Facilitating rapid discovery and development of potentially predictive signatures with the most advanced view of immuno-oncology biology.
The PanCancer IO 360 Gene Expression Panel is a unique 770 gene expression panel for research use only (RUO) that 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 interrogation of mechanisms of immune evasion.
Developed specifically for translational research, this powerful new panel incorporates 15+ potentially predictive Research Use Only (RUO) biological signatures including the 18-gene Tumor Inflammation Signature as recently described in JCI.1
- Translational RUO panel for the research of possible predictive signatures for potential immunotherapy companion diagnostics
- Allows for possible identification of responder/non-responder populations for immunotherapy research
- Characterize disease biology
- Interrogate mechanisms of immune evasion
Download Gene List:
|Tumor Foreignness||Tumor Fitness||Tumor Immune Evasion||Immune Access to Tumor||Inhibitory Metabolism||Cytolytic Immune Activity||Suppressive Immunity||Immune Cell Population Abundance|
|Antigen processing machinery||Apoptosis||PDL1 gene expression||Stroma abundance||Glycolytic activity||Tumor Inflammation Signature||Myeloid-derived Inflammatory signaling||B-cells||Mast Cells|
|Proteasome||Proliferation - Tumor proliferation||IDO1 gene expression||Endothelial cells||Hypoxia||Cytotoxicity||Inflammatory chemokines||CD45||Neutrophils|
|MAGE family gene expression||Loss of JAK-STAT pathway gene expression||Interferon gamma||ARG1 gene expression||CD8 T cells||NK CD56dim cells|
|Loss of antigen processing and presentation gene expression||Interferon downstream signaling||NOS2 gene expression||Cytotoxic cells||NK cells|
|Loss of mismatch repair gene expression||Lymphoid compartment activity||CTLA4 gene expression||DC||T-cells|
|Myeloid compartment activity||IL10 gene expression||Exhausted CD8||Th1 cells (T-bet expression)|
|HLA class 2 antigen presentation||PDL2 gene expression||Macrophages||Treg (FOXP3 expression)|
Possible predictive signatures measuring IO biology trained through combination of domain knowledge, academic collaborations and mining of public and proprietary data.
13 Biological Pathways and Processes
|Category/Gene Number||Category/Gene Number||Category/Gene Number|
|Release of Cancer Cell Antigens||74||Angiogenesis||40||Cancer Antigen Presentation||95|
|Cell Cycling and Proliferation||54||Extracellular Matrix Remodelling||43||T cell priming and Activation||151|
|Tumor Intrinsic Factors||156||Collagens||6||Immune Cells Localization to Tumors||293|
|Common Signaling Pathways||172||Metastasis||20||Recognition of Cancer Cells by T cells||103|
|Killing of Cancers Cells||177|
|Myeloid Cell Activity||262|
|NK Cell Activity||28|
20 internal reference genes include overlapping genes from Hallmarks of Cancer PanCancer Collection for cross-panel comparisons.
Tumor Inflammation Signature1
The Tumor Inflammation Signature includes 18 functional genes known to be associated with response to PD-1/PD-L1 inhibitors pathway blockade.
Includes 4 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.
|18-gene Tumor Inflammation Signature|
1. Ayers, Mark, et al. "IFN-y-related mRNA profile predicts clinical response to PD-1 blockade." The Journal of Clinical Investigation 127.8 (2017).
Ayers, Mark, et al. "IFN-γ–related mRNA profile predicts clinical response to PD-1 blockade." The Journal of Clinical Investigation 127.8 (2017).
Danaher, Patrick, et al. "Gene expression markers of Tumor Infiltrating Leukocytes." Journal for immunotherapy of cancer 5.1 (2017): 18.
Satoh, Jun-ichi, and Hiroko Tabunoki. "A comprehensive profile of ChIP-Seq-based STAT1 target genes suggests the complexity of STAT1-mediated gene regulatory mechanisms." Gene regulation and systems biology 7 (2013): 41.
Becht, Etienne, et al. "Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression." Genome biology 17.1 (2016): 218.
Spranger, Stefani, Riyue Bao, and Thomas F. Gajewski. "Melanoma-intrinsic [beta]-catenin signalling prevents anti-tumour immunity." Nature 523.7559 (2015): 231.
Harris, B. H. L., et al. "Gene expression signatures as biomarkers of tumour hypoxia." Clinical Oncology 27.10 (2015): 547-560.
Manson, G., et al. "Biomarkers associated with checkpoint inhibitors." Annals of Oncology 27.7 (2016): 1199-1206.
Blank, Christian U., et al. "The “cancer immunogram”." Science 352.6286 (2016): 658-660.
For Research Use Only. Not for use in diagnostic procedures.