Jörg Ingo Baumbach

Role of thioredoxin reductase 1 and thioredoxin interacting protein in prognosis of breast cancer

IntroductionThe purpose of this work was to study the prognostic influence in breast cancer of thioredoxin reductase 1 (TXNRD1) and thioredoxin interacting protein (TXNIP), key players in oxidative stress control that are currently evaluated as possible therapeutic targets.MethodsAnalysis of the association of TXNRD1 and TXNIP RNA expression with the metastasis-free interval (MFI) was performed in 788 patients with node-negative breast cancer, consisting of three individual cohorts (Mainz, Rotterdam and Transbig). Correlation with metagenes and conventional clinical parameters (age, pT stage, grading, hormone and ERBB2 status) was explored. MCF-7 cells with a doxycycline-inducible expression of an oncogenic ERBB2 were used to investigate the influence of ERBB2 on TXNRD1 and TXNIP transcription.ResultsTXNRD1 was associated with worse MFI in the combined cohort (hazard ratio = 1.955; P < 0.001) as well as in all three individual cohorts. In contrast, TXNIP was associated with better prognosis (hazard ratio = 0.642; P < 0.001) and similar results were obtained in all three subcohorts. Interestingly, patients with ERBB2-status-positive tumors expressed higher levels of TXNRD1. Induction of ERBB2 in MCF-7 cells caused not only an immediate increase in TXNRD1 but also a strong decrease in TXNIP. A subsequent upregulation of TXNIP as cells undergo senescence was accompanied by a strong increase in levels of reactive oxygen species.ConclusionsTXNRD1 and TXNIP are associated with prognosis in breast cancer, and ERBB2 seems to be one of the factors shifting balances of both factors of the redox control system in a prognostic unfavorable manner.

Ion mobility spectrometry coupled with multi-capillary columns for metabolic profiling of human breath.

Recently, ion mobility spectrometry (IMS) started to be used for direct breath analysis with respect to metabolic profiling, biomarker finding and gas trace analysis. The present review describes the basic operation of an ion mobility spectrometer including the ionization process, humidity effects and sampling procedures. To enhance the resolution, pre-separation by multi-capillary columns (MCCs) is discussed and examples for IMS chromatograms are presented. The focus is to review the analytical method IMS with respect to potential use for direct investigations of humid air in direct breath analysis but not on detailed discussion of results of specific medical application of MCC/IMS or on specific analytes found in exhaled air.

Ion mobility spectrometry for food quality and safety

Ion mobility spectrometry is known to be a fast and sensitive technique for the detection of trace substances, and it is increasingly in demand not only for protection against explosives and chemical warfare agents, but also for new applications in medical diagnosis or process control. Generally, a gas phase sample is ionized by help of ultraviolet light, ß-radiation or partial discharges. The ions move in a weak electrical field towards a detector. During their drift they collide with a drift gas flowing in the opposite direction and, therefore, are slowed down depending on their size, shape and charge. As a result, different ions reach the detector at different drift times, which are characteristic for the ions considered. The number of ions reaching the detector are a measure of the concentration of the analyte. The method enables the identification and quantification of analytes with high sensitivity (ng l−1 range). The selectivity can even be increased — as necessary for the analyses of complex mixtures — using pre-separation techniques such as gas chromatography or multi-capillary columns. No pre-concentration of the sample is necessary. Those characteristics of the method are preserved even in air with up to a 100% relative humidity rate. The suitability of the method for application in the field of food quality and safety — including storage, process and quality control as well as the characterization of food stuffs — was investigated in recent years for a number of representative examples, which are summarized in the following, including new studies as well: (1) the detection of metabolites from bacteria for the identification and control of their growth; (2) process control in food production — beer fermentation being an example; (3) the detection of the metabolites of mould for process control during cheese production, for quality control of raw materials or for the control of storage conditions; (4) the quality control of packaging materials during the production of polymeric materials; and (5) the characterization of products — wine being an example. The challenges of such applications were operation in humid air, fast on-line analyses of complex mixtures, high sensitivity — detection limits have to be, for example, in the range of the odour limits — and, in some cases, the necessity of mobile instrumentation. It can be shown that ion mobility spectrometry is optimally capable of fulfilling those challenges for many applications.

Detection of volatile metabolites of Escherichia coli by multi capillary column coupled ion mobility spectrometry

Detection and immediate quantification of microbial metabolic activities is of high interest in fields as diverse as biotechnology and infection biology. Interestingly, the most direct signals of microbial metabolism, the evolution of volatile metabolites, is largely ignored in the literature, and rather, metabolite concentrations in the microbial surrounding or even disruptive methods for intracellular metabolite measurements (i.e., metabolome analysis) are favored. Here, the development of a multi capillary column coupled ion mobility spectrometer (MCC-IMS) was described for the detection of volatile organic compounds from microbes and the MCC-IMS was used for characterization of metabolic activity of growing Escherichia coli. The MCC-IMS chromatogram of the microbial culture off-gas of the acetone-producing E. coli strain BL21 pLB4 revealed four analytes that positively correlated with growth, which were identified as ethanol, propanone (acetone), heptan-2-one, and nonan-2-one. The occurrence of these analytes was cross-validated by solid-phase micro-extraction coupled with gas chromatography mass spectrometry analysis. With this information in hand, the dynamic relationship between the E. coli biomass concentration and the metabolite concentrations in the headspace was measured. The results suggest that the metabolic pathways of heptan-2-one and nonan-2-one synthesis are regulated independent of each other. It is shown that the MCC-IMS in-line off-gas analysis is a simple method for real-time detection of microbial metabolic activity and discussed its potential for application in metabolic engineering, bioprocess control, and health care.

Peak assignment in multi-capillary column–ion mobility spectrometry using comparative studies with gas chromatography–mass spectrometry for VOC analysis

Over the past years, ion mobility spectrometry (IMS) as a well established method within the fields of military and security has gained more and more interest for biological and medical applications. This highly sensitive and rapid separation technique was crucially enhanced by a multi-capillary column (MCC), pre-separation for complex samples. In order to unambiguously identify compounds in a complex sample, like breath, by IMS, a reference database is mandatory. To obtain a first set of reference data, 16 selected volatile organic substances were examined by MCC-IMS and comparatively analyzed by the standard technique for breath research, thermal desorption–gas chromatography–mass spectrometry. Experimentally determined MCC and GC retention times of these 16 compounds were aligned and their relation was expressed in a mathematical function. Using this function, a prognosis of the GC retention time can be given very precisely according to a recorded MCC retention time and vice versa. Thus, unknown MCC-IMS peaks from biological samples can be assigned—after alignment via the estimated GC retention time—to analytes identified by GC/MS from equivalent accomplished data. One example of applying the peak assignment strategy to a real breath sample is shown in detail.

Breath analysis—performance and potential of ion mobility spectrometry

Ion mobility spectrometry is a fast and sensitive analytical method for the detection of gas phase analytes in the ppb(v)-ppt(v) range under ambient conditions (pressure and temperature). Ion mobility spectrometers coupled with rapid pre-separation like multi-capillary columns (MCC/IMS) are suitable for the selective characterization of complex and humid mixtures. Recently, MCC/IMS have been applied to analyses of human breath for early diagnosis as well as medication and therapy control. The complete procedure of breath analyses including evaluation and interpretation of the data obtained is demonstrated for the first time on exhaled breath after the consumption of a particular candy as an example. An MCC/IMS equipped with a β-radiation source ((63)Ni) requires 5 to 10 min for a complete analysis of exhaled breath. Retention time and reduced ion mobility of the detected signals are compared to an analyte database for the identification of the related analytes. These findings were successfully validated by gas-chromatographic mass spectroscopy of the headspace of the candy via solid-phase micro-extraction and of breath samples on Tenax adsorption tubes. Furthermore, signal height of particular analyte signals as a measure for their concentration was used to monitor the concentration development with time. This exemplary investigation demonstrates that MCC/IMS is a powerful and rapid non-invasive tool for human breath analyses. The method can be used for medical applications (diagnosis, therapy control, metabolic profiling) as well as for a general determination of the metabolic state of a subject (medication, nutrition, fasting). The demonstrated procedure is independent of whether the analytes detected in breath are caused by nutrition or medication or whether they are metabolite characteristics for a particular disease. Therefore, it can directly be transferred to any relevant peak pattern.

Determination of volatile products of human colon cell line metabolism by GC/MS analysis

Colon cancer is one of the most reasons for cancer death worldwide. Thus, it is important to find new prognostic and diagnostic marker, as well as to throw light on the special metabolic pathways of colon cancer cells. This paper highlights for the first time some qualitative differences in the profiles of the volatile metabolites of colon cancer cell lines SW 480 (grade IV, Duke B) and SW 1116 (grade II, Duke A) among themselves and in comparison to the normal colon cell line NCM460, which are mostly represented by ketones and alcohols. These results, which were obtained by applying solid phase micro extraction (SPME) and combined gas chromatography/mass spectrometry (GC/MS), are consistent with Warburg’s hypothesis because the found reaction products may indicate that the cancer cells show the Crabtree’s effect. Furthermore, compounds like undecan-2-ol and pentadecan-2-one were associated for the first time with the human metabolism. In summary, these findings indicate that the metabolism of colon cancer cells differs extremely from the metabolism of healthy cells and it changes during the progress of the disease. Compounds that are present in the breath, the blood and the tissue of patients represent the differences and they can serve as new biomarker for colon cancer in future.

Glycerophospholipid profiling by high‐performance liquid chromatography/mass spectrometry using exact mass measurements and multi‐stage mass spectrometric fragmentation experiments in parallel

A profiling method for glycerophospholipids (GPs) in biological samples was developed using reversed-phase high-performance liquid chromatography (RP-HPLC) coupled to hybrid linear ion trap-Fourier transform ion cyclotron resonance mass spectrometry (LIT-FTICRMS) with electrospray ionization (ESI) in the negative ionization mode. The method allowed qualitative (identification and structure elucidation) and relative quantitative determination of various classes of GPs including phosphatidylcholines, phosphatidylethanolamines, phosphatidylinositols, phosphatidylserines, phosphatidic acids, phosphatidylglycerols, and cardiolipins in a single experiment. Chromatographic separation was optimized by the examination of different buffer systems and special emphasis was paid on the detection by ESI-MS. The hybrid LIT-FTICRMS system was operated in the data-dependent mode, switching automatically between FTICRMS survey scans and LIT-MS/MS experiments. Thereby, exact masses for elemental composition determination and fragmentation data for identification and assignment of fatty acid residues are provided at the same time. The low absolute instrumental limits of detection (0.05 pmol for phosphatidylglycerol to 1 pmol for phosphatidic acid) complemented by a linear dynamic range of 1.5 to 2.5 orders of magnitude facilitated the relative quantification of GP species in a lipid extract from Saccharomyces cerevisiae. The developed method is a valuable tool for in-depth GP profiling of biological systems.

MCC/IMS signals in human breath related to sarcoidosis?results of a feasibility study using an automated peak finding procedure

A feasibility study using an ion mobility spectrometer coupled with a multi-capillary column (MCC) was started to identify characteristic peaks of volatile compounds in exhaled human breath samples of 10 ml volume. The breath of 20 patients with sarcoidosis and suspicion of sarcoidosis because of mediastinal lymph node enlargement was investigated. Using a set of procedures for data processing and scoring a sector of interest was determined within the IMS-chromatogram. It could be shown that a procedure related to a single peak in the IMS-chromatogram delivers differentiation into the two groups of patients with confirmed sarcoidosis and those suffering no sarcoidosis. The potential biomarker is characterized by the following parameters: inverse mobility (1/K(0)) 0.53 ± 0.01 V s cm(-2)-retention time 22 ± 5 s. These results are a first step in breath analysis by MCC/IMS in patients with sarcoidosis by an automated procedure applied to IMS-chromatograms directly.

Integrated statistical learning of metabolic ion mobility spectrometry profiles for pulmonary disease identification.

Exhaled air carries information on human health status. Ion mobility spectrometers combined with a multi-capillary column (MCC/IMS) is a well-known technology for detecting volatile organic compounds (VOCs) within human breath. This technique is relatively inexpensive, robust and easy to use in every day practice. However, the potential of this methodology depends on successful application of computational approaches for finding relevant VOCs and classification of patients into disease-specific profile groups based on the detected VOCs. We developed an integrated state-of-the-art system using sophisticated statistical learning techniques for VOC-based feature selection and supervised classification into patient groups. We analyzed breath data from 84 volunteers, each of them either suffering from chronic obstructive pulmonary disease (COPD), or both COPD and bronchial carcinoma (COPD + BC), as well as from 35 healthy volunteers, comprising a control group (CG). We standardized and integrated several statistical learning methods to provide a broad overview of their potential for distinguishing the patient groups. We found that there is strong potential for separating MCC/IMS chromatograms of healthy controls and COPD patients (best accuracy COPD vs CG: 94%). However, further examination of the impact of bronchial carcinoma on COPD/no-COPD classification performance is necessary (best accuracy CG vs COPD vs COPD + BC: 79%). We also extracted 20 high-scoring VOCs that allowed differentiating COPD patients from healthy controls. We conclude that these statistical learning methods have a generally high accuracy when applied to well-structured, medical MCC/IMS data.