Cancer systems biology in the genome sequencing era: part 1, dissecting and modeling of tumor clones and their networks.

Recent tumor genome sequencing confirmed that one tumor often consists of multiple cell subpopulations (clones) which bear different, but related, genetic profiles such as mutation and copy number variation profiles. Thus far, one tumor has been viewed as a whole entity in cancer functional studies. With the advances of genome sequencing and computational analysis, we are able to quantify and computationally dissect clones from tumors, and then conduct clone-based analysis. Emerging technologies such as single-cell genome sequencing and RNA-Seq could profile tumor clones. Thus, we should reconsider how to conduct cancer systems biology studies in the genome sequencing era. We will outline new directions for conducting cancer systems biology by considering that genome sequencing technology can be used for dissecting, quantifying and genetically characterizing clones from tumors. Topics discussed in Part 1 of this review include computationally quantifying of tumor subpopulations; clone-based network modeling, cancer hallmark-based networks and their high-order rewiring principles and the principles of cell survival networks of fast-growing clones.

[1]  Edwin Wang,et al.  Understanding genomic alterations in cancer genomes using an integrative network approach. , 2013, Cancer letters.

[2]  B. Vogelstein,et al.  Clonal analysis of human colorectal tumors. , 1987, Science.

[3]  E. Schadt,et al.  Characterizing the role of miRNAs within gene regulatory networks using integrative genomics techniques , 2011, Molecular systems biology.

[4]  Lincoln Stein,et al.  Reactome: a database of reactions, pathways and biological processes , 2010, Nucleic Acids Res..

[5]  Ji Luo,et al.  Cancer Proliferation Gene Discovery Through Functional Genomics , 2008, Science.

[6]  Edwin Wang,et al.  Dynamic rewiring of the androgen receptor protein interaction network correlates with prostate cancer clinical outcomes. , 2011, Integrative biology : quantitative biosciences from nano to macro.

[7]  Julio Saez-Rodriguez,et al.  Mapping the human phosphatome on growth pathways , 2012, Molecular systems biology.

[8]  P. Nowell The clonal evolution of tumor cell populations. , 1976, Science.

[9]  Jan-Fang Cheng,et al.  Dicer, Drosha, and outcomes in patients with ovarian cancer. , 2008, The New England journal of medicine.

[10]  J. Dopazo,et al.  Discovering the hidden sub-network component in a ranked list of genes or proteins derived from genomic experiments , 2012, Nucleic acids research.

[11]  D. Lauffenburger,et al.  Combined experimental and computational analysis of DNA damage signaling reveals context-dependent roles for Erk in apoptosis and G1/S arrest after genotoxic stress , 2012, Molecular systems biology.

[12]  N. Rosenfeld,et al.  Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA , 2013, Nature.

[13]  E. Wang,et al.  Dynamic modeling and analysis of cancer cellular network motifs. , 2011, Integrative biology : quantitative biosciences from nano to macro.

[14]  Hidenori Ojima,et al.  Downregulation of the microRNA biogenesis components and its association with poor prognosis in hepatocellular carcinoma , 2013, Cancer science.

[15]  C. Sander,et al.  Mutual exclusivity analysis identifies oncogenic network modules. , 2012, Genome research.

[16]  Sol Efroni,et al.  Biomarker robustness reveals the PDGF network as driving disease outcome in ovarian cancer patients in multiple studies , 2012, BMC Systems Biology.

[17]  Steven J. M. Jones,et al.  Comprehensive molecular portraits of human breast tumours , 2013 .

[18]  Q. Cui,et al.  Regulatory network motifs and hotspots of cancer genes in a mammalian cellular signalling network. , 2007, IET systems biology.

[19]  A. McKenna,et al.  Absolute quantification of somatic DNA alterations in human cancer , 2012, Nature Biotechnology.

[20]  Edda Klipp,et al.  Modelling reveals novel roles of two parallel signalling pathways and homeostatic feedbacks in yeast , 2012, Molecular systems biology.

[21]  Steven J. M. Jones,et al.  Comprehensive genomic characterization of squamous cell lung cancers , 2012, Nature.

[22]  Yang Xiang,et al.  Weighted Frequent Gene Co-expression Network Mining to Identify Genes Involved in Genome Stability , 2012, PLoS Comput. Biol..

[23]  F. Ferrari,et al.  A MicroRNA Targeting Dicer for Metastasis Control , 2010, Cell.

[24]  M. Gerstein,et al.  AlleleSeq: analysis of allele-specific expression and binding in a network framework , 2011, Molecular systems biology.

[25]  Kenneth H. Buetow,et al.  PID: the Pathway Interaction Database , 2008, Nucleic Acids Res..

[26]  N. Carter,et al.  Massive Genomic Rearrangement Acquired in a Single Catastrophic Event during Cancer Development , 2011, Cell.

[27]  Edwin Wang Cancer Systems Biology , 2010 .

[28]  Edwin Wang,et al.  Signaling network analysis of ubiquitin-mediated proteins suggests correlations between the 26S proteasome and tumor progression. , 2009, Molecular bioSystems.

[29]  B. Vogelstein,et al.  A genetic model for colorectal tumorigenesis , 1990, Cell.

[30]  Edwin Wang,et al.  Cancer systems biology in the genome sequencing era: part 2, evolutionary dynamics of tumor clonal networks and drug resistance. , 2013, Seminars in cancer biology.

[31]  A. Børresen-Dale,et al.  The Life History of 21 Breast Cancers , 2012, Cell.

[32]  Javier M. Buldú,et al.  Successful strategies for competing networks , 2013, ArXiv.

[33]  Hiroaki Kitano,et al.  A framework for mapping, visualisation and automatic model creation of signal-transduction networks , 2012, Molecular systems biology.

[34]  Mark D. Johnson,et al.  Functional genomic analysis of chromosomal aberrations in a compendium of 8000 cancer genomes , 2013, Genome research.

[35]  Stephen J. Elledge,et al.  Profiling Essential Genes in Human Mammary Cells by Multiplex RNAi Screening , 2008, Science.

[36]  Y. Nakamura,et al.  Genetic alterations during colorectal-tumor development. , 1988, The New England journal of medicine.

[37]  Benjamin J. Raphael,et al.  Integrated Genomic Analyses of Ovarian Carcinoma , 2011, Nature.

[38]  Edwin Wang,et al.  Self-organization of gene regulatory network motifs enriched with short transcript's half-life transcription factors , 2005, q-bio/0504025.

[39]  T. Graeber,et al.  Glucose deprivation activates a metabolic and signaling amplification loop leading to cell death , 2012, Molecular systems biology.

[40]  Steven J. M. Jones,et al.  Comprehensive molecular portraits of human breast tumors , 2012, Nature.

[41]  Zhiping Weng,et al.  Identification of functional modules that correlate with phenotypic difference: the influence of network topology , 2010, Genome Biology.

[42]  Q. Cui,et al.  Identification of high-quality cancer prognostic markers and metastasis network modules , 2010, Nature communications.

[43]  Jeremy L. Muhlich,et al.  Properties of cell death models calibrated and compared using Bayesian approaches , 2013, Molecular systems biology.

[44]  Simo V. Zhang,et al.  A map of human cancer signaling , 2007, Molecular systems biology.

[45]  J. Qian,et al.  Construction of human activity-based phosphorylation networks , 2013, Molecular systems biology.

[46]  T. Ideker,et al.  Differential network biology , 2012, Molecular systems biology.

[47]  C. Perou,et al.  Allele-specific copy number analysis of tumors , 2010, Proceedings of the National Academy of Sciences.

[48]  E. Wang,et al.  Genetic studies of diseases , 2007, Cellular and Molecular Life Sciences.

[49]  A. McKenna,et al.  Evolution and Impact of Subclonal Mutations in Chronic Lymphocytic Leukemia , 2012, Cell.

[50]  Q. Cui,et al.  Principles of microRNA regulation of a human cellular signaling network , 2006, Molecular systems biology.

[51]  M. Moran,et al.  The human phosphotyrosine signaling network: Evolution and hotspots of hijacking in cancer , 2012, Genome research.

[52]  D. Horst,et al.  Overexpression of Dicer predicts poor survival in colorectal cancer. , 2011, European journal of cancer.