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AGBT: New Weill Cornell Spatial Atlas Project Aims to Discover New Cell Types

HOLLYWOOD, Fla. — Sequencing samples from astronauts has led Weill Cornell Medicine's Chris Mason to think astronomically. Now, he's trying to do the biological equivalent of discovering new planets — discovering new cell types.

In the same way that planets have been discovered by their gravitational interactions with other planets or stars, spatial omics technologies enable researchers to "see interactions for the first time to pick up new kinds of cells" or cells with altered functions that are effectively new cell types, Mason said in a Monday evening talk here at the Advances in Genome Biology and Technology annual meeting.

"What's exciting is that we can see a shift in how the cells are communicating," he said, adding that this type of analysis can "open doors to new biology" such as ligand-receptor analyses, ribosomal and other organelle biology, and cytoskeleton shifts.

Last week, Weill Cornell and NanoString Technologies announced the launch of the Spatial Atlas of Human Anatomy (SAHA) project, which will analyze samples of 30 organs from a diverse population of healthy adults to provide a map of the body at subcellular resolution.

Mason told GenomeWeb that the funding for the project totals approximately $1.5 million from several sources, as well as unspecified amounts of in-kind contributions and reagent discounts from NanoString. Sample processing has been done both in house and by NanoString. Mason's lab already has a GeoMx digital spatial profiler and is expecting to have its CosMx up and running in the next few weeks.

In the talk, Mason showed data from the first several prostate, liver, and colon samples analyzed on NanoString's spatial platforms. The project aims to start by analyzing between three and five samples per organ. "More is always better," he noted. In addition to the samples from healthy individuals, SAHA will analyze about 10 sets of tumor samples, including lung, colorectal, and hematological cancers.

As for discovering new cell types, he pointed to an example gleaned from analyzing colon samples. One from an individual with colorectal cancer turned up cells that were "so aberrant that they don't look like anything else" among the annotated normal cells, he said.

The speed at which this kind of research can be done remains a challenge, though. "The depth of data is extraordinary, but the throughput is medium," Mason noted.