Weill Cornell Medicine and NanoString Collaborate to Create Comprehensive Spatial Atlas of Human Anatomy - Seite 2

“The SAHA data set, obtained at multiple spatial scales, analyte classes, and plex-levels, represents the largest data set of its kind ever collected,” said Joseph Beechem, SVP & CSO of NanoString. “This atlas will transform our understanding of how healthy tissues are organized and function and provide the foundation of understanding required to both treat and diagnose disease states.”

Variability is an important aspect of biological research. The samples, selected to advance medical research, will capture variability across sexes and ancestries (European, African, Latin American, East Asian, and South Asian). All results will be made available to the scientific community through the SAHA data portal, including raw and processed data.

SAHA is a collaborative effort with Weill Cornell Medicine’s Department of Pathology and Laboratory Medicine, Englander Institute for Precision Medicine, and the WorldQuant Initiative for Quantitative Prediction. It will be led by Drs. Chris Mason, Robert E. Schwartz, and Shauna L. Houlihan, and executed in two phases over the next three years. The research will investigate how NanoString’s spatial platforms can synergize for unprecedented biological insights.

Dr. Mason serves on the Scientific Advisory Board and is a paid consultant to NanoString

About NanoString Technologies, Inc.

NanoString Technologies, a leader in spatial biology, offers an ecosystem of innovative discovery and translational research solutions, empowering our customers to map the universe of biology. The GeoMx Digital Spatial Profiler, cited in more than 190 peer-reviewed publications, is a flexible and consistent solution combining the power of whole tissue imaging with gene expression and protein data for spatial whole transcriptomics and proteomics from one FFPE slide. The CosMx Spatial Molecular Imager (SMI) is an FFPE-compatible, single-cell imaging platform powered by spatial multiomics enabling researchers to map single cells in their native environments to extract deep biological insights and novel discoveries from one experiment. The AtoMx Spatial Informatics Platform (SIP) is a cloud-based informatics solution with advanced analytics and global collaboration capabilities, enabling powerful spatial biology insights anytime, anywhere. The foundation of our research tools is our nCounter Analysis System, cited in more than 6,500 peer-reviewed publications, which offers a secure way to easily profile the expression of hundreds of genes, proteins, miRNAs, or copy number variations, simultaneously with high sensitivity and precision.