Constructing personalized longitudinal holo’omes of colon cancer-prone humans and their modeling in flies and mice

Myrofora Panagi, Konstantina Georgila, Aristides G. Eliopoulos and Yiorgos Apidianakis _

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Oncotarget. 2019; 10:4224-4246. https://doi.org/10.18632/oncotarget.6463

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Myrofora Panagi1, Konstantina Georgila2, Aristides G. Eliopoulos2,3 and Yiorgos Apidianakis1

1 Department of Biological Sciences, University of Cyprus, Aglatzia, Nicosia, Cyprus

2 Laboratory of Molecular and Cellular Biology, Division of Basic Sciences, University of Crete Medical School, Heraklion, Crete, Greece

3 Institute of Molecular Biology and Biotechnology, Forth, Heraklion, Crete, Greece

Correspondence to:

Yiorgos Apidianakis, email:

Keywords: Drosophila, inflammation, cancer, microbiota

Received: August 12, 2015    Accepted: November 26, 2015    Epub: December 04, 2015    Published: June 25, 2019


Specific host genes and intestinal microbes, dysbiosis, aberrant immune responses and lifestyle may contribute to intestinal inflammation and cancer, but each of these parameters does not suffice to explain why sporadic colon cancer develops at an old age and only in some of the people with the same profile. To improve our understanding, longitudinal multi-omic and personalized studies will help to pinpoint combinations of host genetic, epigenetic, microbiota and lifestyle-shaped factors, such as blood factors and metabolites that change as we age. The intestinal holo’ome – defined as the combination of host and microbiota genomes, transcriptomes, proteomes, and metabolomes – may be imbalanced and shift to disease when the wrong host gene expression profile meets the wrong microbiota composition. These imbalances can be triggered by the dietary- or lifestyle-shaped intestinal environment. Accordingly, personalized human intestinal holo’omes will differ significantly among individuals and between two critical points in time: long before and upon the onset of disease. Detrimental combinations of factors could therefore be pinpointed computationally and validated using animal models, such as mice and flies. Finally, treatment strategies that break these harmful combinations could be tested in clinical trials. Herein we provide an overview of the literature and a roadmap to this end.

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