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J Mol Biol. 2018 Sep 14;430(18 Pt A):2875-2899. doi: 10.1016/j.jmb.2018.06.016. Epub 2018 Jun 15.

The Emerging Potential for Network Analysis to Inform Precision Cancer Medicine.

Author information

1
Department of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA 92093, USA; Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA 92093, USA.
2
Department of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA 92093, USA.
3
Moores Cancer Center, Division of Hematology and Oncology, University of California San Diego, La Jolla, CA 92093, USA.
4
Department of Medicine, Division of Medical Genetics, University of California San Diego, La Jolla, CA 92093, USA; Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA 92093, USA; Moores Cancer Center and Institute for Genomic Medicine, University of California San Diego, La Jolla, CA 92093, USA; CIFAR, MaRS Centre, West Tower, 661 University Ave., Suite 505, Toronto, ON M5G 1M1, Canada. Electronic address: hkcarter@ucsd.edu.

Abstract

Precision cancer medicine promises to tailor clinical decisions to patients using genomic information. Indeed, successes of drugs targeting genetic alterations in tumors, such as imatinib that targets BCR-ABL in chronic myelogenous leukemia, have demonstrated the power of this approach. However, biological systems are complex, and patients may differ not only by the specific genetic alterations in their tumor, but also by more subtle interactions among such alterations. Systems biology and more specifically, network analysis, provides a framework for advancing precision medicine beyond clinical actionability of individual mutations. Here we discuss applications of network analysis to study tumor biology, early methods for N-of-1 tumor genome analysis, and the path for such tools to the clinic.

KEYWORDS:

cancer systems biology; network analysis; precision cancer medicine

PMID:
29908887
PMCID:
PMC6097914
[Available on 2019-09-14]
DOI:
10.1016/j.jmb.2018.06.016
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