Coming Soon! QuantiGene ViewRNA RX Automated Assays
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QuantiGene ViewRNA ISH Tissue Assay—Unique Benefits
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QuantiGene ViewRNA ISH Tissue Assay—Applications
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RNA In Situ Hybridization in FFPE and Fresh Frozen Tissues—Overview
QuantiGene ViewRNA ISH Tissue Assay is a unique in situ hybridization assay that has the robustness and sensitivity to detect single RNA molecules in individual cells without the challenges of antibody-based protein assays or the traditional RNA expression quantitation assays. The assays allow for RNA localization within the cellular context - tumor micro-environment and intra-tumor heterogeneity – that can provide vital information to biomarker's clinical relevance. Two RNA targets can be visualized in the same tissue section.The assay uses proprietary chemistry for the target specific probe sets and bDNA signal amplification (bDNA) for detection of specific signal, and has four main steps: sample preparation, target hybridization, signal amplification, and detection. Bach automation of the steps can be achieved using the Little Dipper® Processor for Affymetrix which will reduce hands-on time and assay variability.
Assay Performance Highlights
QuantiGene® ViewRNA ISH Tissue Assay |
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| Sample Type | FFPE or fresh frozen tissue sectionsa, fine needle aspiratesb |
| Species | Any |
| Sensitivity | Single RNA copy/cell |
| Plex Level | 2-plex |
| Assay Format | Standard microscope slides |
| Detection | Chromogenic and fluorescent |
| Automation-compatible | Yesc |
| Instrumentation | Brightfield or fluorescence microscope |
a Fresh frozen tissue sections could be used, please refer to the Using Frozen Tissues with the QuantiGene ViewRNA ISH Tissue Assay Technical Note.
b Fine needle aspirates (Ting D. T., et al. Aberrant overexpression of satellite repeats in pancreatic and other epithelial cancers. Science 331(6017):593-6 (2011).)
c Powerful automation solution on Leica BOND RX - Coming Soon. Batch automation of the assay procedures, reducing hands on time and assay variability across users, can be achieved using the Little Dipper® Processor from SciGene.




