Yale School of Public Health Symposium on tissue imaging mass spectrometry: illuminating phenotypic heterogeneity and drug disposition at the molecular level

Georgia Charkoftaki, Nicholas J. W. Rattray, Per E. Andrén, Richard M. Caprioli, Steven Castellino, Mark W. Duncan, Richard J. A. Goodwin, Kevin L. Schey, Sheerin K. Shahidi-Latham, Kirill A. Veselkov, Caroline H. Johnson, Vasilis Vasiliou

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‘A picture is worth a thousand words’ is an idiom from the English language (‘borrowed’ from on old Chinese proverb) that conveys the notion that a complex idea can be succinctly and fully described by a single image. Never has this expression been truer than in the clinical and pharmaceutical arenas. Enormous strides have been made by the scientific community in the evolving field of biomedical imaging with the aim of representing and/or quantifying aspects of disease and drug action by using tools such as radiography, MRI, PET, and ultrasound. Yet linking the phenotypical data generated by these systems to the genome is a challenging task. Identifying the link between the mechanism of disease or failed drug response to the genome of an individual is difficult, because central pieces of information are missing. However, imaging mass spectrometry (IMS) can overcome this issue. IMS aims to detect the molecular constituents of the tissue; these can then be correlated with genome-related characteristics, such as gene expression patterns and possible mutations, and ultimately provide a phenotypic molecular link to the complex disease biology. The big data technology of IMS can generate spatial information of thousands of metabolites and proteins from within a tissue, facilitating a deeper understanding of the connections between the genome, phenotypic characteristics and the biological response. It is a technology that has the potential to serve as a segue between gene expression and observed biological signal.
Original languageEnglish
Number of pages6
JournalHuman Genomics
Issue number10
Publication statusPublished - 27 Feb 2018


  • imaging mass spectrometry
  • biomedical imaging
  • human genome

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