Prospects and challenges of cancer systems medicine: from genes to disease networks

Author:

Karimi Mohammad Reza1,Karimi Amir Hossein1,Abolmaali Shamsozoha1,Sadeghi Mehdi1,Schmitz Ulf2

Affiliation:

1. Department of Cell & Molecular Biology, Semnan University, Semnan, Iran

2. Department of Molecular & Cell Biology, James Cook University, Townsville, QLD 4811, Australia

Abstract

Abstract It is becoming evident that holistic perspectives toward cancer are crucial in deciphering the overwhelming complexity of tumors. Single-layer analysis of genome-wide data has greatly contributed to our understanding of cellular systems and their perturbations. However, fundamental gaps in our knowledge persist and hamper the design of effective interventions. It is becoming more apparent than ever, that cancer should not only be viewed as a disease of the genome but as a disease of the cellular system. Integrative multilayer approaches are emerging as vigorous assets in our endeavors to achieve systemic views on cancer biology. Herein, we provide a comprehensive review of the approaches, methods and technologies that can serve to achieve systemic perspectives of cancer. We start with genome-wide single-layer approaches of omics analyses of cellular systems and move on to multilayer integrative approaches in which in-depth descriptions of proteogenomics and network-based data analysis are provided. Proteogenomics is a remarkable example of how the integration of multiple levels of information can reduce our blind spots and increase the accuracy and reliability of our interpretations and network-based data analysis is a major approach for data interpretation and a robust scaffold for data integration and modeling. Overall, this review aims to increase cross-field awareness of the approaches and challenges regarding the omics-based study of cancer and to facilitate the necessary shift toward holistic approaches.

Funder

Cancer Institute New South Wales

National Health and Medical Research Council

Cancer Council NSW

Publisher

Oxford University Press (OUP)

Subject

Molecular Biology,Information Systems

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