Researchers at NYU Langone Health announced on April 15 a new model that may explain how cancer cells develop resistance to treatments, even those they have not previously encountered. The findings were published as the cover story in the journal Nature.
The study centers on AP-1 proteins, which are quickly activated in cells under stress such as chemotherapy exposure. The authors suggest these proteins play a role in enabling cancer cells to adapt and survive by changing gene activity without altering their DNA sequence.
Itai Yanai, PhD, professor at NYU Langone, said, “For decades, our understanding of drug resistance was that it was primarily caused by the selection of rarely occurring genetic mutations—or changes in the DNA code—that happen to be effective against a specific drug.” He continued, “More recently, we’ve learned that cells can change cellular states to adapt to treatments, but the mechanism has not been clear. We propose the existence of a surprising mechanism whereby cells adapt on the fly, and which may explain why advanced cancers become virtually untreatable.”
First author Gustavo S. França, PhD described how this process works: “Our AP-1 model works like an evolutionary algorithm inside each cancer cell. By deploying AP-1, the cell is able to generate different ways to regulate its genes and then select the one that is most adaptive to its environment.” According to their research, AP-1 proteins form various combinations or dimers that regulate different sets of genes depending on cellular context. This flexibility allows cancer cells to test gene expression patterns until they find one that helps them survive treatment.
The researchers believe this adaptability acts as a toolkit for survival and leads over time to epigenetic changes—heritable alterations in gene activity—that allow resistant traits to be passed down through generations of tumor cells.
Yanai said their findings could influence future treatment strategies: “Instead of targeting its particular state, as most current therapies do, we may also need to target its ability to adapt. If we can block this AP-1 learning mechanism, we may be able to prevent cancer cells from ever becoming treatment resistant in the first place.” The team plans further studies using CRISPR gene editing and single-cell analysis technologies.
França added about next steps: “Our next step is to dissect the AP-1 phosphorylation code. By understanding precisely which AP-1 pairs drive resistance to specific therapies, we can begin to combine conventional cancer therapies with anti-adaptation agents to create treatments that are effective for longer.”
