Signature peptide selection workflow for biomarker quantification using LC-MS-based targeted proteomics.

In contrast to quantification of biotherapeutics, endogenous protein biomarker and target quantification using LC-MS based targeted proteomics can require a much more stringent and time-consuming tryptic signature peptide selection for each specific application. While some general criteria exist, there are no tools currently available in the public domain to predict the ionization efficiency for a given signature peptide candidate. Lack of knowledge of the ionization efficiencies forces investigators to choose peptides blindly, thus hindering method development for low abundant protein quantification.

Comparison of three parallelism assessment methods of biomarker quantification by LC-MS/MS: a case study of the bioanalysis of creatinine in human urine samples.

Currently, no regulatory guidelines are available for parallelism assessment for LC-MS biomarker quantification. Spike recovery, standard addition and dilutional linearity are recommended with no mention of the implications of applying these approaches. Here, using human urine creatinine, the authors compared spike recovery and standard addition in LC-MS biomarker quantification, and evaluated a new hybrid approach: parallelism QCs.