Cancer Center at Illinois (CCIL) member Hee-Sun Han has developed an Intracellular Spatial Transcriptomic Analysis Toolkit (InSTAnT) that allows researchers to look at subcellular patterns. The research findings are published in Nature Communications. After intensive collaboration with CCIL member Dave Zhao and Saurabh Sinha from Georgia Tech, the team accomplished something innovative with import for cancer visualization.
Left to right: Cancer Center at Illinois (CCIL) members Dave Zhao and Hee-Sun Han, and Saurabh Sinha from Georgia Tech University
With the help of a CCIL Seed Grant, the team was able to kick start their research which has grown to be a very successful project. “The CCIL played a big part in helping us explore this direction by funding the groundwork for this research,” said Han.
Their research is in spatial transcriptomics, with a focus on generating a spatially resolved molecular map. This defines molecular interaction in a completely new perspective, purely based on spatial distribution of molecules. “We’re trying to find where thousands of different molecules are located within tissues. We developed a single molecule resolution technology and worked on the concept of looking at the spatial pattern of molecules,” said Han.
Looking at subcellular patterns is something that had never been done before, and InSTAnT provides cancer researchers with information on cellular patterns and what can be found from their results. So far, the patterns Han’s team has found are surprisingly non-random.
InSTAnT has the capability to create these maps at a very high resolution, making for clear visualization of molecules. “Once we know the position of every single molecule, then we can infer which molecules interact. If two molecules keep showing up very close by or co-localized, then it is likely because they are interacting,” said Han.
To explain this in layman terms, Sinha said, “Imagine you have a lot of trees in a big area, and you want to know which species of trees tend to grow near each other. How do you find that? That’s what we were doing with mRNAs and their genes, instead of trees and their species.”
The team’s research is useful in studying cancer, something very complicated since cancer arises from many small, moving pieces. InSTAnT makes it possible for scientists to visualize all these molecules and figure out how to understand them. “Basically, what we’re doing is making molecular Google Maps of cancer tissue. Then after making them, we can start piecing them together and interpreting them,” said Han.
There will be two main beneficiaries to their research, as Zhao explains, “The cancer biologist will be able to discover new patterns that may uncover new information about how cancer develops and works. The data scientist can look at the way we analyze these data and further develop ideas along these lines.” Their next steps will be to think about how to connect this research back to patients, putting their work to practical use potentially with drug development.
The team agreed that the most innovative part of their project was the idea itself and their rigorous approach. Their research did not follow one specific hypothesis; infinite hypotheses can now be formed based on their new data. This work generates new questions that can be followed up on and studied in depth. After years of meetings and hard work, InSTAnT now opens a new world for scientific exploration, making research that was previously impossible a possibility.
“It has been great to have these collaborators. I feel like we’re scientific brothers and sisters. We complement each other, we get ideas, and we brainstorm. It’s been one of the most fun experiences for me in academia, finding people with whom I can resonate and work,” said Han.
“In the words of our favorite famous movie, it’s a ‘whole new world, shining, shimmering, splendid’–and unexplored. Let’s now make sense of it,” concluded Zhao.
Editor’s notes:
Hee-Sun Han is an Assistant Professor of Chemistry. Han is also an affiliate of the Carl R. Woese Institute for Genomic Biology, the Center for Biophysics and Quantitative Biology, the Neuroscience Program, and Bioengineering. Han can be reached at hshan@illinois.edu.
InSTAnT is reported in the paper “Intracellular spatial transcriptomic analysis toolkit (InSTAnT)” and is available online.
doi.org/10.1038/s41467-024-49457-w
This story was written by Florence Lin, CCIL Communications Intern.