Scientists have developed a computer framework to identify key gene regulators that control cell differentiation and can be targeted to help reverse cancer.
To do this, the team led by Kwang-Hyun Cho of Korea Advanced Institute of Science and Technology (KAIST) developed a system based on Boolean logic — a type of mathematical framework where data has only two possible states, like “true” or “false.” In this case, genes are modeled as either “on” or “off,” helping researchers understand how they regulate cell behavior.
The resultant system is capable of reconstructing gene regulatory networks and identifying master regulators that can cause cells to become cancerous. The team named it BENEIN (Boolean Network Inference and Control), describing its creation in the journal Advanced Science.
“Cellular differentiation is the process by which immature progenitor cells develop into specialized types of cells, such as muscle, nerve, or intestinal cells, performing distinct biological functions,” Cho said. “This tightly regulated process is controlled by precisely tuned gene regulatory networks and signaling cascades. However, in cancer, genetic mutations disrupt these networks, causing cells to lose their specialized functions.”
This can result in these cells converting to an immature state that sees them rapidly increase in number. When cells undergo this “dedifferentiation,” this can cause them to develop cancerous traits through a transformation known as “tumorigenesis.”
Cho’s team builds upon the idea that normal cell characteristics can be restored and cancer-specific features suppressed in a process called re-differentiation. By either activating or suppressing the master regulators, cancer cells can potentially be reverted to a normal state.
Identifying the master regulators
This practice of “cancer reversion” is a relatively new therapeutic approach to cancer and a promising alternative to conventional cancer therapies. It aims to revert cancer cells into their differentiated and non-cancerous state by inducing the re-expression of these genes. To do this, the master regulators that first caused this dedifferentiation must be identified — but that is no mean feat.
“The identification of master regulators involves several complex factors. Identifying master regulators remains challenging due to the nonlinear and dynamic nature of gene regulatory networks,” Cho said. “These networks exhibit complex feedback loops and interactions among numerous genes, which makes it difficult to identify regulators with the most significant influence.”
Cho added that gene regulation is complex and unpredictable, characterized by dynamic interactions and feedback loops. Thus, it is challenging to accurately model entire gene regulatory networks. However, Boolean network modeling simplifies this by reducing gene expression to the binary states of “on” and “off.”
“This computational efficiency makes Boolean networks particularly suitable for studying complex biological processes like cellular differentiation,” Cho explained. “BENEIN leverages these advantages by reconstructing gene regulatory networks from single-cell transcriptome data.”
Once master regulators were identified using BENEIN, the team validated their role using computer simulations and experimental “knockdowns” where the gene is essentially turned off in cancer cell lines. They found that by targeting master regulators, they were able to reprogram cancer cells by inducing differentiation and thus suppressing malignancy.
“This approach represents a promising alternative to traditional cancer therapies. Its ability to identify minimal control targets,and simulate their effects on differentiation pathways highlights its effectiveness,” Cho said. “These features establish BENEIN as a robust tool for understanding and controlling cellular differentiation. This highlights the therapeutic potential of cancer reversion.”
While the team tested BENEIN using colorectal cancer cells, they think its use could extend to other cancers and even to other cellular diseases.
“The applications of BENEIN extend beyond cancer reversion. By identifying key regulators of cell state transitions, BENEIN holds potential for broader applications in cell fate control,” Cho said. “This opens new possibilities for studying and manipulating the regulatory mechanisms underlying various cellular states.”
There is much work to be done before the team’s results can be used in a real-world setting.
“The BENEIN system is not yet ready for clinical application. While the results are promising, further preclinical studies and extensive validation are required to confirm the safety and efficacy of this approach in humans,” Cho concluded. “Additionally, our team is actively developing other systems to identify reversion targets for various cancer types, expanding the potential applications of this methodology.”
Reference: J-R. Gong., C-K Lee., H-M Kim., et al., Control of Cellular Differentiation Trajectories for Cancer Reversion, Advanced Science., (2024), DOI: 10.1002/advs.202402132
Feature image credit: DeepMind on Unsplash
