nCounter®
Tumor Signaling 360™ Panel
Helping Your Research
As therapeutics that target tumor signaling evolve, a greater understanding of tumor signaling is required as well as a better understanding of the interactions of tumor cells with the tissue milieu. The Tumor Signaling 360 Panel is intended to play this exact role, enabling deeper profiling of the tumor that is complete, yet focused on signaling pathways of interest for targeted therapeutic development. Covering hundreds of genes involved in tumorigenesis, metastasis, and inflammation, the nCounter Tumor Signaling 360 Panel offers a holistic view of the biology of the tumor, microenvironment, and immune response with an emphasis on dysfunctional cell signaling in cancer.
- Profile 40+ pathways involved in tumor biology, immune evasion, and remodeling of the microenvironment.
- Identify targets for novel therapeutics
- Understand the mechanism of action of targeted therapies
- Determine the extent of anti-tumor immune response with the Tumor Inflammation Signature
- Quantify the presence and relative abundance of 14 different immune cell types
Inspired by systems biology approaches to cancer research, NanoString’s 360 Series Panel Collection gives you a 360° view of gene expression by combining carefully-curated content involved in the biology of the tumor, microenvironment, and the immune response into a single holistic assay. Each panel contains the 18-gene Tumor Inflammation Signature (TIS) that measures a peripherally-suppressed, adaptive immune response and has been shown to correlate with response to checkpoint inhibitors.
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Product Information
The Tumor Inflammation Signature includes 18 functional genes known to be associated with response to PD-1/PD-L1 inhibitors.
Includes four areas of Immune Biology: IFN-ү-responsive genes related to antigen presentation, chemokine expression, cytotoxic activity, and adaptive immune resistance genes.
The tumor inflammation gene expression signature highlights the complex biology of the host immune microenvironment.
View publication and video.
- Ayers, Mark, et al. “IFN-y-related mRNA profile predicts clinical response to PD-1 blockade.” The Journal of Clinical Investigation 127.8 (2017).
Platform Specifications (*Does not apply to Prosigna® Breast Cancer Prognostic Gene Signature Assay (1))
360 Series Product Comparison
Fully-annotated gene lists in Excel format are available for each of the 360 Panels. The table below compares the biology coverage of the 360 Panels across the tumor, microenvironment, and the immune response to that of the PanCancer Panels Collection.
Related Resources
Publications
Midkine expression by stem-like tumor cells drives persistence to mTOR inhibition and an immune-suppressive microenvironment.
mTORC1 is hyperactive in multiple cancer types1,2. Here, we performed integrative analysis of single cell transcriptomic profiling, paired T cell receptor (TCR) sequencing, and spatial transcriptomic profiling on Tuberous Sclerosis Complex (TSC) associated tumors with mTORC1 hyperactivity, and identified a stem-like tumor cell state (SLS) linked to T cell dysfunction via tumor-modulated immunosuppressive macrophages.
Spatially resolved proteomic profiling identifies tumor cell CD44 as a biomarker associated with sensitivity to PD-1 axis blockade in advanced non-small-cell lung cancer.
Background: Most patients with advanced non-small-cell lung cancer (NSCLC) fail to derive significant benefit from programmed cell death protein-1 (PD-1) axis blockade, and new biomarkers of response are needed. In this study, we aimed to discover and validate spatially resolved protein markers associated with sensitivity to PD-1 axis inhibition in NSCLC.
Integrated multi-omics reveals cellular and molecular interactions governing the invasive niche of basal cell carcinoma.
Tumors invade the surrounding tissues to progress, but the heterogeneity of cell types at the tumor-stroma interface and the complexity of their potential interactions hampered mechanistic insight required for efficient therapeutic targeting. Here, combining single-cell and spatial transcriptomics on human basal cell carcinomas, we define the cellular contributors of tumor progression.
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