“RADIOTRANSCRIPTOMICS”: A synergy of imaging and transcriptomics in clinical assessment

Abstract

Recent advances in quantitative imaging and “omics” technology have generated a wealth of mineable biological “big data”. With the push towards a P4 “predictive, preventive, personalized, and participatory” approach to medicine, researchers began integrating complementary tools to further tune existing diagnostic and therapeutic models. The field of radiogenomics has long pioneered such multidisciplinary investigations in neuroscience and oncology, correlating genotypic and phenotypic signatures to study structural and functional changes in relation to altered molecular behavior. Given the innate dynamic nature of complex disorders and the role of environmental and epigenetic factors in pathogenesis, the transcriptome can further elucidate serial modifications undetected at the genome level. We therefore propose “radiotranscriptomics” as a new member of the P4 medicine initiative, combining transcriptome information, including gene expression and isoform variation, and quantitative image annotations.

Graphical abstract

Keywords

quantitative imaging / transcriptomics / RNA-seq / genomics / image genomics / radiogenomics / systems biology / precision medicine

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ACKNOWLEDGEMENTS

This study is supported by National Institutes of Health grants (R01GM105431 and R01NS076631 to Y. X.; R01CA157553 to W. H. and A. B.). Y. X. is supported by an Alfred Sloan Research Fellowship. A. K. is supported by NIH-NCI Biomedical Big Data Training Program at UCLA (T32CA201160).

The authors Amal Katrib, William Hsu, Alex Bui and Yi Xing declare that they have no conflict of interests.

This article does not contain any studies with human or animal subjects performed by any of the authors.

Funding

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg