PanCancer IO 360 Panel
Human and Mouse
Canopy’s Immuno-Oncology service allows researchers that were once limited by sample type and low throughput technology to conduct high throughput robust analysis with a wide variety of sample types including FFPE tissue. The PanCancer IO 360 panel combines vital components involved in the complex interplay between the tumor, microenvironment and immune response in cancer allowing for a multifaceted characterization of disease biology and the interrogation of immune evasion mechanisms. This panel incorporates 47 predictive biological signatures across 770 genes and 16 key immuno-oncology pathways and processes.
Benefits
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Details & data
Immunology Panel Overview
Currently, evaluating immunotherapy responders from non-responders requires flow cytometry to analyze tumor immune infiltrate. However, flow cytometry requires cells from fresh tissue, only a single sample can be sorted at a time, and the sorting process is slow. NanoString has created the PanCancer IO 360 panel to separate check point inhibitor responders from non-responders. There are several advantages of this panel over flow cytometry: 1) fresh tissue is not required, 2) you can conduct analysis on 12 samples at a time, 3) the analysis is fast, and 4) you receive a Tumor Infiltrating Lymphocyte (TIL) abundance score for each sample, making it easy to determine if your treatment had an effect on Tumor Infiltrating Lymphocytes (TILs).
Being able to reliably identify and assess TIL populations is critical in assessing immunotherapy efficacy. The PanCancer IO 360 panel allows you to measure the abundance of immune cell populations within the tumor microenvironment. Tumor models that possess a competent immune system, such as syngeneic models have shown to be a reliable tool in understanding the relationship between the complex interplay between the tumor and host immunity. The mouse PanCancer IO 360 panel is a novel tool engineered specifically for assessing immunotherapy efficacy in syngeneic mouse tumor models.
Category/pathway | Human genes | Mouse genes | |
---|---|---|---|
Tumor Foreignness | Release of Cancer Cell Antigens | 74 | 69 |
Cell Cycling and Proliferation | 54 | 53 | |
Tumor Intrinsic Factors | 156 | 149 | |
Common Signaling Pathways | 172 | 162 | |
Immune Access to Tumor | Angiogenesis | 40 | 41 |
Extracellular Matrix Remodeling | 43 | 41 | |
Collagens | 6 | 6 | |
Metastasis | 20 | 20 | |
Killing of Cancer Cells | 177 | 283 | |
Myeloid Cell Activity | 262 | 258 | |
NK Cell Activity | 28 | 27 | |
Immunometabolisom | 99 | 101 | |
Cytolytic Immune Activity | Cancer Antigen Presentation | 95 | 95 |
T cell Priming and Activation | 151 | 152 | |
Immune Cell Localization to Tumors | 293 | 291 | |
Recognition of Cancer Cells by T cells | 103 | 104 |
PanCancer IO 360 Biological Signatures
Content included in the IO 360 panel allows for calculation of 47 gene signatures measuring biological variables crucial to the tumor-immune interaction. Both analytically validated and research signatures are enriched with potentially predictive genes encompassing seven different biological functions measuring antigen availability, structural barriers to immune infiltration, inhibitory signaling, inhibitory metabolism, pro-immune signaling, killing of tumor cells, tumor receptiveness to immune signaling, tumor proliferation and apoptosis.
Tumor Immunogenicity | Tumor Sensitivity to Immune Attack | Inhibitory Immune Mechanisms | Stromal Factors | Inhibitory Metabolism | Anti-tumor Immune Activity | Inhibitory Immune Signaling | Immune Cell Population Abundance | |
---|---|---|---|---|---|---|---|---|
Antigen Processing Machinery | Apoptosis | IDO1 Gene Expression | Endothelial Cells | Glycolysis | Tumor Inflammation Signature (TIS) | CTLA4 Gene Expression | B Cells | NK CD56dim Cells |
Antigen Presenting Machinery Expression Loss | Tumor Proliferation | PD-L1 Gene Expression | Stromal Tissue Abundance | Hypoxia | Cytotoxicity | IL10 Gene Expression | CD45+ Cells | Natural Killer Cell Abundance |
Immunoproteasome | JAK-STAT Pathway Gene Expression Loss | B7-H3 Gene Expression | Interferon Gamma Signaling | Inflammatory Chemokines | CD8 T Cell | T Cells Abundance | ||
MAGE Genes Expression | TGF-Beta Gene Expression | Interferon Signaling Response | Myeloid-Derived Inflammatory Signaling | Cytotoxic Cells | TH1 Cell (TBX21/T-bet) Expression | |||
Loss of Mismatch Repair Gene Expression | Lymphoid Compartment Activity | PD-1 Gene Expression | Dendritic Cells | Treg (FOXP3 Expression) | ||||
MHC Class II Antigen Presentation | PD-L2 Gene Expression | Exhausted CD8 Cell | ||||||
Myeloid Compartment Activity | TIGIT Gene Expression | Macrophage | ||||||
ARG1 Gene Expression | Mast Cells | |||||||
NOS2 Gene Expression | Neutrophils |
Genes in panel
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References
Published use of this panel
Ayers, Mark, et al. “IFN-y-related mRNA profile predicts clinical response to PD-1 blockade.” The Journal of Clinical Investigation 127.8 (2017).