Abstract:

A research team from the Korea Advanced Institute of Science and Technology (KAIST), led by Professor Kwang-Hyun Cho, has developed an innovative technology that enables the reversal of cancer cells to a phenotypic state similar to normal cells without requiring their destruction. This approach, based on systems biology and attractor landscape analysis, uses a computational model based on single-cell RNA sequencing (scRNA-seq) data to identify key molecular switches (HDAC2, FOXA2, and MYB) that regulate cellular redifferentiation. Successfully applied to colorectal cancer cells, this method has shown the ability to reverse tumorigenesis both in vitro and in vivo, offering a promising alternative to conventional therapies that eliminate tumor cells, which carry severe side effects and the risk of recurrence. Published on January 22, 2025, in Advanced Science (DOI: 10.1002/advs.202402132), this work, supported by the National Research Foundation of Korea, the Ministry of Science and ICT, and the Korea Health Industry Development Institute, has been transferred to BioRevert Inc. for clinical development, marking a step toward less invasive and more effective cancer treatments.

Introduction:

Cancer is one of the leading causes of death worldwide, and current treatments, though effective, are often invasive and associated with severe side effects. It is an irreversible disease due to the accumulation of genetic alterations, such as mutations in oncogenes or tumor suppressor genes, which trigger abnormal cellular behaviors (Martincorena et al., 2017). However, experimental evidence has shown that under certain conditions, cancer cells can revert to non-malignant phenotypes, a phenomenon known as tumor reversion (Telerman & Amson, 2009; Cho et al., 2017). Unlike conventional therapies, such as chemotherapy, radiotherapy, or surgery, which focus on eradicating tumor cells but often generate systemic toxicity, damage to healthy tissues, and recurrence due to the persistence of resistant cells, a team from KAIST, led by Professor Kwang-Hyun Cho of the Department of Biomedical Engineering, has developed an innovative technology based on molecular reprogramming. This approach induces the redifferentiation of cancer cells into phenotypic states similar to normal cells, avoiding their destruction and offering a promising alternative that reduces severe side effects and the risk of recurrence associated with traditional treatments.

Methods and Results:

The study combined systems biology with molecular experimentation to develop and validate a tumor reversion strategy. Initially, the attractor landscape analysis was used to map the differentiation trajectories during tumorigenesis, representing cellular states as attractors in a multidimensional space (Huang et al., 2009). Using scRNA-seq data from colorectal cancer cells and adjacent normal tissues, a dynamic model based on the BENEIN framework was constructed, which inferred key gene interactions and simulated transitions between cellular states (Kim et al., 2017). The simulations identified HDAC2, FOXA2, and MYB as master regulators whose modulation could induce redifferentiation.

To validate these findings, in vitro experiments were conducted on colorectal cancer cell lines, manipulating the expression of the identified genes using techniques such as siRNA and CRISPR/Cas9. Post-treatment transcriptomic analyses revealed a partial restoration of gene expression patterns characteristic of normal epithelial cells, with reexpression of differentiation markers and suppression of genes associated with tumor proliferation. In vivo assays in immunodeficient mice confirmed these results, showing a significant reduction in tumor size and metastatic capacity, with no systemic toxicity. Histopathological and molecular analysis corroborated the cellular redifferentiation, demonstrating the feasibility of tumor reversion as a therapeutic strategy (Cho et al., 2016).

Discussion and Conclusions:

This study demonstrates that tumor reversion is a feasible process through the manipulation of genetic networks at critical transition points, using a combination of internal controls (IC) and external controls (EC). The IC, based on the modulation of genes like HDAC2, FOXA2, and MYB, remodels the attractor landscape to destabilize malignant states, while the EC, through extracellular signals, stabilizes normal phenotypes (Shin & Cho, 2023). This approach, validated in colorectal cancer, overcomes the limitations of previous differentiation therapies, which have been successful in leukemias such as acute promyelocytic leukemia, but face challenges in solid tumors due to the complexity of their signaling networks (Lo-Coco et al., 2013).

The integration of scRNA-seq analysis and computational modeling allows for a systematic approach to identifying therapeutic targets, providing a scalable framework for other cancers. However, challenges remain, such as optimizing the delivery of control factors and ensuring the long-term stability of reverted phenotypes (Powers & Pollack, 2016). Conceptualizing cancer as a chronic manageable disease rather than a lethal condition could transform clinical management, allowing patients to maintain a high quality of life through continuous or repetitive EC regimens.

In conclusion, this work establishes a new paradigm in cancer treatment, highlighting the potential of systems biology to develop less invasive reversion therapies. The transfer to BioRevert Inc. and the plans for clinical trials mark a step toward translating these findings into practical applications, with significant implications for modern oncology.

• Expansion to other types of tumors: Extend studies to cancers such as breast, lung, and pancreas to assess the universality of the identified molecular switches.
• Optimization of combined IC/EC therapies: Develop strategies integrating internal controls (gene modulation) and external controls (drugs or environmental signals) to maximize the stability of reversion.
• Personalized medicine: Implement scRNA-seq analysis to design therapies tailored to each patient’s molecular profile, optimizing effectiveness.

• Long-term clinical trials: Initiate clinical studies to validate the safety and efficacy of these therapies in humans, with a focus on preventing recurrences and managing cancer as a chronic disease.
• Integration of multi-omics: Incorporate proteomic and epigenomic data to improve the accuracy of dynamic models and the identification of therapeutic targets.