The Overall Objective of the PNNL Clinical Proteome Characterization Center (PCPCC) is to facilitate cancer biomarker development by linking the cancer genotype to the cancer phenotype using detailed comprehensive and quantitative characterization of cancer proteomes to complement the extensive genome-level characterization provided by The Cancer Genome Atlas (TCGA). The PCPCC will contribute to the success of the planned network of Protein Characterization Centers (PPCs) by utilizing robust and quantitative proteomics technologies and workflows, including simultaneous application of state-of-the-art validated platforms and advanced developmental platforms, for systematic discovery and verification of protein biomarkers that can be qualified in clinical studies, using the cancer specimens and associated data provided by the CPTC. The Discovery Unit will make measurements providing a comprehensive and quantitative characterization of the cancer proteomes that provides Information including protein abundances, splicing variants, mutations, and posttranslational modifications to complement the genomic characterization for CPTC-supplied biospecimens. The extensive database of genomic information on these samples will be integrated with the quantitative proteomic measurements made by the PCPCC, other available proteomics Information (e.g., from other PCC's), and a systems-level analysis of tumor-specific pathways to produce a prioritized list of highly credentialed candidates based on a weighted integration of multiple sources of Information, including clinical oncology and cancer biology. The Verification Unit will systemically develop and apply multiplexed verification assays directed at specific protein targets as identified and selected by the Biomarker Candidate Selection Subcommittee. The PCPCC will develop sensitive, selective, quantitative assays for a minimum of 100 protein targets per year and apply ultra-sensitive assays to biometric verification with a throughput of at least 500 plasma (or serum) samples per year, for a total of at least 2500 samples. Additionally, as in the Discovery efforts, measurements with the best available validated platform will be augmented by measurements with a developmental high performance platform for the same samples (for an overall total of at least 1000 samples per year, and >5000 total) to provide quantitative measurements for low-abundance otherwise undetectable candidates. As part of a consortium of PCC's, the PCPCC will also work to advance the efforts of others based upon e.g. the cancer tumor proteomics data generated, as well as subsequent biomarker clinical qualification and validation efforts.
Despite recent declines in the cancer death rate, cancer remains a significant source of mortality: 25% of all deaths In the US are attributed to cancer. There Is a real clinical need for earlier diagnosis, more accurate prognosis, and more effective therapeutic targeting to improve the outcome for patients with cancer. The PCPCC is dedicated to using the best state-of-the-art and advanced developmental MS platforms and methods, systems biology approaches, and clinical collaborations, to advance the discovery and verification of cancer biomarkers.
|Amidan, Brett G; Orton, Daniel J; Lamarche, Brian L et al. (2014) Signatures for mass spectrometry data quality. J Proteome Res 13:2215-22|
|McDermott, Jason E; Huang, Yufei; Zhang, Bing et al. (2014) Integrative genomics and computational systems medicine. Biomed Res Int 2014:945253|
|Fujimoto, Grant M; Monroe, Matthew E; Rodriguez, Larissa et al. (2014) Accounting for population variation in targeted proteomics. J Proteome Res 13:321-3|
|Mertins, Philipp; Yang, Feng; Liu, Tao et al. (2014) Ischemia in tumors induces early and sustained phosphorylation changes in stress kinase pathways but does not affect global protein levels. Mol Cell Proteomics 13:1690-704|
|Woo, Sunghee; Cha, Seong Won; Na, Seungjin et al. (2014) Proteogenomic strategies for identification of aberrant cancer peptides using large-scale next-generation sequencing data. Proteomics 14:2719-30|
|Whiteaker, Jeffrey R; Halusa, Goran N; Hoofnagle, Andrew N et al. (2014) CPTAC Assay Portal: a repository of targeted proteomic assays. Nat Methods 11:703-4|
|Wu, Chaochao; Shi, Tujin; Brown, Joseph N et al. (2014) Expediting SRM assay development for large-scale targeted proteomics experiments. J Proteome Res 13:4479-87|
|Rodland, Karin D (2014) As if biomarker discovery isn't hard enough: the consequences of poorly characterized reagents. Clin Chem 60:290-1|
|Carr, Steven A; Abbatiello, Susan E; Ackermann, Bradley L et al. (2014) Targeted peptide measurements in biology and medicine: best practices for mass spectrometry-based assay development using a fit-for-purpose approach. Mol Cell Proteomics 13:907-17|
|Wang, Sheng; Yang, Feng; Camp 2nd, David G et al. (2014) Proteomic approaches for site-specific O-GlcNAcylation analysis. Bioanalysis 6:2571-80|
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