All the cells in your body work together and each can have a different role. Their individual function not only depends on cell type, but can also depend on their specific location and surroundings.

A CIRM supported and collaborative study at the Gladstone Institutes, UC San Francisco (UCSF), and UC Berkeley has developed a more efficient method than ever before to simultaneously map the specialized diversity and spatial location of individual cells within a tissue or a tumor.

The technique is named XYZeq and involves segmenting a tissue into microscopic regions. Within each of these microscopic grids, each cell’s genetic information is analyzed in order to better understand how each particular cell functions relative to its spacial location.

For this study, the team obtained tissue from mice with liver and spleen tumors. A slice of tissue was then placed on a slide that divides the tissue into hundreds of “microwells” the size of a grain of salt. Each cell in the tissue gets tagged with a unique “molecular barcode” that represents the microwell it’s contained in, much like a zip code. The cells are then mixed up and assigned a second barcode to ensure that each cell within a given square can be individually identified, similar to a street address within a zip code. Finally, the genetic information in the form of RNA from each cell is analyzed. Once the results are obtained, both barcodes tell the researchers exactly where in the tissue it came from.

The team found that some cell types located near the liver tumor were not evenly spaced out. They also found immune cells and specific types of stem cells clustered in certain regions of the tumor. Additionally, certain stem cells had different levels of some RNA molecules depending on how far they resided from the tumor.

The researchers aren’t entirely sure what this pattern means, but they believe that it’s possible that signals generated by or near the tumor affect what nearby cells do.

In a press release, Alex Marson, M.D., Ph.D., a senior author of the study, elaborates on what the XYZeq technology could mean for disease modeling.

“I think we’re actually taking a step toward this being the way tissues are analyzed to diagnose, characterize, or study disease; this is the pathology of the future.”

The full results of the study were published in Science Advances.