Cornell Team Adapts Precision Labeling Method to Map Cancer-Specific Protein Interactions

A Cornell University-led research group has adapted a photochemically driven labeling technique to capture protein-to-protein interactions that occur specifically in cancer cells, an approach that could eventually lead to targeted therapies for prostate, small-cell lung, pancreatic and other deadly cancers.

The method, called µMap (MicroMap), is a nanoscale proximity labeling technique that the group, led by Ciaran Seath, adapted to more precisely label protein-protein interactions in cancer-specific cells. Rather than measuring whether protein levels are elevated, the technique identifies where proteins are located and what they are interacting with inside the cell.

“Rather than looking at whether protein levels are elevated or not, we’re looking at where they are,” said Seath, senior author of the paper published in Nature Chemical Biology. “We’ve identified something that is really vital for this set of cancers to grow and proliferate, and that kind of opens up this whole field.”

To demonstrate the approach, the team applied it to c-Myc, a transcription factor that controls cellular growth and is deregulated in nearly half of all cancers but has been difficult to study directly. Using µMap, the researchers attached chemical antennas to c-Myc proteins in three prostate cell lines representing healthy prostate, AR-negative prostate cancer and AR-positive prostate cancer, then compared the resulting “interactomes” across all three. The comparison revealed several shared interaction partners, and cross-referencing them with the open-access DepMap cancer database highlighted a signaling protein called SLK as a protein of interest in AR-negative prostate cancer specifically.

A closer look using the labeling technique showed SLK’s localization in cancer cells was different from normal—it moved into the nucleus, where it helped stabilize c-Myc, despite being present at similar concentrations in both healthy and cancerous cells.

“When you have this transcription factor that has maybe 10, 20 or 30 times its regular protein, it can start to go places it shouldn’t and interact with things it shouldn’t,” Seath said. “Once we identify those kind of novel complexes, we can use them as a handle to treat the disease only, and not impact the healthy cells. Using µMap enabled us to look very precisely at those interactomes, those ‘neighborhoods,’ in disease.”

The findings illustrate how the precision labeling approach can distinguish context-specific protein behavior, such as SLK’s role in helping healthy cells regenerate tissue—as in healing sunburned skin—versus its co-opted role driving growth in cancer cells.