Abstract
While considerable research into colorectal cancer (CRC) has implicated many genetic alterations that trigger the disease and sustain its progression, there are few well-validated, clinically useful molecular biomarkers of CRC. The observation that cancer is highly diverse across individual tumors is manifested at the molecular level by concomitantly diverse patterns of gene expression. However, while analysis of gene expression has been used to identify candidate biomarkers of cancer, such biomarkers frequently do not cross validate well on independent datasets and this has raised legitimate concerns regarding the usefulness of gene expression based markers. It is has been postulated that by integrating the functional information of gene products into the approach, networks of mechanistically related gene products may be identified and used to develop more robust biomarkers. Many such approaches focus on established signaling pathways for this purpose; however, pathways consisting of a few proteins interacting in a serial fashion oversimplify, and provide inadequate models for, a complex phenotype (e.g. CRC) mediated by a constellation of interacting gene products. Here, we discuss several integrative techniques based on cellular networks (protein–protein interactions) and incorporation of lower-coverage, but functionally relevant proteomic data, and show the power these techniques hold for prioritizing disease genes for biomarker discovery and biological verification of function.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Vidal M (2005) Interactome modeling. FEBS Lett 579:1834–1838
Edelman EJ, Guinney J et al (2008) Modeling cancer progression via pathway dependencies. PLoS Comput Biol 4:e28
Auffray C (2007) Protein subnetwork markers improve prediction of cancer outcome. Mol Syst Biol 3:141–142
Ideker T, Sharan R (2008) Protein networks in disease. Genome Res 18(4):644–652
Nibbe RK, Chowdhury SA et al (2011) Protein–protein interaction networks and subnetworks in the biology of disease. Wiley Interdiscip Rev Syst Biol Med 3(3):357–367
Shoemaker BA, Panchenko AR (2007) Deciphering protein-protein interactions. Part I. Experimental techniques and databases. PLoS Comput Biol 3:e42
Chuang HY, Lee E, Liu YT, Lee D, Ideker T (2007) Network based classification of breast cancer metastasis. Mol Syst Biol 3:140
Goh KI, Cusick ME et al (2007) The human disease network. Proc Natl Acad Sci U S A 104:8685–8690
Barrenas F, Chavali S et al. (2009) Network properties of complex human disease genes identified through genome-wide association studies. PLoS One 4:e8090
Oti M, Brunner HG (2007) The modular nature of genetic diseases. Clin Genet 71(1):1–11
Vanunu O, Magger O et al (2010) Associating genes and protein complexes with disease via network propagation. PLoS Comput Biol 6(1):e1000641
Liu Y, Koyutürk M et al (2012) Gene interaction enrichment and network analysis to identify dysregulated pathways and their interactions in complex diseases. BMC Syst Biol 6(1):65
Chowdhury SA, Nibbe RK et al (2011) Subnetwork state functions define dysregulated subnetworks in cancer. J Comput Biol 18(3):263–281
Nibbe RK, Markowitz S et al (2009) Discovery and scoring of protein interaction subnetworks discriminative of late stage human colon cancer. Mol Cell Proteomics 8(4):827–845
Friedman DB, Hill S et al (2004) Proteome analysis of human colon cancer by two-dimensional difference electrophoresis and mass spectrometry. Proteomics 4:793–811
Prasad TSK, Goel R et al (2009) Human protein reference database—2009 update. Nucleic Acids Res 37:D767–D772
Ries LAG, Melbert D et al (2007) SEER cancer statistics review, 1975–2004, National Cancer Institute, National Institutes of Health Bethesda, MD
Slattery ML, Samowitz et al (2004) Associations among IRS1, IRS2, IGF1, and IGFBP3 genetic polymorphisms and colorectal cancer. Cancer Epidemiol Biomark Prev 13:1206–1214
Stallmach A, von Lampe B et al (1992) Diminished expression of integrin adhesion molecules on human colonic epithelial cells during the benign to malign tumour transformation. Gut 33:342–346
Barrett T, Wilhite SE et al (2013) NCBI GEO: archive for functional genomics data sets–update. Nucleic Acids Res 41(Database issue):D991–D995
Chatr-Aryamontri A, Breitkreutz BJ et al (2012) The BioGRID interaction database: 2013 update. Nucleic Acids Res 37(Database issue):D412–D416
Jensen et al (2009) STRING 8—a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res 37(Database issue):D412–D416
Dudley JT, Tibshirani R (2009) Disease signatures are robust across tissues and experiments. Mol Syst Biol 5:307
Turner B, Razick S (2010) iRefWeb: interactive analysis of consolidated protein interaction data and their supporting evidence. Database (Oxford) 2010:baq023
Nibbe RK, Koyutürk M et al (2010) An integrative -omics approach to identify functional sub-networks in human colorectal cancer. PLoS Comput Biol 6(1):e1000639
Liu X, Lin CY et al (2005) CCT chaperonin complex is required for the biogenesis of functional Plk1. Mol Cell Biol 25:4993–5010
Coghlin C, Carpenter B et al. (2006) Characterization and over-expression of chaperonin t-complex proteins in colorectal cancer. J Pathol 210:351–357
Sjöblom T, Jones S et al. (2006) The consensus coding sequences of human breast and colorectal cancers. Science 314:268–274
Acknowledgments
The research presented here was supported, in part, by National Institutes of Health Grants UL1-RR024989 from the National Center for Research Resources (Clinical and Translational Science Awards), P30-CA043703 from the Case Western Reserve University Cancer Center Proteomics Core, and T32-GM008803 from the NIGMS (Institutional National Research Service Award). This work was also supported, in part, by NSF CAREER Award CCF-0953195.
All inquiries related to SASSy, X-TALKER, or CRANE should be directed to john.schenkel@neoproteomics.net.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Koyuturk, M., Nibbe, R. (2015). Omics and Biomarkers Development for Intestinal Tumorigenesis. In: Yang, V., Bialkowska, A. (eds) Intestinal Tumorigenesis. Springer, Cham. https://doi.org/10.1007/978-3-319-19986-3_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-19986-3_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19985-6
Online ISBN: 978-3-319-19986-3
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)