TMAX – a Database System Integrating Tissue Biomarker & Genomic Data

Background: Popular approaches in human tissue-based biomarker discovery include tissue microarrays (TMAs) and DNA Microarrays (DMAs) for protein and gene expression profiling respectively. The data generated by these analytic platforms, together with associated image, clinical and pathological data currently reside on widely different information platforms, making searching and cross-platform analysis difficult. Consequently, there is a strong need to develop a single coherent database capable of correlating all available data types.

Method: This study presents TMAX, a database system to facilitate biomarker discovery tasks. TMAX organises a variety of biomarker discovery-related data into the database. Both TMA and DMA experimental data are integrated in TMAX and connected through common DNA/protein biomarkers. Patient clinical data (including tissue pathological data), computer assisted tissue image and associated analytic data are also included in TMAX to enable the truly high throughput processing of ultra-large digital slides for both TMAs and whole slide tissue digital slides. A comprehensive web front-end was built with embedded XML parser software and predefined SQL queries to enable rapid data exchange in the form of standard XML files.

Results & Conclusion: TMAX represents one of the first attempts to integrate TMA data with public gene expression experiment data. Experiments suggest that TMAX is robust in managing large quantities of data from different sources (clinical, TMA, DMA and image analysis). Its web front-end is user friendly, easy to use, and most importantly allows the rapid and easy data exchange of biomarker discovery related data. In conclusion, TMAX is a robust biomarker discovery data repository and research tool, which opens up the opportunities for biomarker discovery and further integromics research.

Collectives of diagnostic biomarkers identify high-risk subpopulations of hematuria patients: exploiting heterogeneity in large-scale biomarker data

Background: Ineffective risk stratification can delay diagnosis of serious disease in patients with hematuria. We applied a systems biology approach to analyze clinical, demographic and biomarker measurements (n = 29) collected from 157 hematuric patients: 80 urothelial cancer (UC) and 77 controls with confounding pathologies.

Methods: On the basis of biomarkers, we conducted agglomerative hierarchical clustering to identify patient and biomarker clusters. We then explored the relationship between the patient clusters and clinical characteristics using Chi-square analyses. We determined classification errors and areas under the receiver operating curve of Random Forest Classifiers (RFC) for patient subpopulations using the biomarker clusters to reduce the dimensionality of the data.

Results: Agglomerative clustering identified five patient clusters and seven biomarker clusters. Final diagnoses categories were non-randomly distributed across the five patient clusters. In addition, two of the patient clusters were enriched with patients with ‘low cancer-risk’ characteristics. The biomarkers which contributed to the diagnostic classifiers for these two patient clusters were similar. In contrast, three of the patient clusters were significantly enriched with patients harboring ‘high cancer-risk” characteristics including proteinuria, aggressive pathological stage and grade, and malignant cytology. Patients in these three clusters included controls, that is, patients with other serious disease and patients with cancers other than UC. Biomarkers which contributed to the diagnostic classifiers for the largest ‘high cancer- risk’ cluster were different than those contributing to the classifiers for the ‘low cancer-risk’ clusters. Biomarkers which contributed to subpopulations that were split according to smoking status, gender and medication were different.

Conclusions: The systems biology approach applied in this study allowed the hematuric patients to cluster naturally on the basis of the heterogeneity within their biomarker data, into five distinct risk subpopulations. Our findings highlight an approach with the promise to unlock the potential of biomarkers. This will be especially valuable in the field of diagnostic bladder cancer where biomarkers are urgently required. Clinicians could interpret risk classification scores in the context of clinical parameters at the time of triage. This could reduce cystoscopies and enable priority diagnosis of aggressive diseases, leading to improved patient outcomes at reduced costs. © 2013 Emmert-Streib et al; licensee BioMed Central Ltd.

Standardization of diagnostic biomarker concentrations in urine; the hematuria caveat

Sensitive and specific urinary biomarkers can improve patient outcomes in many diseases through informing early diagnosis. Unfortunately, to date, the accuracy and translation of diagnostic urinary biomarkers into clinical practice has been disappointing. We believe this may be due to inappropriate standardization of diagnostic urinary biomarkers. Our objective was therefore to characterize the effects of standardizing urinary levels of IL-6, IL-8, and VEGF using the commonly applied standards namely urinary creatinine, osmolarity and protein. First, we report results based on the biomarker levels measured in 120 hematuric patients, 80 with pathologically confirmed bladder cancer, 27 with confounding pathologies and 13 in whom no underlying cause for their hematuria was identified, designated “no diagnosis”. Protein levels were related to final diagnostic categories (p = 0.022, ANOVA). Osmolarity (mean = 529 mOsm; median = 528 mOsm) was normally distributed, while creatinine (mean = 10163 µmol/l, median = 9350 µmol/l) and protein (0.3297, 0.1155 mg/ml) distributions were not. When we compared AUROCs for IL-6, IL-8 and VEGF levels, we found that protein standardized levels consistently resulted in the lowest AUROCs. The latter suggests that protein standardization attenuates the “true” differences in biomarker levels across controls and bladder cancer samples. Second, in 72 hematuric patients; 48 bladder cancer and 24 controls, in whom urine samples had been collected on recruitment and at follow-up (median = 11 (1 to 20 months)), we demonstrate that protein levels were approximately 24% lower at follow-up (Bland Altman plots). There was an association between differences in individual biomarkers and differences in protein levels over time, particularly in control patients.

Fumonisin B-1 as a Urinary Biomarker of Exposure in a Maize Intervention Study Among South African Subsistence Farmers

Background: The consumption of maize highly contaminated with carcinogenic fumonisins has been linked to high oesophageal cancer rates. The aim of this study was to validate a urinary fumonisin B-1 (UFB1) biomarker as a measure of fumonisin exposure and to investigate the reduction in exposure following a simple and culturally acceptable intervention.

Methods: At baseline home-grown maize, maize-based porridge, and first-void urine samples were collected from female participants (n = 22), following their traditional food practices in Centane, South Africa. During intervention the participants were trained to recognize and remove visibly infected kernels, and to wash the remaining kernels. Participants consumed the porridge prepared from the sorted and washed maize on each day of the two-day intervention. Porridge, maize, and urine samples were collected for FB1 analyses.

Results: The geometric mean (95% confidence interval) for FB1 exposure based on porridge (dry weight) consumption at baseline and following intervention was 4.84 (2.87-8.14) and 1.87 (1.40-2.51) mg FB1/kg body weight/day, respectively, (62% reduction, P < 0.05). UFB1C, UFB1 normalized for creatinine, was reduced from 470 (295-750) at baseline to 279 (202-386) pg/mg creatinine following intervention (41% reduction, P = 0.06). The UFB1C biomarker was positively correlated with FB1 intake at the individual level (r - 0.4972, P < 0.01). Urinary excretion of FB1 was estimated to be 0.075% (0.054%-0.104%) of the FB1 intake.

Conclusion: UFB1 reflects individual FB1 exposure and thus represents a valuable biomarker for future fumonisin risk assessment.

Impact: The simple intervention method, hand sorting and washing, could positively impact on food safety and health in communities exposed to fumonisins. Cancer Epidemiol Biomarkers Prev; 20(3); 483-9. (C)2011 AACR.

Study of aflatoxin exposure in a Brazilian population using an aflatoxin - albumin biomarker

The evaluation of exposure to aflatoxins (AF) by measurement of the level of contamination in food is hampered due to the heterogeneous distribution of AF in food. Therefore, an alternative is to estimate the exposure using specific biological markers (biomarkers) based on an understanding of the metabolism of the compound. For AF, these include aflatoxin-N-7-guanine in the urine, or AFB(1)-albumin (AF-alb) in the blood. This study assessed the level of exposure to AF in Brazilian individuals using a biomarker approach, i.e. the AF-alb adducts. Blood samples were collected from urban residents (n=50; aged 18-52) in June 1999, at the Blood Center of Antonio Carlos de Camargo Hospital, Sao Paulo, Brazil. AF-alb adduct levels were determined, by ELISA following serum albumin extraction and digestion. AF-alb adducts were detected in 31/50 (62%) samples [range 0-57.3 pg AFB(1)-lys adducts/mg of blood albumin (pg/mg)]. The mean level of positives was 14.9 pg/mg and males had the two highest levels measured (57.1 and 57.3 pg/mg). There was no correlation with age or profession. This is the first study of Brazilian, or indeed South American, individuals that has determined exposure to AF at the individual level using a biomarker approach. These levels are similar to those observed in the Philippines. These data warrant further investigation of both the sources and consequences of exposure to this potent toxin in Brazil.

Biomonitoring aquatic environmental quality in a marine protected area: A biomarker approach

The main aims of the present study, conducted in the framework of the MONIQUA-Egadi Scientific Project, were twofold: first, to make the first step in the development and validation of an ecotoxicological approach for the assessment of marine pollution in coastal environments on the basis of a set of biomarker responses in new sentinel species; and second, to obtain preliminary information on environmental quality in an Italian marine protected area, the Egadi Islands (Sicily). Several cytochrome P450-dependent mixed-function oxidase activities were measured in the following sentinel species: rainbow wrasse Coris julis, gastropod limpet Patella caerulea, and sea urchin Paracentrotus lividus. The results suggest that specimens from the Favignana Harbor may be exposed to P450 inducers, whereas most of the other sites seem to share similar environmental quality. The proposed approach has potential for assessment of environmental quality in marine protected areas.

Homogenous growth of gold nanocrystals for quantification of PSA protein biomarker

We report on another alternative sensing platform for the detection of protein biomarker (PSA–ACT complex) based on homogenous growth of Au nanocrystals in solution phase. The immuno-recognition event is translated into the gold nanoparticle growth signal which can be intuitively recognized by an unaided eye, or quantitatively measured by an UV–vis spectrophotometric analysis. Surface plasmonic signature and kinetics of the Au nanogrowth in the homogenous phase containing of HAuCl4, AA, and CTAB have also been studied to provide suitable parameters for the immunoassay. As a result, detection limit of PSA–ACT complex was determined to be 10 fM. The result indicated that this is a very sensitive, robust, simple, and economic strategy to detect protein biomarkers, and it has great potential to detect other biological interactions.

The ultrasensitive detection of prostate cancer biomarker based on resonant Rayleigh light-scattering response of single Au nanoparticle

A proof-of-concept study was reported on analysis of antigen-antibody recognition based on resonant Rayleigh scattering response of single Au nanoparticles on a microimaging chamber. As benefited by a traditional dark-field microscope and a spectrograph, tiny 30 nm Au nanoparticles were effectively used as nanosensors to monitor changes in refractive index induced by every single binding of the adsorbates. The individual Au nanoparticles were observed with very high signal-to-noise ratio, and a LSPR ?max shift of about 2.5 nm accounting for the detection of PSA antigen with concentration as low as 0.1 pg ml-1 was recorded. This resulted in the successful demonstration of a non-labelling detection system for proteins as well as thousands of different chemical or biological species with possibility of miniaturization and multiplexing scheme.

Carboxymethylethanolamine, a biomarker of phospholipid modification during the maillard reaction in vivo

Nepsilon-(Carboxymethyl)lysine (CML) is a stable chemical modification of proteins formed from both carbohydrates and lipids during autoxidation reactions. We hypothesized that carboxymethyl lipids such as (carboxymethyl)phosphatidylethanolamine (carboxymethyl-PE) would also be formed in these reactions, and we therefore developed a gas chromatography-mass spectrometry assay for quantification of carboxymethylethanolamine (CME) following hydrolysis of phospholipids. In vitro, CME was formed during glycation of dioleoyl-PE under air and from linoleoylpalmitoyl-PE, but not from dioleoyl-PE, in the absence of glucose. In vivo, CME was detected in lipid extracts of red blood cell membranes, approximately 0.14 mmol of CME/mol of ethanolamine, from control and diabetic subjects, (n = 22, p > 0.5). Levels of CML in erythrocyte membrane proteins were approximately 0.2 mmol/mol of lysine for both control and diabetic subjects (p > 0.5). For this group of diabetic subjects there was no indication of increased oxidative modification of either lipid or protein components of red cell membranes. CME was also detected in fasting urine at 2-3 nmol/mg of creatinine in control and diabetic subjects (p = 0.085). CME inhibited detection of advanced glycation end product (AGE)-modified protein in a competitive enzyme-linked immunosorbent assay using an anti-AGE antibody previously shown to recognize CML, suggesting that carboxymethyl-PE may be a component of AGE lipids detected in AGE low density lipoprotein. Measurement of levels of CME in blood, tissues, and urine should be useful for assessing oxidative damage to membrane lipids during aging and in disease.

Lipoxidation products as biomarkers of oxidative damage to proteins during lipid peroxidation reactions

Oxidative stress is implicated in the pathogenesis of numerous disease processes including diabetes mellitus, atherosclerosis, ischaemia reperfusion injury and rheumatoid arthritis. Chemical modification of amino acids in protein during lipid peroxidation results in the formation of lipoxidation products which may serve as indicators of oxidative stress in vivo. The focus of the studies described here was initially to identify chemical modifications of protein derived exclusively from lipids in order to assess the role of lipid peroxidative damage in the pathogenesis of disease. Malondialdehye (MDA) and 4-hydroxynonenal (HNE) are well characterized oxidation products of polyunsaturated fatty acids on low-density lipoprotein (LDL) and adducts of these compounds have been detected by immunological means in atherosclerotic plaque. Thus, we first developed gas chromatography-mass spectrometry assays for the Schiff base adduct of MDA to lysine, the lysine-MDA-lysine diimine cross-link and the Michael addition product of HNE to lysine. Using these assays, we showed that the concentrations of all three compounds increased significantly in LDL during metal-catalysed oxidation in vitro. The concentration of the advanced glycation end-product N epsilon-(carboxymethyl)lysine (CML) also increased during LDL oxidation, while that of its putative carbohydrate precursor the Amadori compound N epsilon-(1-deoxyfructose-1-yl)lysine did not change, demonstrating that CML is a marker of both glycoxidation and lipoxidation reactions. These results suggest that MDA and HNE adducts to lysine residues should serve as biomarkers of lipid modification resulting from lipid peroxidation reactions, while CML may serve as a biomarker of general oxidative stress resulting from both carbohydrate and lipid oxidation reactions.