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.
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.
|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|
|White, Forest M; Wolf-Yadlin, Alejandro (2016) Methods for the Analysis of Protein Phosphorylation-Mediated Cellular Signaling Networks. Annu Rev Anal Chem (Palo Alto Calif) 9:295-315|
|Liu, Qi; Zhang, Bing (2016) Integrative Omics Analysis Reveals Post-Transcriptionally Enhanced Protective Host Response in Colorectal Cancers with Microsatellite Instability. J Proteome Res 15:766-76|
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