In this application, we propose to establish an integrated proteome characterization center (PCC) with an outstanding team of scientists and clinicians in order to construct a cancer biomarker pipeline using genoproteomic approaches. This multidisciplinary team consists of internationally recognized experts in clinical oncology, clinical chemistry, cancer biology, proteomic technologies, proteomics/genomics-specific bioinformatics, biostatistics and experimental design, metrology/standards, technology optimization, assay construction, project management and patient advocacy. The plan is to connect genomics with proteomics (genoproteomics). We believe that genomic data provides a highly valuable molecular route towards the identification of genes and pathways that could be useful for the detection, differential diagnosis, outcome prediction and therapeutic targets of cancer. The proteomic approaches will provide the identification of unique features that are inherent to proteins including post-translational modifications, such as glycosylation and phosphorylation. We propose a two- step strategy to construct an evidence-based, proteomic biomarker pipeline for ovarian and other carcinomas. The first step is the discovery of candidate biomarkers from genomic data including TCGA using mass spectrometry and affinity based technologies on human specimens. The goal is to comprehensively characterize tumor and normal biospecimens and identify their protein composition in order to systematically identify and prioritize cancer-related proteins for advancement to verification. The second step is the verification of these candidates using targeted assays. The goal is to generate accurate, reproducible, sensitive, quantitative, multiplex assays using optimized and standardized high-throughput technologies for the discovered biomarkers. While this application is not intended to conduct large scale clinical studies, we believe that the ultimate clinical application and the performance characteristics of these assays should be clearly defined. With this multidisciplinary team of outstanding scientists and clinicians, our PCC offers the best opportunity for the success of biomarker discovery and verification for personalized cancer medicine.

Public Health Relevance

Understanding the molecular networking in carcinogenesis is essential for the development of a successful strategy to reduce cancer mortality. Based on the genomic alterations identified from TCGA and other sources, this application will focus on the development of a clinically useful protein biomarker pipeline using state-of-the art proteomics technologies for personalized cancer medicine.

National Institute of Health (NIH)
National Cancer Institute (NCI)
Resource-Related Research Projects--Cooperative Agreements (U24)
Project #
Application #
Study Section
Special Emphasis Panel (ZCA1-SRLB-R (J1))
Program Officer
Hiltke, Tara
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Johns Hopkins University
Schools of Medicine
United States
Zip Code
Thomas, Stefani N; Chen, Lijun; Liu, Yang et al. (2017) Targeted Proteomic Analyses of Histone H4 Acetylation Changes Associated with Homologous-Recombination-Deficient High-Grade Serous Ovarian Carcinomas. J Proteome Res 16:3704-3710
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
Zhou, Jianliang; Yang, Weiming; Hu, Yingwei et al. (2017) Site-Specific Fucosylation Analysis Identifying Glycoproteins Associated with Aggressive Prostate Cancer Cell Lines Using Tandem Affinity Enrichments of Intact Glycopeptides Followed by Mass Spectrometry. Anal Chem 89:7623-7630
Yang, Shuang; Zhang, Lei; Thomas, Stefani et al. (2017) Modification of Sialic Acids on Solid Phase: Accurate Characterization of Protein Sialylation. Anal Chem 89:6330-6335
Wan, Jun; Su, Yijing; Song, Qifeng et al. (2017) Methylated cis-regulatory elements mediate KLF4-dependent gene transactivation and cell migration. Elife 6:
Wu, Xinyan; Zahari, Muhammad Saddiq; Renuse, Santosh et al. (2017) The non-receptor tyrosine kinase TNK2/ACK1 is a novel therapeutic target in triple negative breast cancer. Oncotarget 8:2971-2983
Shah, Punit; Yang, Weiming; Sun, Shisheng et al. (2017) Platelet glycoproteins associated with aspirin-treatment upon platelet activation. Proteomics 17:
Yang, Shuang; Clark, David; Liu, Yang et al. (2017) High-throughput analysis of N-glycans using AutoTip via glycoprotein immobilization. Sci Rep 7:10216
Yu, Kun-Hsing; Hart, Steven N; Goldfeder, Rachel et al. (2017) HARNESSING BIG DATA FOR PRECISION MEDICINE: INFRASTRUCTURES AND APPLICATIONS. Pac Symp Biocomput 22:635-639
Yu, Kun-Hsing; Berry, Gerald J; Rubin, Daniel L et al. (2017) Association of Omics Features with Histopathology Patterns in Lung Adenocarcinoma. Cell Syst 5:620-627.e3

Showing the most recent 10 out of 155 publications