Radiation metabolomics. 4. UPLC-ESI-QTOFMS-Based metabolomics for urinary biomarker discovery in gamma-irradiated rats

Radiation metabolomics has aided in the identification of a number of biomarkers in cells and mice by ultra-performance liquid chromatography-coupled time-of-flight mass spectrometry (UPLC-ESI-QTOFMS) and in rats by gas chromatography-coupled mass spectrometry (GCMS). These markers have been shown to be both dose- and time-dependent. Here UPLC-ESI-QTOFMS was used to analyze rat urine samples taken from 12 rats over 7 days; they were either sham-irradiated or γ-irradiated with 3 Gy after 4 days of metabolic cage acclimatization. Using multivariate data analysis, nine urinary biomarkers of γ radiation in rats were identified, including a novel mammalian metabolite, N-acetyltaurine. These upregulated urinary biomarkers were confirmed through tandem mass spectrometry and comparisons with authentic standards. They include thymidine, 2'-deoxyuridine, 2'deoxyxanthosine, N(1)-acetylspermidine, N-acetylglucosamine/galactosamine-6-sulfate, N-acetyltaurine, N-hexanoylglycine, taurine and, tentatively, isethionic acid. Of these metabolites, 2'-deoxyuridine and thymidine were previously identified in the rat by GCMS (observed as uridine and thymine) and in the mouse by UPLC-ESI-QTOFMS. 2'Deoxyxanthosine, taurine and N-hexanoylglycine were also seen in the mouse by UPLC-ESI-QTOFMS. These are now unequivocal cross-species biomarkers for ionizing radiation exposure. Downregulated biomarkers were shown to be related to food deprivation and starvation mechanisms. The UPLC-ESI-QTOFMS approach has aided in the advance for finding common biomarkers of ionizing radiation exposure.

Radiation metabolomics. 3. Biomarker discovery in the urine of gamma-irradiated rats using a simplified metabolomics protocol of gas chromatography-mass spectrometry combined with random forests machine learning algorithm

Abstract Radiation metabolomics employing mass spectral technologies represents a plausible means of high-throughput minimally invasive radiation biodosimetry. A simplified metabolomics protocol is described that employs ubiquitous gas chromatography-mass spectrometry and open source software including random forests machine learning algorithm to uncover latent biomarkers of 3 Gy gamma radiation in rats. Urine was collected from six male Wistar rats and six sham-irradiated controls for 7 days, 4 prior to irradiation and 3 after irradiation. Water and food consumption, urine volume, body weight, and sodium, potassium, calcium, chloride, phosphate and urea excretion showed major effects from exposure to gamma radiation. The metabolomics protocol uncovered several urinary metabolites that were significantly up-regulated (glyoxylate, threonate, thymine, uracil, p-cresol) and down-regulated (citrate, 2-oxoglutarate, adipate, pimelate, suberate, azelaate) as a result of radiation exposure. Thymine and uracil were shown to derive largely from thymidine and 2'-deoxyuridine, which are known radiation biomarkers in the mouse. The radiation metabolomic phenotype in rats appeared to derive from oxidative stress and effects on kidney function. Gas chromatography-mass spectrometry is a promising platform on which to develop the field of radiation metabolomics further and to assist in the design of instrumentation for use in detecting biological consequences of environmental radiation release.

Multiplex assays for biomarker research and clinical application: translational science coming of age

Over the last decade, translational science has come into the focus of academic medicine, and significant intellectual and financial efforts have been made to initiate a multitude of bench-to-bedside projects. The quest for suitable biomarkers that will significantly change clinical practice has become one of the biggest challenges in translational medicine. Quantitative measurement of proteins is a critical step in biomarker discovery. Assessing a large number of potential protein biomarkers in a statistically significant number of samples and controls still constitutes a major technical hurdle. Multiplexed analysis offers significant advantages regarding time, reagent cost, sample requirements and the amount of data that can be generated. The two contemporary approaches in multiplexed and quantitative biomarker validation, antibody-based immunoassays and MS-based multiple (or selected) reaction monitoring, are based on different assay principles and instrument requirements. Both approaches have their own advantages and disadvantages and therefore have complementary roles in the multi-staged biomarker verification and validation process. In this review, we discuss quantitative immunoassay and multiple reaction monitoring/selected reaction monitoring assay principles and development. We also discuss choosing an appropriate platform, judging the performance of assays, obtaining reliable, quantitative results for translational research and clinical applications in the biomarker field.

Informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography and high-resolution mass spectrometry (GCxGC-HRMS)

This paper describes informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography (GCxGC) and high-resolution mass spectrometry (HRMS). GCxGC-HRMS analysis produces large data sets that are rich with information, but highly complex. The size of the data and volume of information requires automated processing for comprehensive cross-sample analysis, but the complexity poses a challenge for developing robust methods. The approach developed here analyzes GCxGC-HRMS data from multiple samples to extract a feature template that comprehensively captures the pattern of peaks detected in the retention-times plane. Then, for each sample chromatogram, the template is geometrically transformed to align with the detected peak pattern and generate a set of feature measurements for cross-sample analyses such as sample classification and biomarker discovery. The approach avoids the intractable problem of comprehensive peak matching by using a few reliable peaks for alignment and peak-based retention-plane windows to define comprehensive features that can be reliably matched for cross-sample analysis. The informatics are demonstrated with a set of 18 samples from breast-cancer tumors, each from different individuals, six each for Grades 1-3. The features allow classification that matches grading by a cancer pathologist with 78% success in leave-one-out cross-validation experiments. The HRMS signatures of the features of interest can be examined for determining elemental compositions and identifying compounds.

Murine model of surgically induced acute aortic dissection type A

This study aimed at developing a murine model of surgically induced acute aortic dissection type A for investigation of the formation and progression of acute aortic dissection and to test whether this system could be used for biomarker discovery.

Cardiovascular proteomics: implications for clinical applications

Proteomics is fulfilling its potential and beginning to impact the diagnosis and therapy of cardiovascular disease. As de novo proteomics analysis gets more streamlined, and robust high-throughput methods are developed, more and more attention is being directed toward the field of cardiovascular serum and plasma biomarker discovery. To take cardiovascular proteomics from bench to bedside, great care must be taken to achieve reproducible results. Despite technical advances, however, the absolute number of clinical biomarkers thus far discovered by a proteomics approach is small. Although several factors contribute to this lack, one step is to build "translation teams" involving a close collaboration between researchers and clinicians.

Mining tissue microarray data to uncover combinations of biomarker expression patterns that improve intermediate staging and grading of clear cell renal cell cancer

PURPOSE: Tumor stage and nuclear grade are the most important prognostic parameters of clear cell renal cell carcinoma (ccRCC). The progression risk of ccRCC remains difficult to predict particularly for tumors with organ-confined stage and intermediate differentiation grade. Elucidating molecular pathways deregulated in ccRCC may point to novel prognostic parameters that facilitate planning of therapeutic approaches. EXPERIMENTAL DESIGN: Using tissue microarrays, expression patterns of 15 different proteins were evaluated in over 800 ccRCC patients to analyze pathways reported to be physiologically controlled by the tumor suppressors von Hippel-Lindau protein and phosphatase and tensin homologue (PTEN). Tumor staging and grading were improved by performing variable selection using Cox regression and a recursive bootstrap elimination scheme. RESULTS: Patients with pT2 and pT3 tumors that were p27 and CAIX positive had a better outcome than those with all remaining marker combinations. A prolonged survival among patients with intermediate grade (grade 2) correlated with both nuclear p27 and cytoplasmic PTEN expression, as well as with inactive, nonphosphorylated ribosomal protein S6. By applying graphical log-linear modeling for over 700 ccRCC for which the molecular parameters were available, only a weak conditional dependence existed between the expression of p27, PTEN, CAIX, and p-S6, suggesting that the dysregulation of several independent pathways are crucial for tumor progression. CONCLUSIONS: The use of recursive bootstrap elimination, as well as graphical log-linear modeling for comprehensive tissue microarray (TMA) data analysis allows the unraveling of complex molecular contexts and may improve predictive evaluations for patients with advanced renal cancer.

Inflammation as a psychophysiological biomarker in chronic psychosocial stress

The measurement of inflammation by biomarkers not only documents clinically relevant infections but also offers an important tool to pin point potentially harmful effects of chronic psychosocial stressors. This article focuses firstly on basic biology of inflammation and lists main biomarkers currently used in psycho-physiologic research. In the second part, the effects of the hypothalamic-pituitary-adrenal (HPA) axis and the autonomic nervous system as pathways modulating stress-related inflammation are discussed. Furthermore, current evidence of how chronic psychosocial stressors are related to alterations in inflammatory activity is presented. In summary, job stress, low socioeconomic status, childhood adversities as well as life events, caregiver stress, and loneliness were all shown to exert effects on immunologic activity.

Urinary soluble HLA-DR is a potential biomarker for acute renal transplant rejection

BACKGROUND.: Urine is a potentially rich source of biomarkers for monitoring kidney dysfunction. In this study, we have investigated the potential of soluble human leukocyte antigen (sHLA)-DR in the urine for noninvasive monitoring of renal transplant patients. METHODS.: Urinary soluble HLA-DR levels were measured by sandwich enzyme-linked immunosorbent assay in 103 patients with renal diseases or after renal transplantation. sHLA-DR in urine was characterized by Western blotting and mass spectrometry. RESULTS.: Acute graft rejection was associated with a significantly elevated level of urinary sHLA-DR (P<0.0001), compared with recipients with stable graft function or healthy individuals. A receiver operating characteristic curve analysis showed the area under the curve to be 0.88 (P<0.001). At a selected threshold, the sensitivity was 80% and specificity was 98% for detection of acute renal transplant rejection. sHLA-DR was not exosomally associated and was of lower molecular weight compared with the HLA-DR expressed as heterodimer on the plasma membrane of antigen-presenting cells. CONCLUSIONS.: sHLA-DR excreted into urine is a promising indicator of renal transplant rejection.

Natural products as leads for anticancer drug discovery: discovery of new chemotypes of microtubule stabilizers through reengineering of the epothilone scaffold

Epothilones are bacterial macrolides with potent microtubule-stabilizing and antiproliferative activity, which have served as successful lead structures for the discovery of several clinical candidates for cancer treatment. Overall, seven epothilone-type agents have been advanced to clinical evaluation in humans so far and one of these has been approved by the FDA in 2007 for clinical use in breast cancer patients. Notwithstanding these impressive numbers, however, the structural diversity represented by the collection of epothilone analogs that have been (or still are) investigated clinically is rather limited and their individual structures show little divergence from the original natural product leads. In contrast, we have elaborated a series of epothilone-derived macro-lactones, whose overall structural features significantly deviate from those of the natural epothilone scaffold and thus define new structural families of microtubule-stabilizing agents. Key elements of our hypermodification strategy are the change of the natural epoxide geometry from cis to trans, the incorporation of conformationally constrained side chains, the removal of the C(3)-hydroxyl group, and the replacement of C(12) with nitrogen. The latter modification leads to aza-macrolides that may be described as 'non-natural natural products'.

Saliva/pathogen biomarker signatures and periodontal disease progression

The purpose of this study was to determine the role of saliva-derived biomarkers and periodontal pathogens during periodontal disease progression (PDP). One hundred human participants were recruited into a 12-month investigation. They were seen bi-monthly for saliva and clinical measures and bi-annually for subtraction radiography, serum and plaque biofilm assessments. Saliva and serum were analyzed with protein arrays for 14 pro-inflammatory and bone turnover markers, while qPCR was used for detection of biofilm. A hierarchical clustering algorithm was used to group study participants based on clinical, microbiological, salivary/serum biomarkers, and PDP. Eighty-three individuals completed the six-month monitoring phase, with 39 [corrected] exhibiting PDP, while 44 [corrected] demonstrated stability. Participants assembled into three clusters based on periodontal pathogens, serum and salivary biomarkers. Cluster 1 members displayed high salivary biomarkers and biofilm; 71% [corrected] of these individuals were undergoing PDP. Cluster 2 members displayed low biofilm and biomarker levels; 76% [corrected] of these individuals were stable. Cluster 3 members were not discriminated by PDP status; however, cluster stratification followed groups 1 and 2 based on thresholds of salivary biomarkers and biofilm pathogens. The association of cluster membership to PDP was highly significant (p < 0.0007). [corrected] The use of salivary and biofilm biomarkers offers potential for the identification of PDP or stability (ClinicalTrials.gov number, CT00277745).

Phosphatidylethanol (PEth) as a Biomarker of Alcohol Consumption in HIV-Positive Patients in Sub-Saharan Africa

Background:  Alcohol is heavily consumed in sub-Saharan Africa and affects HIV transmission and treatment and is difficult to measure. Our goal was to examine the test characteristics of a direct metabolite of alcohol consumption, phosphatidylethanol (PEth). Methods:  Persons infected with HIV were recruited from a large HIV clinic in southwestern Uganda. We conducted surveys and breath alcohol concentration (BRAC) testing at 21 daily home or drinking establishment visits, and blood was collected on day 21 (n = 77). PEth in whole blood was compared with prior 7-, 14-, and 21-day alcohol consumption. Results:  (i) The receiver operator characteristic area under the curve (ROC-AUC) was highest for PEth versus any consumption over the prior 21 days (0.92; 95% confidence interval [CI]: 0.86 to 0.97). The sensitivity for any detectable PEth was 88.0% (95% CI: 76.0 to 95.6) and the specificity was 88.5% (95% CI: 69.8 to 97.6). (ii) The ROC-AUC of PEth versus any 21-day alcohol consumption did not vary with age, body mass index, CD4 cell count, hepatitis B virus infection, and antiretroviral therapy status, but was higher for men compared with women (p = 0.03). (iii) PEth measurements were correlated with several measures of alcohol consumption, including number of drinking days in the prior 21 days (Spearman r = 0.74, p < 0.001) and BRAC (r = 0.75, p < 0.001). Conclusions:  The data add support to the body of evidence for PEth as a useful marker of alcohol consumption with high ROC-AUC, sensitivity, and specificity. Future studies should further address the period and level of alcohol consumption for which PEth is detectable.

Two patterns of adipokine and other biomarker dynamics in a long-term weight loss intervention

Long-term dietary intervention frequently induces a rapid weight decline followed by weight stabilization/regain. Here, we sought to identify adipokine biomarkers that may reflect continued beneficial effects of dieting despite partial weight regain.