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Review
. 2018 Feb 21;9(1):77-102.
doi: 10.1007/s13167-018-0128-8. eCollection 2018 Mar.

The crucial role of multiomic approach in cancer research and clinically relevant outcomes

Miaolong Lu  1   2   3 , Xianquan Zhan  1   2   3   4
Affiliations
Review

The crucial role of multiomic approach in cancer research and clinically relevant outcomes

Miaolong Lu et al. EPMA J. .

Abstract

Cancer with heavily economic and social burden is the hot point in the field of medical research. Some remarkable achievements have been made; however, the exact mechanisms of tumor initiation and development remain unclear. Cancer is a complex, whole-body disease that involves multiple abnormalities in the levels of DNA, RNA, protein, metabolite and medical imaging. Biological omics including genomics, transcriptomics, proteomics, metabolomics and radiomics aims to systematically understand carcinogenesis in different biological levels, which is driving the shift of cancer research paradigm from single parameter model to multi-parameter systematical model. The rapid development of various omics technologies is driving one to conveniently get multi-omics data, which accelerates predictive, preventive and personalized medicine (PPPM) practice allowing prediction of response with substantially increased accuracy, stratification of particular patients and eventual personalization of medicine. This review article describes the methodology, advances, and clinically relevant outcomes of different "omics" technologies in cancer research, and especially emphasizes the importance and scientific merit of integrating multi-omics in cancer research and clinically relevant outcomes.

Keywords: Cancer; Multi-omics; Personalization of medical services; Predictive, preventive medicine.

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Conflict of interest statement

Compliance with ethical standardsThe authors declare that there is no conflict of interests regarding the publication of this article.

Figures

Fig. 1
Fig. 1
Multiomics and PPPM in cancer
Fig. 2
Fig. 2
The general workflow of RNA-seq. EST: expressed sequence tag
Fig. 3
Fig. 3
The MS-based proteomics workflow. 2DGE: two-dimensional gel electrophoresis; MS: mass spectrometry; MS/MS: tandem mass spectrometry; and LC: liquid chromatography
Fig. 4
Fig. 4
The general workflow of radiomics
See this image and copyright information in PMC

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