Recent Publications Demonstrate the Performance of the GeoMx DSP and Establish New Standards for Spatial Profiling in Discovery & Translational Research

On May 12, 2020 NanoString Technologies, Inc. (NASDAQ:NSTG), a leading provider of life science tools for discovery and translational research, reported several recent peer-reviewed publications that utilized the company’s GeoMx Digital Spatial Profiler (DSP) to discover spatially-resolved biomarkers (Press release, NanoString Technologies, MAY 12, 2020, View Source [SID1234557617]). GeoMx DSP is an integrated system comprised of hardware, software, and reagents, capable of being read out using either the nCounter Analysis System or Next-Generation Sequencing (NGS).

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The first of these papers entitled, "Multiplex digital spatial profiling of proteins and RNA in fixed tissue," was published in the journal Nature Biotechnology (View Source). In this paper, a team of scientists from NanoString provide the most complete description to date of the GeoMx DSP’s capabilities to spatial profile proteins and RNA in formalin-fixed paraffin-embedded (FFPE) tissue.

The study describes extensive validation of the performance of each multiplexed panel using FFPE cell lines and compares performance to standard methods such as traditional immunohistochemistry (IHC) and in situ hybridization (ISH). The publication also includes case studies of the use of GeoMx DSP across a variety of tissue types and disease areas, illustrating the platform’s flexibility in selecting regions of interest (ROI) for analysis. Examples of key applications enabled by the light directed, non-destructive, ROI selection include auto-segmentation of tumor and tumor microenvironment, hypothesis-free gridding of the entire tissue samples, contour mapping across tissue substructures, and rare cell profiling. In addition, this is the first peer-reviewed publication to detail the performance achieved when GeoMx DSP is read out using NGS, including data spatially profiling 1,400+ genes using a prototype version of the Cancer Transcriptome Atlas.

"Spatial biology is emerging as a fundamental area of research in both discovery and translational science," said Joe Beechem, Chief Scientific Offer and SVP of R&D for NanoString. "Together these papers demonstrate the power and flexibility of GeoMx DSP to span the entire continuum of research — discovering new biology, identifying disease biomarkers, and potentially enabling future diagnostic tests."

Two recent publications from David Rimm and colleagues at Yale University further highlight the translational capabilities of the GeoMx DSP platform. The first publication, "Digital quantitative assessment of PD-L1 using digital spatial profiling" was published in the Nature journal Laboratory Investigation (View Source). This publication highlights the dynamic range of digital counts, high correlation to IHC and quantitative IHC, and the reproducibility of the GeoMx DSP platform. GeoMx DSP was found to generate data comparable to well established industry standard IHC assays which include the FDA approved PD-L1 assay, lab-developed test assays and quantitative immunofluorescence.

Dr. Rimm’s group second paper titled, "Biomarkers associated with beneficial PD-1 checkpoint blockade in Non-Small Cell Lung Cancer (NSCLC) identified using high-plex digital spatial profiling" was published in the journal Clinical Cancer Research. The authors used GeoMx DSP to discover twelve spatially informed biomarkers that are predictive of response to PD-1 checkpoint blockade and associated with clinical outcomes in NSCLC patients. The researchers concluded that the ability to reliably quantify multiple targets from a single tissue has the potential to make GeoMx DSP ideally suited for developing companion diagnostic assays. (View Source).

"The robust quantification and molecular compartmentalization capabilities were critical in identifying immune compartment specific biomarker candidates for predicting response to PD-1 checkpoint blockade," said David Rimm, MD, PhD, Professor of Pathology and Medicine, Yale University. "These data provide confidence for discovering novel bioclassifiers as well as developing clinical applications, from prognostic assays to companion diagnostics, using the GeoMx DSP system."