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nCounter® Gene Fusion Panels and CNV Assays
Prosigna Score / ROR Score:
The ROR Score has been validated to predict the risk of recurrence of disease in ER+ breast cancer after surgery and treatment with 5 years of endocrine therapy. The ROR score depends upon the biology of the intrinsic subtypes, the proliferation score of the tumor, and the tumor size as shown in the equation below:
ROR = aRLumA + bRLumB + cRHer2 + dRBasal + eP + fT
Each of the R variables in the equation above indicate the Pearson correlation coefficient of the PAM50 expression profile for the tumor compared to each of the prototypical centroids for the intrinsic subtypes shown in the heatmap below. P is the proliferation score, which is the average gene expression profile of genes associated with cell-cycle progression and T is the tumor stage.
Figure: Heatmap of PAM50 genes by subtype. Red is higher expression and green is lower expression
Increasing numbers of actionable fusions have made traditional technologies such as PCR and FISH inefficient and costly. NGS can profile multiple fusions in a single assay but is slow, complex, and expensive. Combined with direct digital counting on the nCounter System and Junction Sequence probe design, the detection of fusion genes is highly sensitive, quantitative, and easy:
Directly detect hundreds of fusions in one assay
Gets results in less than 24 hrs with just 15 minutes of hands-on time
Use challenging sample types including FFPE tissue sections
Multiplex at the price of single-plex assays
Aberrations in copy number are implicated in many diseases, from genetic disorders to cancer. FISH has traditionally been used to detect CNVs, but the growing number and importance of CNVs has made higher-plex technologies such as microarrays and NGS more attractive. However, these approaches require cumbersome and time-consuming workflows and a significant amount of expertise. Additionally, most microarrays are not able to resolve CNVs from FFPE samples.
GeoMx DSP COVID-19 Protein and RNA Analysis
Rapidly perform high-plex spatial analyses of the host response in FFPE or fresh frozen tissue using the GeoMx Digital Spatial Profiler (DSP). NanoString’s GeoMx DSP platform enables high-plex protein and RNA experiments in key areas of biology such as molecular response, cellular (immune) response, tissue damage, and drivers of individual susceptibility to severe forms of disease.
The GeoMx COVID-19 Immune Response Atlas, a ~1,850-plex RNA assay, enables spatial studies of the SARS-CoV-2 virus and host response. RNA targets include COVID-19 receptors and proteases, pulmonary alveolar type I and II markers, lung biology markers, viral response markers, and SARS-CoV-2 probes. RNA targets are profiled simultaneously using the GeoMx DSP and an Illumina next-generation sequencer (NGS) for readout. Users can run ACD RNAscope™ probes alongside GeoMx RNA probes to identify regions of interest.
A five-antibody custom, ready-to-go protein panel, with receptor, protease, and viral markers is available through the GeoMx Technology Access Program or for order through Abcam. This COVID-19 GeoMx-formatted Antibody is run with the 20-plex GeoMx Immune Cell Profiling Core (plus controls) with readout on the nCounter Analysis System. Users can add up to six 10-plex modules including the Immune Activation Status, Immune Cell Typing, and/or Cell Death modules to more deeply profile proteins involved in T cell activation and cell death. NanoString scientists can recommend commercially-available markers for lung epithelium, nasal epithelium, immune response markers, and the viral spike protein.
NanoString’s nCounter technology makes it easy to directly quantify CNVs from up to 800 loci with
Robust performance on FFPE
A simple assay that doesn’t require expertise
Minimal hands-on time and fast time-to-results
Lower cost than FFPE microarray assays or NGS
Additionally, the nCounter v2 Cancer Copy Number Assay offers an off-the-shelf option for multiplexed quantification of 87 genes commonly amplified or deleted in cancer including PIK3CA, AKT, PTEN, BRCA, ERBB2, and MYC.
Optimized for FFPE samples
Copy number analysis of 87 genes commonly amplified or deleted in cancer
Digital quantitation of highly amplified genes
Specific detection of bi-allelic and multi-allelic number of copies
You can choose from several options to meet your lab’s fusion detection needs
Use our Vantage 3D Lung Gene Fusion or our Vantage 3D Leukemia Gene Fusion
Make your own custom fusion assay using a Custom codeset or Element Reagents
nCounter CNV Assays: direct and robust CNV detection with a simple workflow
The eight essential components of stem cell biology
Stem Cell Renewal:
Stem Cell Prolifiration
PSC Pluripotency Markers and Regulators
Naive State/Primed State
Histone Acetylation & Methylation
Oxidative Stress Response
Amino Acid Metabolism
Fatty Acid Metabolism
Differentiation Signaling and Pathways:
HOX Gene Activation
Endodermal /Ectodermal /Mesodermal Lineage Markers
Key Somatic Cell Types
Custom & Clinical Products
Daily Sample Throughput
Self-assembled, interchangeable probes, optimized for smaller validation projects with maximum flexibility
Self-assembled, interchangeable probes for high-throughput, sample multiplexing projects
User-designed, turn-key solution that comes ready-to-use
mRNA, CNV, Fusions
mRNA, miRNA, CNV, Fusions
Cell line drug screen, biomarker development, infectious disease
Gene Signature Development
Model Organism, Microbes, Agriculture
nCounter Vantage 3D Lung Gene Fusion Panel: Includes 63 probes: 35 for specific fusion detection, 24 for positional gene expression imbalance detection, and 4 internal reference genes. Master Kit reagents sold separately.
nCounter Vantage 3D Leukemia Gene Fusion Panel: Includes 42 probes: 27 for specific fusion detection, 12 leukemia biomarkers, and 3 internal reference genes. Master Kit reagents sold separately.
nCounter v2 Cancer CN Assay: Enables copy number quantification for 87 genes commonly amplified or deleted in cancer. Optimized for FFPE analysis. Master Kits sold separately.
Please contact us for more info at email@example.com