Proteomic Measurements for Precision Medicine

Proteomes (i.e., the complete set of proteins found in a cell, serum, or biological tissue) are not predicted by genomes and vary with both cell type and time in terms of protein expression levels and post-translational modifications (PTMs).  Proteomics aims to identify, characterize, and quantify proteins, peptides, and PTMs in order to better understand basic biology, discover biomarkers and therapeutic targets, and accelerate drug development.  Ultimately, robust measurements of proteomes could help translate basic science discoveries into the clinical practice of personalized medicine.

A critical and growing need in proteomics is the ability to accurately measure levels of proteins, especially those that may have been modified after biosynthesis (e.g., due to a disease or drug treatment).  Currently, most proteomic analyses rely on mass spectrometry (MS) methods.  Such measurements are challenging due to the dynamic range of protein concentrations in biological samples, which can exceed 10 orders of magnitude, as well as the high number of components in such samples.  In addition, MS is not inherently quantitative and PTMs introduce further complications due to their complexity and diversity (i.e., more than 300 PTMs are known to occur in humans).  PTM detection is often crucial because abnormal PTMs are a hallmark of many diseases, such as cancer.

To address the key challenges of proteomics, researchers at IBBR are developing methods for quantitative protein measurements in complex systems.  One approach focuses on developing internal standards, called QconCATs, for biomarker quantification; QconCATs are artificial proteins composed of concatenated tryptic peptide sequences taken from the target proteins.  Another approach focuses on developing chemical tags and derivatization methods for identifying and quantifying PTMs.  Efforts are also underway to develop next-generation protein sequencing for identification and quantification of proteins, which specifically addresses the limitations of current methods with respect to dynamic range, detection of low abundance proteins, and throughput of measurement.