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High Throughput MicroRNA Profiling: Optimized Multiplex qRT-PCR at Nanoliter Scale on the Fluidigm Dynamic ArrayTM IFCs
Published on: August 3, 2011
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Spatially resolved and multiplexed MicroRNA quantification from tissue using nanoliter well arrays
Maxwell B Nagarajan1, Augusto M Tentori1, Wen Cai Zhang2
11Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139 USA.
Microsystems & Nanoengineering
|May 19, 2020
Summary
We developed a new method for spatially resolved microRNA (miRNA) measurements in FFPE tissues. This technique can quantify tissue heterogeneities and aid in biomarker-based diagnostics for diseases like lung cancer.
Area of Science:
- Biomedical Engineering
- Molecular Biology
- Cancer Research
Background:
- Spatially resolved gene expression is crucial for medical studies and companion diagnostics.
- Current technologies for quantifying and multiplexing gene expression in tissues are limited.
- MicroRNA (miRNA) analysis in formalin-fixed, paraffin-embedded (FFPE) tissues presents unique challenges.
Purpose of the Study:
- To present a novel method for spatially resolved and multiplexed miRNA measurements.
- To enable quantification of miRNA expression directly from FFPE tissue sections.
- To demonstrate the application of this technology in a relevant cancer model.
Main Methods:
- Utilized nanoliter well arrays to pixelate FFPE tissue sections.
- Employed photopatterned hydrogels for quantitative miRNA detection.
- Applied the method to a genetically engineered mouse model for non-small cell lung cancer (K-rasLSL-G12D/+; p53fl/fl).
Main Results:
- Successfully performed spatially resolved and multiplexed miRNA measurements from FFPE tissue.
- Identified differentially expressed miRNAs within tumors of the mouse model.
- Demonstrated the ability to quantify miRNA heterogeneities within the tissue sample.
Conclusions:
- The developed technology allows for precise, spatially resolved miRNA quantification in FFPE tissues.
- This method can reveal tissue heterogeneities important for understanding disease.
- The technology holds potential for developing informed, biomarker-based diagnostics.
