MIBI-TOF: A multiplexed imaging platform relates cellular phenotypes and tissue structure

Leeat Keren(Stanford University), Marc Bossé(Stanford University), Steve Thompson(Stanford University), Tyler Risom(Stanford University), Kausalia Vijayaragavan(Stanford University), Erin McCaffrey(Stanford University), Diana M. Marquez(Stanford University), Roshan Angoshtari(Stanford University), Noah F. Greenwald(Stanford University), Harris G. Fienberg(Stanford University), Jennifer Wang(Stanford University), Neeraja Kambham(Stanford University), David H. Kirkwood(Stanford University), Garry P. Nolan(Stanford University), Thomas J. Montine(Stanford University), Stephen J. Galli(Stanford University), Robert B. West(Stanford University), Sean C. Bendall(Stanford University), Michael Angelo(Stanford University)
Science Advances
October 9, 2019
Cited by 448Open Access
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Abstract

Understanding tissue structure and function requires tools that quantify the expression of multiple proteins while preserving spatial information. Here, we describe MIBI-TOF (multiplexed ion beam imaging by time of flight), an instrument that uses bright ion sources and orthogonal time-of-flight mass spectrometry to image metal-tagged antibodies at subcellular resolution in clinical tissue sections. We demonstrate quantitative, full periodic table coverage across a five-log dynamic range, imaging 36 labeled antibodies simultaneously with histochemical stains and endogenous elements. We image fields of view up to 800 μm × 800 μm at resolutions down to 260 nm with sensitivities approaching single-molecule detection. We leverage these properties to interrogate intrapatient heterogeneity in tumor organization in triple-negative breast cancer, revealing regional variability in tumor cell phenotypes in contrast to a structured immune response. Given its versatility and sample back-compatibility, MIBI-TOF is positioned to leverage existing annotated, archival tissue cohorts to explore emerging questions in cancer, immunology, and neurobiology.


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