Highly selective and automated online SPE LC-MS3 method for determination of cortisol and cortisone in human hair as biomarker for stress related diseases.

Hair analysis has been increasingly used to establish long-term biomarkers of exposure to both endogenous and exogenous substances, with a special emphasis on steroidal hormones. Hair cortisol and cortisone have been associated to physiological and psychological strains, anxiety and depression. Hair is a very complex matrix, which might jeopardize analyte detection at low concentrations. A new, highly selective and sensitive method based on fragments of second order, MS(3) (MS/MS/MS), was developed and validated for the analysis of hair cortisol and cortisone. An online solid phase extraction was performed on a C8 restricted access material (RAM) phase following by separation on a reversed-phase C18 column using methanol and 0.02% ammonium hydroxide as mobile phase. The developed method required minimal sample preparation and the injection of only 50 µL of sample leading to a LOQ of 2 pg mg(-1). Good linear responses were observed in the range 2-200 pg mg(-1) (R(2)>0.99) and extraction recoveries ranged between 77-125% and 70-123% for cortisol and cortisone, respectively. Intra- and inter-assay coefficients of variation were between 1.4 and 14%. In order to evaluate the applicability of the method, preliminary tests (N=33) were conducted in 3 cm hair samples (close to scalp) of healthy volunteers with an age range of 4-63. Average concentrations in hair were 12.7±14 pg mg(-1) and 41.6±42 pg mg(-1) for cortisol and cortisone, respectively. Further investigations on cortisol and cortisone as biomarkers for chronic psychological strain will be assessed as a next step.

Identifying prostate carcinoma by MALDI-Imaging.

Prostate cancer has become one of the most common malignancies worldwide. Although lacking in specificity its diagnosis is still based partially on the serum-based test for prostate-specific antigen. As its pathogenesis has not yet been deciphered, the ongoing search for new and more reliable biomarkers remains a challenge to stratify disease onset and progression. Matrix-assisted laser desorption/ionization (MALDI)-Imaging is a promising technique to assist in this endeavor. It delivers accurate mass spectrometric information of the sample's proteins and enables the visualization of the spatial distribution of protein expression profiles and correlation of the information with the histomorphological features of the same tissue section. This study describes the analysis of 22 prostate sections (11 with and 11 without prostate cancer) by MALDI-Imaging. Specific protein expression patterns were obtained for normal and cancerous regions within the tissue sections. Applying a 'support vector machine' algorithm to classify the cancerous from the non-cancerous regions, an overall cross-validation, a sensitivity and specificity of 88, 85.21 and 90.74%, respectively, was achieved. Additionally four distinctively overexpressed peaks were identified: 2,753 and 6,704 Da for non-cancerous glands, and 4,964 and 5,002 Da for cancerous glands. The results of this first clinical study utilizing the new technique of MALDI-Imaging underline its vast potential to identify candidates for more reliable prostate cancer tumor markers and to enlighten the pathogenesis of prostate cancer.