Abstract 2441: NanoString 3D Biology™ technology: simultaneous digital counting of DNA, RNA and protein
Authors: Lausted Chris , Zhou Yong , Lee Jinho , Vellano Christopher , Eterovic Karina A. , Song Ping , Tang Lin-ya , Fawcett Gloria , Kim Tae-Beom , Chen Ken , Geiss Gary , Meredith Gavin , Mei Qian , Demirkan Gokhan , Dunaway Dwayne , Kim Dae , Ross P. Martin , Manrao Elizabeth , Elliott Nathan , Warren Sarah , Bailey Christina , Huang Chung-Ying , Beechem Joseph , Mills Gordon , Hood Leroy 
Published: July 2017

Introduction: Development of improved cancer diagnostics and therapeutics requires detailed understanding of the genomic, transcriptomic, and proteomic profiles in the tumor microenvironment. Current technologies can excel at measuring a single analyte, but it remains challenging to simultaneously collect high-throughput DNA, RNA, and protein data from small samples. We have developed an approach that uses optical barcodes to simultaneously profile DNA, RNA, and protein from as little as 5ng DNA, 25ng RNA, and 250ng protein or just 2 5µm FFPE slides, and simplifies data analysis by generating digital counts for each analyte.

Methods: The approach uses paired capture and reporter oligonucleotide probes and optical barcodes to enumerate up to 800 targets. The platform was initially developed to measure RNA, and we have adapted it to measure DNA single nucleotide variants (SNVs), proteins, and phospho-proteins. SNVs are detected by direct hybridization of sequence discriminating probes to the wild-type and mutant sequence of interest. Proteins are detected via binding of oligonucleotide-conjugated antibodies.

Results: Combinations of DNA, RNA, and protein in biological and experimental contexts. SNV probes are able to detect variant alleles down to 5% abundance within a wild type population and can discriminate variants within mutation hotspots. It was &gt;96% accurate at identifying variants from samples displaying a range of allele frequencies and DNA integrity when benchmarked against next-generation sequencing. Protein detection has been developed for cell surface, cytosolic, and nuclear proteins, as well as phospho-proteins. It was validated against flow cytometry, western blot, and mass spectrometry using cell lines with ectopic target expression and primary cells. To demonstrate concurrent measurement of DNA, RNA, and protein from a single system, BRAFWT or BRAFV600E cell lines were treated with the BRAFV600E inhibitor vemurafenib and the MEK inhibitor trametinib. We measured the allele usage at the BRAFV600 locus, as well as BRAFV600E dependent changes in mRNA expression, protein expression and protein phosphorylation in a single experiment.

Conclusions: 3D Biology has several advantages over other analytical approaches. Direct, single-molecule digital counting allows detection over a broad dynamic range with high reproducibility, often over 98% concordance between technical replicates. The simultaneous interrogation of DNA, RNA, and protein maximizes the amount of data obtained from precious samples and minimizes instrumentation demands by leveraging a single detection platform. The 3D Biology approach allows holistic, digital analysis of biological samples with high specificity and precision. This technology is currently available for research use, but may also have clinical application in the future.

Citation Format: Chris Lausted, Yong Zhou, Jinho Lee, Christopher Vellano, Karina A. Eterovic, Ping Song, Lin-ya Tang, Gloria Fawcett, Tae-Beom Kim, Ken Chen, Gary Geiss, Gavin Meredith, Qian Mei, Gokhan Demirkan, Dwayne Dunaway, Dae Kim, P. Martin Ross, Elizabeth Manrao, Nathan Elliott, Sarah Warren, Christina Bailey, Chung-Ying Huang, Joseph Beechem, Gordon Mills, Leroy Hood. NanoString 3D Biology™ technology: simultaneous digital counting of DNA, RNA and protein [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2441. doi:10.1158/1538-7445.AM2017-2441