Messenger and noncoding RNAs expression play a central role in shaping tumor development and clinical cancer outcomes. However, it is not possible to fully appreciate their functions in the absence of spatial context information. This application seeks to develop mass-tag-based molecularly specific imaging methods that can will be able to detect as many as 40 to 100+ in situ hybridization (ISH) RNA targets in morphologically intact cells and tissues, simultaneously and with single-molecule sensitivity. The technique is analogous to laser-scanning confocal microscopy, except that the scanning is performed using a tightly focused ion beam, rather than a similarly sized point of laser light. And instead of fluorophores, the labels detected are clusters of metal atoms attached to individual probes. When ionized and collected at a detector, these metal species are unambiguously distinguished based on their mass (atomic weight). Preliminary data using a highly focused, scanning oxygen ion beam and 10 antibodies applied simultaneously to clinical formalin-fixed, paraffin- embedded breast cancer tissues demonstrate histology-like images that reveal bound antibody location with subcellular resolution. We will extend this work to develop and validate similar methods for the simultaneous detection of multiple different coding and/or noncoding RNA species, particularly those with proven or suspected significance for cancer biology and translational medicine. The RNA labeling technology will be based on the related but non-imaging approach of mass-tag-based flow cytometry developed in the Nolan laboratory. This labeling strategy relies in part on paired initial cDNA probes that must bind to adjacent sequences to generate a secondary target for branched-chain metal-labeled DNA reporters. The initial double- binding requirement dramatically decreases the impact of non-specific binding on ultimate signal generation. First steps will be to demonstrate the feasibility of mass-tagged multiplexed detection of RNA species. We will optimize labeling and binding parameters necessary to achieve at least 10X multiplexing, and will determine achievable sensitivity and specificity. We will then explore effects of pre-analytical variables including sample preparation methodologies. Finally, to document potential utility, we will examine cell lines with well- documented quantitative RNA expression profiles, as well as mouse and human clinical breast cancer specimens using relevant probe targets. Implications: The methods outlined here will allow spatially resolved evaluation of numerous signaling pathways simultaneously, and will also shed light on interactions between cells whose detailed individual phenotypes we can assess. In addition, at the subcellular level, we anticipate that the ability to detect, in three- dimensions, multiple RNAs and RNA-protein complexes with ~50-nm isotropic resolution will open up new vistas in basic and translational cell biology. Clinically, we expect to adapt existing gene-expression panel analysis to intact tissues-with an ability to monitor relevant but possibly minor tumor subpopulations.

Public Health Relevance

The biology and clinical course of cancers can often be predicted by the presence and distribution within cells and tissues of RNA molecules that play roles in cell division, invasion, metastasis and evasion of the host's immune system. While next-generation analysis tools, like DNA and RNA sequencing, can look at thousands or even millions of bits of molecular data, they typically do not show where the relevant molecules are located. We describe a new, non-optical microscopic technology that can visualize as many as 100 RNA molecules inside cells and tissues simultaneously;we think this may prove to be a remarkable engine for research and clinical advances in the understanding and treatment of cancer.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Exploratory/Developmental Grants (R21)
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Special Emphasis Panel (ZCA1-SRLB-Q (J1))
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Mazurchuk, Richard V
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University of California Davis
Schools of Medicine
United States
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Wernig, Gerlinde; Chen, Shih-Yu; Cui, Lu et al. (2017) Unifying mechanism for different fibrotic diseases. Proc Natl Acad Sci U S A 114:4757-4762
Jensen, Helle; Chen, Shih-Yu; Folkersen, Lasse et al. (2017) EBI3 regulates the NK cell response to mouse cytomegalovirus infection. Proc Natl Acad Sci U S A 114:1625-1630
Mukherjee, Sayak; Jensen, Helle; Stewart, William et al. (2017) In silico modeling identifies CD45 as a regulator of IL-2 synergy in the NKG2D-mediated activation of immature human NK cells. Sci Signal 10:
Frei, Andreas P; Bava, Felice-Alessio; Zunder, Eli R et al. (2016) Highly multiplexed simultaneous detection of RNAs and proteins in single cells. Nat Methods 13:269-75
Samusik, Nikolay; Good, Zinaida; Spitzer, Matthew H et al. (2016) Automated mapping of phenotype space with single-cell data. Nat Methods 13:493-6
Levenson, Richard M; Borowsky, Alexander D; Angelo, Michael (2015) Immunohistochemistry and mass spectrometry for highly multiplexed cellular molecular imaging. Lab Invest 95:397-405