Colorectal cancer (CRC) is the third leading cause of cancer-related death in the United States. Metastatic spread is the cause of death for the vast majority of patients who die from solid tumors, including CRC patients. Notwithstanding the extensive molecular data collected on human tumors and metastatic models, the process of metastasis remains poorly understood. Our long-term goal is to use integrative systems biology approaches to investigate the molecular mechanisms that underlie CRC metastasis in order to develop new strategies for the prognosis and treatment of CRC patients. The central hypothesis for this proposal is as follows: Metastasis is the functional consequence of the deregulation of interconnected gene networks. We propose that metastasis-related networks can be identified by analyzing gene expression profiles from well-defined metastatic models within the context of gene co-expression and protein interaction networks.
Specific aims are: 1) Identify metastasis-related network modules and make module-based predictions for CRC survival. 2) Derive, validate, and confirm functional significance of transcriptional regulators of survival-predictive modules. 3) Network-based prioritization and experimental screening of putative effectors of metastasis. The proposed studies will provide important information on the network mechanisms of CRC metastasis and use this information to improve patient prognosis and discover novel therapeutic targets.

Public Health Relevance

Biological basis of colorectal cancer metastasis is poorly understood. We hypothesize that metastasis is the functional consequence of the deregulation of interconnected gene networks. The studies will integrate computational and experimental approaches to identify network mechanisms of CRC metastasis in order to improve patient prognosis and discover novel therapeutic targets.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM088822-04
Application #
8294651
Study Section
Special Emphasis Panel (ZGM1-GDB-2 (CP))
Program Officer
Krasnewich, Donna M
Project Start
2009-08-20
Project End
2014-06-30
Budget Start
2012-07-01
Budget End
2014-06-30
Support Year
4
Fiscal Year
2012
Total Cost
$382,239
Indirect Cost
$137,214
Name
Vanderbilt University Medical Center
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
004413456
City
Nashville
State
TN
Country
United States
Zip Code
37212
Slebos, Robbert J C; Wang, Xia; Wang, Xiaojing et al. (2015) Proteomic analysis of colon and rectal carcinoma using standard and customized databases. Sci Data 2:150022
Zhang, Bing; Wang, Jing; Wang, Xiaojing et al. (2014) Proteogenomic characterization of human colon and rectal cancer. Nature 513:382-7
Tripathi, Manish K; Deane, Natasha G; Zhu, Jing et al. (2014) Nuclear factor of activated T-cell activity is associated with metastatic capacity in colon cancer. Cancer Res 74:6947-57
Wang, Xiaojing; Zhang, Bing (2014) Integrating genomic, transcriptomic, and interactome data to improve Peptide and protein identification in shotgun proteomics. J Proteome Res 13:2715-23
Halvey, Patrick J; Wang, Xiaojing; Wang, Jing et al. (2014) Proteogenomic analysis reveals unanticipated adaptations of colorectal tumor cells to deficiencies in DNA mismatch repair. Cancer Res 74:387-97
Shi, Zhiao; Wang, Jing; Zhang, Bing (2013) NetGestalt: integrating multidimensional omics data over biological networks. Nat Methods 10:597-8
Liu, Qi; Ullery, Jody; Zhu, Jing et al. (2013) RNA-seq data analysis at the gene and CDS levels provides a comprehensive view of transcriptome responses induced by 4-hydroxynonenal. Mol Biosyst 9:3036-46
Wang, Jing; Qian, Jun; Hoeksema, Megan D et al. (2013) Integrative genomics analysis identifies candidate drivers at 3q26-29 amplicon in squamous cell carcinoma of the lung. Clin Cancer Res 19:5580-90
Liu, Qi; Halvey, Patrick J; Shyr, Yu et al. (2013) Integrative omics analysis reveals the importance and scope of translational repression in microRNA-mediated regulation. Mol Cell Proteomics 12:1900-11
Zhu, Jing; Wang, Jing; Shi, Zhiao et al. (2013) Deciphering genomic alterations in colorectal cancer through transcriptional subtype-based network analysis. PLoS One 8:e79282

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