Biomarkers measured in a minimally invasive and repeatable way can expedite the early diagnosis of disease, the indication of disease prognosis, and the discovery of new drug targets for therapy. Serum proteomic profiling for biomarker detection may reflect the abnormality or pathologic state of various diseases through the protein/peptide peaks that are expressed differently between diseased and healthy individuals. Since the procedures are simple, inexpensive, and minimally invasive, serum proteomic methods readily lend themselves to screening-test development; their robustness and ease promise to translate into routine clinical practice. The objective of this project is to construct a high-throughput proteomic profiling analysis toolset, Proteomics Biomarker Information System (ProBIS), which can provide early biomarker detection and identification for clinical proteomics healthcare. Our main contributions are: (1) High Resolution Proteomic Profiling: different from traditional low resolution mass spectrometry analysis, we will use high resolution profile to analyze the low-molecular weight (LMW) end of the proteomic spectrum for more precise analysis; and (2) Integrated System for Biomarker Discovery and Identification: identification and sequencing of the underlying discriminatory proteins/peptides will reveal the insights of biomarkers and characterize disease pathway. The results of this project will have an impact on the computer science community and an equal, if not greater, impact on the broad medical community that is in need of such a proteomic profiling data analysis tool. The experiments will be driven by a series of case studies, including ovarian cancer early relapse monitoring and prostate cancer diagnosis. The solutions for these case studies will have a direct impact on individual areas. Our source code and data will be available for general dissemination over the internet, and discoveries will be integrated into the classroom.
