Surface-activated chemical ionization-electrospray ionization source improves biomarker discovery with mass spectrometry

Abstract

Rationale: Mass spectrometry (MS) is increasingly employed for the discovery of clinical biomarkers. However, due to sensitivity limitations related to in-source ionization yield, many potential biomarkers are not detected by standard mass spectrometers. Therefore, more efficient ion-source technologies are needed to improve MS applications in biomarker discovery.

Methods: Among novel ion-source technologies, Surface-Activated Chemical Ionization (SACI), although endowed with high sensitivity linked to its ability to reduce chemical noise in mass spectra, has seen limited application in biomarker discovery to date, due to its selectivity for highly polar compounds. However, in combination with an Electrospray Ionization (ESI) source, SACI selectivity can be enlarged in the range of less polar compounds. To validate the new SACI-ESI approach in biomarker discovery, we applied it to a translational setting in oncology. We performed MS profiles of 101 human serum samples from a male population, aged 40 or older, coming to the clinic for prostate cancer evaluation based on multiple PSA exams, digital rectal examination and echography. The SACI-ESI MS spectra were analyzed and classified with an innovative bioinformatic approach based on the MS-search freeware developed in house.

Results: Here we demonstrate that the SACI-ESI combination can produce MS spectra with greater sensitivity and lower noise than those obtained with the common ESI alone. We found that the SACI-ESI combination increased the number of detectable compounds and produced better quality of profiles in liquid chromatography (LC) coupled with MS (LC/MS) analysis of human serum samples, improving disease prediction potential.

Conclusions: SACI-ESI can facilitate MS-based discovery of potential biomarkers in human serum. Combined with the proposed bioinformatic approach (based on XCMS and NIST data elaboration) for the analysis of the MS spectra obtained, the potential for developing biomarkers with diagnostic capabilities are demonstrated in a prostate cancer diagnosis clinical setting.