Diagnosing Cancer By Analyzing Glycans

Aberrantly expressed glycosyltransferases are characteristic of a number of diseases, but detecting specific glycosyltransferases for diagnostic use is notoriously difficult. The next best thing would be to detect abnormal glycans produced by the disease-related glycosyltransferases, but single glycans cannot be directly connected to the activity of specific glycosyltransferases. A new “bottom up” (component analysis) technique devised by Chad R. Borges of the Biodesign Institute at Arizona State University and coworkers could help resolve this logjam (Anal. Chem., DOI: 10.1021/ac3035579). Noting that unusual disease-related glycans contain unique amounts of “glycan nodes”—characteristic combinations of specific sugars and linkage types—they developed a GC/MS technique to detect node levels as stand-ins for the disease-related glyco­syltransferases that produce them. They use the technique to diagnose lung cancer in blood plasma samples with 76 to 88% reliability. They believe the reliability can be improved and the technique can be extended to diagnose a variety of other conditions.