nCounter® Myeloid Innate Immunity Panel
Helping Your Research
The nCounter® Myeloid Innate Immunity Panel provides comprehensive coverage of myeloid-derived cells in a targeted gene expression assay. These panels can be used with multiple sample types like peripheral blood mononuclear cells (PBMCs) or formalin-fixed paraffin-embedded (FFPE) tissue sections and provide results in less than 24 hours with minimal hands-on time and data analysis.
The Myeloid Innate Immunity Panel is designed to encompass all aspects of the innate immune response of myeloid-derived cells and can be used for basic and translational research in immuno-oncology, autoimmunity, and infectious disease. The panel is curated to include the most current and relevant genes and is available in both human and mouse versions. Use the Myeloid Innate Immunity Panel to study:
- Mechanisms of immune evasion
- Damage response, wound healing & tissue repair
- Immune regulation
- Disease pathogenesis
- Treatment response vs. non-response
How It Works
The nCounter Myeloid Innate Immunity Panels were developed in collaboration with leading experts in the field of immuno-oncology but can be used to study the role of myeloid-derived cells whenever the innate immune system is implicated in the response to a disease or pathogen. Each panel enables characterization of the innate immune response by profiling genes involved in the recruitment and activation of selected myeloid subtypes.
770 genes In 19 different pathways and processes across 7 different myeloid cell types
Rapidly analyze Complex immune responses with publication-quality results next day
Optimized for difficult sample types including FFPE, PBMCs, or FACS sorted cells
Genes represent all major myeloid cell types including neutrophils, eosinophils, mast cells, dendritic cells, monocytes, and macrophages with 19 functional and pathway annotations
Customize with Panel Plus to spike-in up to 55 genes of your choice to tailor the panel for your research project
Panel Selection Tool
Find the gene expression panel for your research with easy to use panel proFind Your Panel
Immunostimulatory cancer-associated fibroblast subpopulations can predict immunotherapy response in head and neck cancer.
Purpose: Cancer-associated fibroblasts (CAF) have been implicated as potential mediators of checkpoint immunotherapy response. However, the extensive heterogeneity of these cells has precluded rigorous understanding of their immunoregulatory role in the tumor microenvironment.
Spatial profiling reveals association between WNT pathway activation and T-cell exclusion in acquired resistance of synovial sarcoma to NY-ESO-1 transgenic T-cell therapy.
Background: Genetically engineered T-cell immunotherapies for adoptive cell transfer (ACT) have emerged as a promising form of cancer treatment, but many of these patients develop recurrent disease. Furthermore, delineating mechanisms of resistance may be challenging since the analysis of bulk tumor profiling can be complicated by spatial heterogeneity.
A Novel Artificial Intelligence–Powered Method for Prediction of Early Recurrence of Prostate Cancer After Prostatectomy and Cancer Drivers.
To develop a novel artificial intelligence (AI)–powered method for the prediction of prostate cancer (PCa) early recurrence and identification of driver regions in PCa of all Gleason Grade Group (GGG). MATERIALS AND METHODS: Deep convolutional neural networks were used to develop the AI model.