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.



Offers several advantages over Flow Cytometry including the use of frozen and FFPE tissue, higher throughput and less assay time.


Mouse panel is specifically designed for immunotherapy efficacy studies using syngeneic mouse tumor models.


Aids in the identification of responder/non-responder populations in immunotherapy research; analyze therapy strategies to determine whether or not they have an effect on Tumor Infiltrating Lymphocytes.


47 biological signatures measuring immune cell populations and key tumor and immune activities.

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.

PanCancer IO 360 Pathways and Processes
Category/pathwayHuman genesMouse genes
Tumor Foreignness
Release of Cancer Cell Antigens7469
Cell Cycling and Proliferation5453
Tumor Intrinsic Factors156149
Common Signaling Pathways172162
Immune Access to Tumor
Extracellular Matrix Remodeling4341
Killing of Cancer Cells
Myeloid Cell Activity
NK Cell Activity
Cytolytic Immune Activity
Cancer Antigen Presentation
T cell Priming and Activation
Immune Cell Localization to Tumors
Recognition of Cancer Cells by T cells


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.


PanCancer IO 360 Biological Signatures
Tumor ImmunogenicityTumor Sensitivity to Immune AttackInhibitory Immune MechanismsStromal FactorsInhibitory MetabolismAnti-tumor Immune ActivityInhibitory Immune SignalingImmune Cell Population Abundance
Antigen Processing MachineryApoptosisIDO1 Gene ExpressionEndothelial CellsGlycolysisTumor Inflammation Signature (TIS)CTLA4 Gene ExpressionB CellsNK CD56dim Cells
Antigen Presenting Machinery Expression LossTumor ProliferationPD-L1 Gene ExpressionStromal Tissue AbundanceHypoxiaCytotoxicityIL10 Gene ExpressionCD45+ CellsNatural Killer Cell Abundance
ImmunoproteasomeJAK-STAT Pathway Gene Expression LossB7-H3 Gene ExpressionInterferon Gamma SignalingInflammatory ChemokinesCD8 T CellT Cells Abundance
MAGE Genes ExpressionTGF-Beta Gene ExpressionInterferon Signaling ResponseMyeloid-Derived Inflammatory SignalingCytotoxic CellsTH1 Cell (TBX21/T-bet) Expression
Loss of Mismatch Repair Gene ExpressionLymphoid Compartment ActivityPD-1 Gene ExpressionDendritic CellsTreg (FOXP3 Expression)
MHC Class II Antigen PresentationPD-L2 Gene ExpressionExhausted CD8 Cell
Myeloid Compartment ActivityTIGIT Gene ExpressionMacrophage
ARG1 Gene ExpressionMast Cells
NOS2 Gene ExpressionNeutrophils

Genes in panel

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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).