nCounter® Viral Panel Plus Menu
Helping Your Research
There are many applications in infectious disease research where viral detection is useful, such as understanding how the viral life cycle affects the host response, disease pathogenesis, the impact of antivirals and vaccines, and chronic infection. It can be difficult with RNA sequencing to detect viral transcripts in infected samples due to the overwhelming amount of host material present.
How it Works
The targeted and customizable nature of nCounter technology makes it easy to profile transcripts from the host and one or more pathogens simultaneously. Probes for pathogens can be added as a Panel Plus spike-in to an off-the-shelf human or mouse Gene Expression Panel or included in a de novo Custom CodeSet. The nCounter Viral Panel Plus Menu is a list of pre-designed Research Use Only probes for eight viruses associated with chronic disease and/or cancer. You can use the pre-designed probes as is in a Panel Plus design or mix and match probes from different viruses to create your own Panel Plus of choice. Probes were designed to cover as many sequences as possible while at the same time ensuring sensitivity, specificity, and breadth of coverage.
Probes cannot be used in a standalone assay and must be paired with an nCounter Gene Expression Panel. Check with bioinformatics about compatibility with a specific panel; however, the Viral Panel Plus Menu has been designed to be compatible with most nCounter panels. Probes are also compatible with Elements™ chemistry and PlexSet™ assays. Viral detection may differ across different sample types.
For ideal coverage of the host response to a particular virus, pair the Viral Panel Plus Menu probes with the Host Response Panel or study the effect of chronic viral infections on T cell, B cell, and NK cell function with the Immune Exhaustion Panel.
Panel Selection Tool
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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.