Distribution and quantification of irinotecan and its active metabolite SN-38 in colon cancer murine model systems using MALDI MSI.

Tissue distribution and quantitative analysis of small molecules is a key to assess the mechanism of drug action and evaluate treatment efficacy. The prodrug irinotecan (CPT-11) is widely used for chemotherapeutic treatment of colorectal cancer. CPT-11 requires conversion into its active metabolite SN-38 to exert the desired pharmacological effect. MALDI-Fourier transform ion cyclotron resonance (FT-ICR) and MALDI-time-of-flight (TOF) mass spectrometry imaging (MSI) were performed for detection of CPT-11 and SN-38 in tissue sections from mice post CPT-11 injection. In-depth information was gained about the distribution and quantity of drug compounds in normal and tumor tissue. The prodrug was metabolized, as proven by the detection of SN-38 in liver, kidney and digestive tract. In tumors from genetic mouse models for colorectal cancer (Apc (1638N/wt) x pvillin-Kras (V12G) ), CPT-11 was detected but not the active metabolite. In order to correlate drug distribution relative to vascularization, MALDI data were superimposed with CD31 (PECAM-1) immunohistochemistry. This analysis indicated that intratumoral access of CPT-11 mainly occurred by extravasation from microvessels. The present study exploits the power of MALDI MSI in drug analysis, and presents a novel approach to monitor drug distribution in relation to vessel functionality in preclinical and clinical research.

Human breath gas analysis in the screening of gestational diabetes mellitus.

BACKGROUND: We present a pilot study on the feasibility of the application and advantages of online, noninvasive breath gas analysis (BGA) by proton transfer reaction quadrupole mass spectrometry for the screening of gestational diabetes mellitus (GDM) in 52 pregnant women by means of an oral glucose tolerance test (OGTT). SUBJECTS AND METHODS: We collected and identified samples of end-tidal breath gas from patients during OGTT. Time evolution parameters of challenge-responsive volatile organic compounds (VOCs) in human breath gas were estimated. Multivariate analysis of variance and permutation analysis were used to assess feasibility of BGA as a diagnostic tool for GDM. RESULTS: Standard OGTT diagnosis identified pregnant women as having GDM (n = 8), impaired glucose tolerance (n = 12), and normal glucose tolerance (n = 32); a part of this latter group was further subdivided into a "marginal" group (n = 9) because of a marginal high 1-h or 2-h OGTT value. We observed that OGTT diagnosis (four metabolic groups) could be mapped into breath gas data. The time evolution of oxidation products of glucose and lipids, acetone metabolites, and thiols in breath gas after a glucose challenge was correlated with GDM diagnosis (P = 0.035). Furthermore, basal (fasting) values of dimethyl sulfide and values of methanol in breath gas were inversely correlated with phenotype characteristics such as homeostasis model assessment of insulin resistance index (R = -0.538; P = 0.0002, P(corrected) = 0.0034) and pregestational body mass index (R = -0.433; P = 0.0013, P(corrected) = 0.022). CONCLUSIONS: Noninvasive BGA in challenge response studies was successfully applied to GDM diagnosis and offered an insight into metabolic pathways involved. We propose a new approach to the identification of diagnosis thresholds for GDM screening.