Susanna Fletcher Greer, Chief Scientific Officer at The V Foundation, shared on LinkedIn:
“One of the things I love most about science is that the best research often begins with a deceptively simple question. In this case, the question the V Foundation grantee Dr. Evgeny Izumchenko and team at the University of Chicago asked was: why does a benign growth sometimes become cancer?
Dr. Izumchenko is studying inverted papilloma; a noncancerous growth that develops in the nasal cavity and sinuses. Most people will never have heard of it, but in a subset of patients it is associated with a rare cancer called sinonasal squamous cell carcinoma. These cancers can be difficult to treat, and because they are so uncommon, they are also really difficult to study.
There simply are not thousands of patients, large datasets, or many clinical trials to help us understand what drives the disease or how best to treat it. That makes every patient sample incredibly valuable.
In this study, the Izumchenko team were able to examine normal tissue, inverted papilloma, and cancer from the same patients. In essence, they had the opportunity to look at what was changing as normal tissue moved toward malignancy. And instead of examining just one piece of the biology, they studied DNA, gene activity, and even mitochondrial DNA to build a much more complete picture of what was happening.
What they found was fascinating and, in retrospect, not surprising: there was not one obvious genetic switch that suddenly transformed a benign growth into cancer. Instead, the biology changed progressively. Meaning, as the tissue moved from normal to papilloma to cancer, programs responsible for cell growth, metabolism, and tissue remodeling became increasingly active, while some of the systems that help eliminate damaged cells or recognize abnormal ones became less active.
To me, this is a great example of why cancer research has moved so far beyond simply looking for a single mutation. Cancer is often an entire biological system being gradually rewired. But understanding what is changing creates another challenge. Once we identify hundreds or even thousands of molecular changes,
- How do we decide which ones matter most?
- Which should we pursue?
- Which might actually become a treatment?
This is where artificial intelligence became particularly useful. And here it was: Dr. Izumchenko used an AI driven platform to analyze the genes that became increasingly active as the disease progressed and to prioritize potential therapeutic targets.
AI did not discover a cure. Instead AI helped answer a much more practical question: of everything we have learned, where should we look next?
And that question led to something interesting. The analysis identified several potential vulnerabilities that can already be targeted by drugs approved for other diseases. That raises the possibility of drug repurposing, where researchers can ask whether an existing therapy might work in a rare cancer with very limited treatment options. The study also identified additional targets that now deserve further laboratory investigation.
These findings do not mean patients have a new treatment tomorrow as these ideas still need to be validated very carefully. Biology always gets the final vote. But I think this paper illustrates one of the most exciting ways AI can contribute to cancer research, particularly in rare cancers.
When you cannot simply make a study bigger, you have to learn more from every sample you have. Today we can generate enormous amounts of biological information from a relatively small number of patients. AI gives researchers another tool to find patterns within that complexity and decide which hypotheses are most worth pursuing.
That is what excites me about AI in cancer research. It is not replacing scientists. It is giving great scientists another way to ask better questions, make more of every precious patient sample, and potentially move promising ideas toward patients faster.
For rare cancers, where every patient and every experiment matters, that could be enormously powerful. And ultimately, that is always the question I come back to: can we use the tools available to us to move cancer research faster and get better answers to patients sooner?
Increasingly, AI is helping us do exactly that.
Find the Izumchenko lab here and read their paper here.”
Other articles featuring Susanna Fletcher Greer on OncoDaily.