The Cancer Genome Atlas (TCGA) initiative, by generating comprehensive genomic characterization of diverse human cancers, poses the critical question of how genomic variation translates to cancer. Genomic abnormalities are thought to drive cancer phenotypes through their effects on proteins and proteomes, which can be analyzed by systematic application of new proteomic technologies. The National Cancer Institute (NCI) Clinical Proteomic Technology Assessment for Cancer (CPTAC) initiative has implemented standardized technology platforms in a biomarker development pipeline and, as one of the initial 5 CPTAC programs, we have made a major contribution to this effort. We have already pioneered this pipeline for cancer biomarker development through the Jim Ayers Institute for Precancer Detection and Diagnosis, a unique initiative established in the Vanderbilt-lngram Cancer Center. This application proposes the Vanderbilt Proteome Characterization Center (Vanderbilt PCC) built on the expertise and infrastructure of the Ayers Institute. The overall goal of the Vanderbilt PCC is to integrate genomic information with proteomic technologies to discover and verify protein biomarkers for cancer. To analyze genomically characterized tumor tissue biospecimens from the TCGA program, we will apply standardized liquid chromatography-tandem mass spectrometry (LC-MS/MS) and liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM-MS) platforms. These analyses will encompass global protein expression changes and changes in phosphorylated and acetylated proteins that regulate signaling networks in cancer. The Vanderbilt PCC will integrate TCGA-derived genomic data and other relevant information into the discovery process and develop systematic approaches to prioritize biomarker candidates. We will verify biomarker candidates in clinically relevant cohorts with standardized, targeted analyses. We will also advance technologies for assessment of signaling networks and functional subproteomes, the integration of genomic and proteomic data and the evaluation of analytical system performance. The Vanderbilt PCC brings to the CPTC network a fully integrated program with expertise in all of the critical areas specified by the RFA.

Public Health Relevance

Cancer is characterized by abnormalities in genes, which are thought to cause disease by altering the content of tissue proteins and the functions they control. This project will use newly-developed technologies to link changes in tissue proteins to extensive new data on genetic abnormalities in tumors. The goal of the project is to identify protein characteristics that could serve as new diagnostics to aid the detection and treatment of cancer.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Resource-Related Research Projects--Cooperative Agreements (U24)
Project #
5U24CA159988-04
Application #
8771264
Study Section
Special Emphasis Panel (ZCA1-SRLB-R (J1))
Program Officer
Rivers, Robert C
Project Start
2011-08-26
Project End
2016-07-31
Budget Start
2014-08-01
Budget End
2015-07-31
Support Year
4
Fiscal Year
2014
Total Cost
$5,426,046
Indirect Cost
$1,735,748
Name
Vanderbilt University Medical Center
Department
Biochemistry
Type
Schools of Medicine
DUNS #
004413456
City
Nashville
State
TN
Country
United States
Zip Code
37212
Wang, Xiaojing; Codreanu, Simona G; Wen, Bo et al. (2018) Detection of Proteome Diversity Resulted from Alternative Splicing is Limited by Trypsin Cleavage Specificity. Mol Cell Proteomics 17:422-430
Simmons, Alan J; Lau, Ken S (2017) Deciphering tumor heterogeneity from FFPE tissues: Its promise and challenges. Mol Cell Oncol 4:e1260191
Fu, Ling; Liu, Keke; Sun, Mingan et al. (2017) Systematic and Quantitative Assessment of Hydrogen Peroxide Reactivity With Cysteines Across Human Proteomes. Mol Cell Proteomics 16:1815-1828
Wang, Jing; Ma, Zihao; Carr, Steven A et al. (2017) Proteome Profiling Outperforms Transcriptome Profiling for Coexpression Based Gene Function Prediction. Mol Cell Proteomics 16:121-134
Sun, Rui; Fu, Ling; Liu, Keke et al. (2017) Chemoproteomics Reveals Chemical Diversity and Dynamics of 4-Oxo-2-nonenal Modifications in Cells. Mol Cell Proteomics 16:1789-1800
Wang, Jing; Mouradov, Dmitri; Wang, Xiaojing et al. (2017) Colorectal Cancer Cell Line Proteomes Are Representative of Primary Tumors and Predict Drug Sensitivity. Gastroenterology 153:1082-1095
Ruggles, Kelly V; Krug, Karsten; Wang, Xiaojing et al. (2017) Methods, Tools and Current Perspectives in Proteogenomics. Mol Cell Proteomics 16:959-981
Morales-Betanzos, Carlos A; Lee, Hyoungjoo; Gonzalez Ericsson, Paula I et al. (2017) Quantitative Mass Spectrometry Analysis of PD-L1 Protein Expression, N-glycosylation and Expression Stoichiometry with PD-1 and PD-L2 in Human Melanoma. Mol Cell Proteomics 16:1705-1717
Hutton, Josiah E; Wang, Xiaojing; Zimmerman, Lisa J et al. (2016) Oncogenic KRAS and BRAF Drive Metabolic Reprogramming in Colorectal Cancer. Mol Cell Proteomics 15:2924-38
Simmons, Alan J; Scurrah, CheriƩ R; McKinley, Eliot T et al. (2016) Impaired coordination between signaling pathways is revealed in human colorectal cancer using single-cell mass cytometry of archival tissue blocks. Sci Signal 9:rs11

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