Top-Down Proteomics for Biomarker Research
There’s been considerable excitement of late about the clinical potential of next-generation DNA sequencing. After all, many diseases, such as cancer, sickle cell anemia and Huntington’s disease, are encoded in mutations or variations in genomic DNA. Yet these diseases physically manifest themselves in the presence and absence of proteins and small molecules. Thus, focused efforts are on cataloging and characterizing these molecules to identify molecular indicators (read: biomarkers) of disease, prognosis, therapeutic response and progression. At the protein level, such studies are conducted using mass spectrometry, and they can be done in either of two ways. The simplest and most widely used approach is “bottom-up proteomics.” Here, protein extracts—representing, say, cancerous and normal tissues—are broken down into peptides with a proteinase, chromatographically separated and then analyzed in a mass spectrometer. The goal is to identify peptides (and thus, the proteins they represent) whose abundance or post-translational modification (PTM) changes as a result of disease or treatment.