, Dr. Jeong-Ryeol Gong >
Professor Kwang-Hyun Cho’s research team has recently been highlighted for their work on developing an original technology for cancer reversal treatment that does not kill cancer cells but only changes their characteristics to reverse them to a state similar to normal cells. This time, they have succeeded in revealing for the first time that a molecular switch that can induce cancer reversal at the moment when normal cells change into cancer cells is hidden in the genetic network.
KAIST (President Kwang-Hyung Lee) announced on the 5th of February that Professor Kwang-Hyun Cho's research team of the Department of Bio and Brain Engineering has succeeded in developing a fundamental technology to capture the critical transition phenomenon at the moment when normal cells change into cancer cells and analyze it to discover a molecular switch that can revert cancer cells back into normal cells.
A critical transition is a phenomenon in which a sudden change in state occurs at a specific point in time, like water changing into steam at 100℃. This critical transition phenomenon also occurs in the process in which normal cells change into cancer cells at a specific point in time due to the accumulation of genetic and epigenetic changes.
The research team discovered that normal cells can enter an unstable critical transition state where normal cells and cancer cells coexist just before they change into cancer cells during tumorigenesis, the production or development of tumors, and analyzed this critical transition state using a systems biology method to develop a cancer reversal molecular switch identification technology that can reverse the cancerization process. They then applied this to colon cancer cells and confirmed through molecular cell experiments that cancer cells can recover the characteristics of normal cells.
This is an original technology that automatically infers a computer model of the genetic network that controls the critical transition of cancer development from single-cell RNA sequencing data, and systematically finds molecular switches for cancer reversion by simulation analysis. It is expected that this technology will be applied to the development of reversion therapies for other cancers in the future.
Professor Kwang-Hyun Cho said, "We have discovered a molecular switch that can revert the fate of cancer cells back to a normal state by capturing the moment of critical transition right before normal cells are changed into an irreversible cancerous state."
< Figure 1. Overall conceptual framework of the technology that automatically constructs a molecular regulatory network from single-cell RNA sequencing data of colon cancer cells to discover molecular switches for cancer reversion through computer simulation analysis. Professor Kwang-Hyun Cho's research team established a fundamental technology for automatic construction of a computer model of a core gene network by analyzing the entire process of tumorigenesis of colon cells turning into cancer cells, and developed an original technology for discovering the molecular switches that can induce cancer cell reversal through attractor landscape analysis. >
He continued, "In particular, this study has revealed in detail, at the genetic network level, what changes occur within cells behind the process of cancer development, which has been considered a mystery until now." He emphasized, "This is the first study to reveal that an important clue that can revert the fate of tumorigenesis is hidden at this very critical moment of change."
< Figure 2. Identification of tumor transition state using single-cell RNA sequencing data from colorectal cancer. Using single-cell RNA sequencing data from colorectal cancer patient-derived organoids for normal and cancerous tissues, a critical transition was identified in which normal and cancerous cells coexist and instability increases (a-d). The critical transition was confirmed to show intermediate levels of major phenotypic features related to cancer or normal tissues that are indicative of the states between the normal and cancerous cells (e). >
The results of this study, conducted by KAIST Dr. Dongkwan Shin (currently at the National Cancer Center), Dr. Jeong-Ryeol Gong, and doctoral student Seoyoon D. Jeong jointly with a research team at Seoul National University that provided the organoids (in vitro cultured tissues) from colon cancer patient, were published as an online paper in the international journal ‘Advanced Science’ published by Wiley on January 22nd.
(Paper title: Attractor landscape analysis reveals a reversion switch in the transition of colorectal tumorigenesis) (DOI: https://doi.org/10.1002/advs.202412503)
< Figure 3. Reconstruction of a dynamic network model for the transition state of colorectal cancer.
A new technology was established to build a gene network computer model that can simulate the dynamic changes between genes by integrating single-cell RNA sequencing data and existing experimental results on gene-to-gene interactions in the critical transition of cancer. (a). Using this technology, a gene network computer model for the critical transition of colorectal cancer was constructed, and the distribution of attractors representing normal and cancer cell phenotypes was investigated through attractor landscape analysis (b-e). >
This study was conducted with the support of the National Research Foundation of Korea under the Ministry of Science and ICT through the Mid-Career Researcher Program and Basic Research Laboratory Program and the Disease-Centered Translational Research Project of the Korea Health Industry Development Institute (KHIDI) of the Ministry of Health and Welfare.
< Figure 4. Quantification of attractor landscapes and discovery of transcription factors for cancer reversibility through perturbation simulation analysis. A methodology for implementing discontinuous attractor landscapes continuously from a computer model of gene networks and quantifying them as cancer scores was introduced (a), and attractor landscapes for the critical transition of colorectal cancer were secured (b-d). By tracking the change patterns of normal and cancer cell attractors through perturbation simulation analysis for each gene, the optimal combination of transcription factors for cancer reversion was discovered (e-h). This was confirmed in various parameter combinations as well (i). >
< Figure 5. Identification and experimental validation of the optimal target gene for cancer reversion. Among the common target genes of the discovered transcription factor combinations, we identified cancer reversing molecular switches that are predicted to suppress cancer cell proliferation and restore the characteristics of normal colon cells (a-d). When inhibitors for the molecular switches were treated to organoids derived from colon cancer patients, it was confirmed that cancer cell proliferation was suppressed and the expression of key genes related to cancer development was inhibited (e-h), and a group of genes related to normal colon epithelium was activated and transformed into a state similar to normal colon cells (i-j). >
< Figure 6. Schematic diagram of the research results. Professor Kwang-Hyun Cho's research team developed an original technology to systematically discover key molecular switches that can induce reversion of colon cancer cells through a systems biology approach using an attractor landscape analysis of a genetic network model for the critical transition at the moment of transformation from normal cells to cancer cells, and verified the reversing effect of actual colon cancer through cellular experiments. >
2025.02.05 View 51630 -
KAIST Develops Foundational Technology to Revert Cancer Cells to Normal Cells
Despite the development of numerous cancer treatment technologies, the common goal of current cancer therapies is to eliminate cancer cells. This approach, however, faces fundamental limitations, including cancer cells developing resistance and returning, as well as severe side effects from the destruction of healthy cells.
< (From top left) Bio and Brain Engineering PhD candidates Juhee Kim, Jeong-Ryeol Gong, Chun-Kyung Lee, and Hoon-Min Kim posed for a group photo with Professor Kwang-Hyun Cho >
KAIST (represented by President Kwang Hyung Lee) announced on the 20th of December that a research team led by Professor Kwang-Hyun Cho from the Department of Bio and Brain Engineering has developed a groundbreaking technology that can treat colon cancer by converting cancer cells into a state resembling normal colon cells without killing them, thus avoiding side effects.
The research team focused on the observation that during the oncogenesis process, normal cells regress along their differentiation trajectory. Building on this insight, they developed a technology to create a digital twin of the gene network associated with the differentiation trajectory of normal cells.
< Figure 1. Technology for creating a digital twin of a gene network from single-cell transcriptome data of a normal cell differentiation trajectory. Professor Kwang-Hyun Cho's research team developed a digital twin creation technology that precisely observes the dynamics of gene regulatory relationships during the process of normal cells differentiating along a differentiation trajectory and analyzes the relationships among key genes to build a mathematical model that can be simulated (A-F). In addition, they developed a technology to discover key regulatory factors that control the differentiation trajectory of normal cells by simulating and analyzing this digital twin. >
< Figure 2. Digital twin simulation simulating the differentiation trajectory of normal colon cells. The dynamics of single-cell transcriptome data for the differentiation trajectory of normal colon cells were analyzed (A) and a digital twin of the gene network was developed representing the regulatory relationships of key genes in this differentiation trajectory (B). The simulation results of the digital twin confirm that it readily reproduces the dynamics of single-cell transcriptome data (C, D). >
Through simulation analysis, the team systematically identified master molecular switches that induce normal cell differentiation. When these switches were applied to colon cancer cells, the cancer cells reverted to a normal-like state, a result confirmed through molecular and cellular experiments as well as animal studies.
< Figure 3. Discovery of top-level key control factors that induce differentiation of normal colon cells. By applying control factor discovery technology to the digital twin model, three genes, HDAC2, FOXA2, and MYB, were discovered as key control factors that induce differentiation of normal colon cells (A, B). The results of simulation analysis of the regulatory effects of the discovered control factors through the digital twin confirmed that they could induce complete differentiation of colon cells (C). >
< Figure 4. Verification of the effect of the key control factors discovered using colon cancer cells and animal experiments on the reversibility of colon cancer. The key control factors of the normal colon cell differentiation trajectory discovered through digital twin simulation analysis were applied to actual colon cancer cells and colon cancer mouse animal models to experimentally verify the effect of cancer reversibility. The key control factors significantly reduced the proliferation of three colon cancer cell lines (A), and this was confirmed in the same way in animal models (B-D). >
This research demonstrates that cancer cell reversion can be systematically achieved by analyzing and utilizing the digital twin of the cancer cell gene network, rather than relying on serendipitous discoveries. The findings hold significant promise for developing reversible cancer therapies that can be applied to various types of cancer.
< Figure 5. The change in overall gene expression was confirmed through the regulation of the identified key regulatory factors, which converted the state of colon cancer cells to that of normal colon cells. The transcriptomes of colon cancer tissues and normal colon tissues from more than 400 colon cancer patients were compared with the transcriptomes of colon cancer cell lines and reversible colon cancer cell lines, respectively. The comparison results confirmed that the regulation of the identified key regulatory factors converted all three colon cancer cell lines to a state similar to the transcriptome expression of normal colon tissues. >
Professor Kwang-Hyun Cho remarked, "The fact that cancer cells can be converted back to normal cells is an astonishing phenomenon. This study proves that such reversion can be systematically induced."
He further emphasized, "This research introduces the novel concept of reversible cancer therapy by reverting cancer cells to normal cells. It also develops foundational technology for identifying targets for cancer reversion through the systematic analysis of normal cell differentiation trajectories."
This research included contributions from Jeong-Ryeol Gong, Chun-Kyung Lee, Hoon-Min Kim, Juhee Kim, and Jaeog Jeon, and was published in the online edition of the international journal Advanced Science by Wiley on December 11. (Title: “Control of Cellular Differentiation Trajectories for Cancer Reversion”) DOI: https://doi.org/10.1002/advs.202402132
< Figure 6. Schematic diagram of the research results. Professor Kwang-Hyun Cho's research team developed a source technology to systematically discover key control factors that can induce reversibility of colon cancer cells through a systems biology approach and a digital twin simulation analysis of the differentiation trajectory of normal colon cells, and verified the effects of reversion on actual colon cancer through molecular cell experiments and animal experiments. >
The study was supported by the Ministry of Science and ICT and the National Research Foundation of Korea through the Mid-Career Researcher Program and Basic Research Laboratory Program. The research findings have been transferred to BioRevert Inc., where they will be used for the development of practical cancer reversion therapies.
2024.12.23 View 136994 -
A KAIST-SNUH Team Devises a Way to Make Mathematical Predictions to find Metabolites Related to Somatic Mutations in Cancers
Cancer is characterized by abnormal metabolic processes different from those of normal cells. Therefore, cancer metabolism has been extensively studied to develop effective diagnosis and treatment strategies. Notable achievements of cancer metabolism studies include the discovery of oncometabolites* and the approval of anticancer drugs by the U.S. Food and Drug Administration (FDA) that target enzymes associated with oncometabolites. Approved anticancer drugs such as ‘Tibsovo (active ingredient: ivosidenib)’ and ‘Idhifa (active ingredient: enasidenib)’ are both used for the treatment of acute myeloid leukemia. Despite such achievements, studying cancer metabolism, especially oncometabolites, remains challenging due to time-consuming and expensive methodologies such as metabolomics. Thus, the number of confirmed oncometabolites is very small although a relatively large number of cancer-associated gene mutations have been well studied.
*Oncometabolite: A metabolite that shows pro-oncogenic function when abnormally accumulated in cancer cells. An oncometabolite is often generated as a result of gene mutations, and this accumulation promotes the growth and survival of cancer cells. Representative oncometabolites include 2-hydroxyglutarate, succinate, and fumarate.
On March 18th, a KAIST research team led by Professor Hyun Uk Kim from the Department of Chemical and Biomolecular Engineering developed a computational workflow that systematically predicts metabolites and metabolic pathways associated with somatic mutations in cancer through collaboration with research teams under Prof Youngil Koh, Prof. Hongseok Yun, and Prof. Chang Wook Jeong from Seoul National University Hospital.
The research teams have successfully reconstructed patient-specific genome-scale metabolic models (GEMs)* for 1,043 cancer patients across 24 cancer types by integrating publicly available cancer patients’ transcriptome data (i.e., from international cancer genome consortiums such as PCAWG and TCGA) into a generic human GEM. The resulting patient-specific GEMs make it possible to predict each patient’s metabolic phenotypes.
*Genome-scale metabolic model (GEM): A computational model that mathematically describes all of the biochemical reactions that take place inside a cell. It allows for the prediction of the cell’s metabolic phenotypes under various genetic and/or environmental conditions.
< Figure 1. Schematic diagram of a computational methodology for predicting metabolites and metabolic pathways associated with cancer somatic mutations. of a computational methodology for predicting metabolites and metabolic pathways associated with cancer somatic mutations. >
The team developed a four-step computational workflow using the patient-specific GEMs from 1,043 cancer patients and somatic mutation data obtained from the corresponding cancer patients. This workflow begins with the calculation of the flux-sum value of each metabolite by simulating the patient-specific GEMs. The flux-sum value quantifies the intracellular importance of a metabolite. Next, the workflow identifies metabolites that appear to be significantly associated with specific gene mutations through a statistical analysis of the predicted flux-sum data and the mutation data. Finally, the workflow selects altered metabolic pathways that significantly contribute to the biosynthesis of the predicted oncometabolite candidates, ultimately generating metabolite-gene-pathway sets as an output.
The two co-first authors, Dr. GaRyoung Lee (currently a postdoctoral fellow at the Dana-Farber Cancer Institute and Harvard Medical School) and Dr. Sang Mi Lee (currently a postdoctoral fellow at Harvard Medical School) said, “The computational workflow developed can systematically predict how genetic mutations affect cellular metabolism through metabolic pathways. Importantly, it can easily be applied to different types of cancer based on the mutation and transcriptome data of cancer patient cohorts.”
Prof. Kim said, “The computational workflow and its resulting prediction outcomes will serve as the groundwork for identifying novel oncometabolites and for facilitating the development of various treatment and diagnosis strategies”.
This study, which was supported by the National Research Foundation of Korea, has been published online in Genome Biology, a representative journal in the field of biotechnology and genetics, under the title "Prediction of metabolites associated with somatic mutations in cancers by using genome‑scale metabolic models and mutation data".
2024.03.18 View 13281