Researchers have developed a new method to alter the progression of diseases and engineer tumors that are more susceptible to treatment. By creating a flexible genetic system, they transformed cancer cells into a ‘Trojan horse,’ prompting them to self-destruct and eliminate nearby drug-resistant cancer cells – a unique strategy to tackle the diverse and variable nature of cancer.
Dealing with cancer can often seem like a never-ending challenge. The disease evolves and becomes resistant to treatments, making it difficult for clinicians to predict when and where resistance will develop, putting them at a disadvantage. However, a team led by researchers from Penn State has discovered a way to reshape the progression of diseases and develop tumors that are more responsive to treatment.
They devised a modular genetic system that transforms cancer cells into a “Trojan horse,” leading them to self-destruct and eliminate neighboring drug-resistant cancer cells. Tested in human cell cultures and in mice to provide evidence, this system outsmarted a wide range of resistance mechanisms.
The results were published today (July 4) in the journal Nature Biotechnology. Additionally, the researchers have filed a preliminary patent application for the technology outlined in their study.
“The concept originated from frustration. While we are making progress in developing new cancer treatments, how can we explore potential cures for more advanced cancers?” stated Justin Pritchard, Dorothy Foehr Huck and J. Lloyd Huck Early Career Entrepreneurial Associate Professor of Biomedical Engineering and the senior author of the study. “Selection gene drives represent a potent new approach for evolution-guided anti-cancer therapy. I find it intriguing that we can turn a tumor’s inherent evolutionary trait against itself.”
Pritchard highlighted that newer personalized cancer medications often fail not due to their inefficiency but because of the inherent variety and complexity of cancer. Even if an initial therapy is effective, resistance eventually arises, rendering the drug ineffective and allowing the cancer to resurface. Clinicians then find themselves starting over with a new drug until resistance develops once more. This cycle continues with each new treatment until no further options remain.
“It’s like playing Whac-A-Mole. You can’t predict which ‘mole’ will emerge next, making it challenging to determine the best drug for treating the tumor. We are always reacting, caught off guard,” explained Scott Leighow, a postdoctoral scholar in biomedical engineering and the lead author of the study.
The researchers pondered whether they could proactively tackle resistance mechanisms before cancer cells evolve and unpredictably appear. Could they prompt a specific “mole” to emerge on the board, one that they prefer and are equipped to combat?
What began as a theoretical exercise is proving to be effective. The team formulated a modular system called a dual-switch selection gene drive, which they introduced into non-small cell lung cancer cells with an EGFR gene mutation. This mutation serves as a target for existing drugs on the market.
The system consists of two genes or switches. The first switch acts as a selection gene, enabling researchers to toggle drug resistance on and off like a light switch. When the first switch is activated, the genetically altered cells become temporarily resistant to a specific drug, such as a non-small cell lung cancer medication. When the tumor is treated with the drug, the naturally drug-sensitive cancer cells are eliminated, leaving behind the modified resistant cells and a small population of original drug-resistant cells. Over time, the modified cells proliferate, suppressing the growth and evolution of new resistance in the original cells.
The resulting tumor primarily comprises genetically modified cells. Turning off switch one renders the cells drug-sensitive again. Switch two contains the therapeutic element, housing a suicide gene that enables the modified cells to produce a diffusible toxin capable of eliminating both the modified and neighboring unaltered cells.
“This not only eradicates the engineered cells but also targets the surrounding cells, particularly the original resistant population,” Pritchard remarked. “This is crucial for preventing tumor regrowth.”
Initially, the team simulated tumor cell populations and employed mathematical models to validate the concept. Subsequently, they isolated each switch, packaging them into viral vectors and evaluating their functionality in human cancer cell lines individually. They then integrated the two switches into a single system and re-evaluated its efficacy. Upon successful in vitro testing, the team conducted experiments on mice.
However, the researchers aimed not just to demonstrate the system’s functionality but also to assess its versatility. They rigorously tested the system using intricate genetic libraries of resistance variants to confirm that the gene drive could robustly counteract various genetic resistance scenarios that could arise in cancer cell populations.
The results were promising: Only a few engineered cells were necessary to dominate the cancer cell population and eliminate high levels of genetic variability. Pritchard emphasized that this was a significant strength of the study, both conceptually and experimentally.
“The beauty of this approach is that we can target cancer cells proactively without having to await their growth or resistance development, which would be too late at that stage,” Leighow added.
The researchers are currently focused on translating this genetic system so that it can be safely and selectively delivered into growing tumors and potentially metastatic disease.
Other authors from Penn State who contributed to the study include Marco Archetti, an associate professor of biology; Shun Yao, a postdoctoral scholar in biology; Ivan Sokirniy, a graduate student at the Huck Institutes of Life Sciences; and Joshua Reynolds and Zeyu Yang, members of the Department of Biomedical Engineering. Co-author Haider Inam was a doctoral student in biomedical engineering during the research and is currently a research scientist at the Broad Institute of MIT and Harvard. Dominik Wodarz, a professor at the University of California, San Diego, also provided input for the study.
This work was supported by the Huck Institutes of Life Sciences’ HITS Fund, the National Cancer Institute, and the National Institute of Biomedical Imaging and Bioengineering Trailblazer award.
