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Combating Cancer: A Novel Approach to Reversing Tumor Back to Tissue

  • Writer: Hailey Kim
    Hailey Kim
  • Feb 22
  • 2 min read

After discovering remedies for smallpox, developing antibiotics, and pioneering vaccines that have saved millions of lives, humans are still facing one of the greatest medical challenges of all: cancer. Cancer, a disease characterized by the uncontrollable growth and spread of abnormal cells, remains one of the most feared illnesses worldwide, largely because there is still no single, definitive cure that works universally and without severe side effects.


Current treatments for cancer that are commonly employed include chemotherapy, surgery, and radiation, which are effective in reducing tumor size or eliminating detectable cancer cells, yet also often result in significant relapse rates. Chemotherapy in particular functions by targeting rapidly dividing cells, yet it lacks the ability to distinguish between cancerous and normal cells. As a result, healthy cells such as those in hair follicles and bone marrow are damaged, leading to established side effects, including hair loss, weakened immunity, and nausea.


Overcoming such limitations, a research team led by Korea Advanced Institute of Science and Technology (KAIST) recently reported a groundbreaking possibility.


What if cancer cells could be reprogrammed into their normal form rather than destroyed?


The core of this study is a computational tool developed by the research team called Boolean network inference and control (BENEIN), which can find the “master switches” controlling cell development by analyzing single-cell data and mapping these into gene networks. Thus, it can predict which specific genes are the key "master regulators" that, if controlled, could force cancer cells to resume normal development. To test their framework, the team applied BENEIN to human intestinal cell data, focusing on how normal intestinal cells differentiate into mature enterocytes (the specialized cells lining the gut that absorb nutrients). In colorectal cancer, this differentiation process is disrupted. Cancer cells remain in a more stem-like, undifferentiated state, which enables continuous division.


         Using their computational model, the team identified three genes as critical regulatory nodes preventing normal differentiation: MYB, HDAC2, and FOXA2. In simple terms, these three genes maintain the cancerous identity of colorectal tumor cells.


Source: KAIST News Center
Source: KAIST News Center

To further validate their predictions, researchers suppressed (knocked down) these three genes in colorectal cancer cells. Notably, the genes were not eliminated entirely; rather, their activity was reduced to disrupt the malignant cell networks.


The findings were compelling and exceeded initial expectations. Primarily, the proliferation rates (how quickly cancer cells copy their DNA and divide into new cells) decreased, indicating a slower tumor development. Second, gene expressions were altered and shifted from oncogenic (causing development of tumor) to neutral, mature enterocytes. Having validated through petri-dish observations, tests on mouse models were also conducted, where similar results could be seen. Tumor growth was reduced, and cells aligned more with their normal tissue structure.


What makes this study particularly significant is that it has shattered the previous conception that cancer should be treated by directly attacking cancerous cells, and provided an alternative potential of “resetting” cells’ lost regulatory network and differentiation pathways. While still in its early stages, this research offers a promising groundwork for future differentiation-based cancer treatments.



Citations


암세포를 정상 세포로 되돌리는 기술, 카이스트 연구진 개발. 한국암재활협회 https://www.kcrs.co.kr/info/info_010100.html?bmain=view&uid=346 (2024).

Gong, J.-R. et al. Control of Cellular Differentiation Trajectories for Cancer Reversion. Advanced Science (2024).

KAIST, 암세포 정상세포로 되돌리는 혁신적 치료 기술 개발. 충청일보 https://www.ccdailynews.com/news/articleView.html?idxno=2316076 (2024).

 
 
 

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Hailey Kim @kxxlin8    

Serena Lim  @dhxgj85

Sarah Kim   @sarahk1m._

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