Selecting targets for therapeutic validation through differential protein expression using chromatography-mass...

Area of Science:

• Proteomics and Bioinformatics
• Drug Discovery and Development
• Cancer Therapeutics

Background:

• Identifying therapeutic targets requires accurate quantitation of protein expression in normal versus diseased cells.
• Gene and protein expression level comparisons can be confounded by biological variation and disease processes.
• Target validation necessitates demonstrating disease association and minimal expression in healthy tissues.

Purpose of the Study:

• To establish an industrial-scale proteomics platform for reproducible drug target discovery.
• To validate potential therapeutic targets by quantifying protein expression levels.
• To develop processes for identifying small molecule and antibody targets, as well as serum biomarkers.

Main Methods:

• Utilized a proteomics-based discovery platform integrating cell biology, protein chemistry, mass spectrometry, and bioinformatics.
• Employed isotope labeling for differential analysis (ICAT™) to quantify tryptic peptides.
• Applied the platform to human pancreatic adenocarcinoma cell lines for target and biomarker discovery.

Main Results:

• Successfully established processes for discovering small molecule drug targets and therapeutic antibody targets for cell surface proteins.
• Developed a standardized fractionation procedure for identifying serum markers of pancreatic cancer.
• Demonstrated the utility of the proteomics platform in a large-scale study of pancreatic cancer cell lines.

Conclusions:

• Reproducible quantitation of protein expression levels via large-scale proteomics is an effective method for generating high-utility drug targets.
• The developed platform enables efficient identification of therapeutic targets and biomarkers for diseases like pancreatic cancer.
• Addressing challenges in both experimental and computational aspects is crucial for successful target discovery undertakings.