By Jerry Grillo

As Ahmet F. Coskun and his team of researchers continue their mission to create a 3D atlas of the human body, mapping cells and tissues, they’re making discoveries that could lead to better treatments for the most common type of lung cancer.

While they’re at it, they’re pioneering new fields of research, and possibly spinning the work into a new commercial venture.

Last year, Coskun and his team introduced a new study in “single cell spatial metabolomics,” which explores the distribution of small molecules — metabolites — within tissues and organs. Now they’re spearheading “spatial interactomics,” a research area concerned with interactions between various biomolecules inside of individual cells. 

To study these interactions, they’ve developed an innovative technique, or tool, to better understand why non-small cell lung cancer, or NSCLC, resists treatment in so many patients. They call it the “intelligent sequential proximity ligation assay,” or iseqPLA.

“It’s a smart test that can look at proteins and how they interact with each other in space,” said Coskun, Bernie Marcus Early Career Professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University.

“Basically, we’re the first to create a new research area on spatial protein-protein interactions, which can tell us more about cell types and their functions,” said Coskun. “With spatial interactomics, we can validate how cells physically touch, sense, and regulate nearby cells through the interaction of pairs of proteins.”

So, the immediate goal of spatial interactomics is to investigate how protein-protein interactions drive drug resistance in NSCLC. And iseqPLA allows researchers to visualize how it’s all happening at the subcellular level. Coskun’s team described its work recently in the journal Nature Biomedical Engineering. He’s also forming a company to commercialize the technology.

Smarter Tools

Drugs called tyrosine kinase inhibitors (TKIs, like Osimertinib) have been successful in treating people with NSCLC. But many patients who initially respond well to the regimen, eventually develop a resistance. Protein interactions, a molecular kind of crosstalk, are a prime suspect in causing this resistance. 

Proteins interact with each other all the time, and this mingling controls how cells grow, divide, or survive. Coskun and his team want to see how these interactions change in response to cancer treatment, and iseqPLA shows them, essentially attaching glowing tags to proteins, lighting up their locations and interactions under a microscope.

“We believe it will be a groundbreaking tool,” he said.

With that in mind, Coskun is planning to form a startup company called SpatAllize. He’s working with VentureLab, the nonprofit organization at Georgia Tech that provides entrepreneurship programs for students and faculty.

“We are currently performing customer interviews and forming a strategy for a viable plan towards the marketplace,” he said.

He also plans to expand iseqPLA’s utility into other areas of research, focusing on how protein interactions influence the immune system, the heart, and brain health. His team is also developing a spatial interactomics robot that integrates iseqPLA with advanced imaging and automated deep learning.

“This will allow us to map all molecules within cells and tissues for an even better understanding of drug-cell interactions, particularly in cancer treatment planning,” Coskun said.

CITATION: Shuangyi Cai, Thomas Hu, Abhijeet Venkataraman, Felix G. Rivera Moctezuma, Efe Ozturk, Nicholas Zhang, Mingshuang Wang, Tatenda Zvidzai, Sandip Das, Adithya Pillai, Frank Schneider, Suresh S. Ramalingam, YouTake Oh, Shi-Yong Sun, and Ahmet F. Coskun. “Spatially resolved subcellular protein–protein interactomics in drug-perturbed lung-cancer cultures and tissues.” Nature Biomedical Engineering.     https://doi.org/10.1038/s41551-024-01271-x

FUNDING: This research was supported by the National Institutes of Health, grant Nos. P50CA217691, P30CA138292, and R33CA291197; and the National Science Foundation, grant No. R35GM151028. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of any funding agency.

COMPETING INTERESTS: Coskun, Cai, and Hu declare a patent application related to the spatial-signaling interactomics assay (U.S. Provisional 63/399,427 and U.S. Application No. 18/452,178).