iTRAQ identification of candidate serum biomarkers associated with metastatic progression of human prostate cancer

A major challenge in the management of patients with prostate cancer is identifying those individuals at risk of developing metastatic disease, as in most cases the disease will remain indolent. We analyzed pooled serum samples from 4 groups of patients (n = 5 samples/group), collected prospectively and actively monitored for a minimum of 5 yrs. Patients groups were (i) histological diagnosis of benign prostatic hyperplasia with no evidence of cancer 'BPH', (ii) localised cancer with no evidence of progression, 'non-progressing' (iii) localised cancer with evidence of biochemical progression, 'progressing', and (iv) bone metastasis at presentation 'metastatic'. Pooled samples were immuno-depleted of the 14 most highly abundant proteins and analysed using a 4-plex iTRAQ approach. Overall 122 proteins were identified and relatively quantified. Comparisons of progressing versus non-progressing groups identified the significant differential expression of 25 proteins (p<0.001). Comparisons of metastatic versus progressing groups identified the significant differential expression of 23 proteins. Mapping the differentially expressed proteins onto the prostate cancer progression pathway revealed the dysregulated expression of individual proteins, pairs of proteins and 'panels' of proteins to be associated with particular stages of disease development and progression. The median immunostaining intensity of eukaryotic translation elongation factor 1 alpha 1 (eEF1A1), one of the candidates identified, was significantly higher in osteoblasts in close proximity to metastatic tumour cells compared with osteoblasts in control bone (p = 0.0353, Mann Whitney U). Our proteomic approach has identified leads for potentially useful serum biomarkers associated with the metastatic progression of prostate cancer. The panels identified, including eEF1A1 warrant further investigation and validation.

Plasma biomarkers as predictors of outcome in patients with advanced hepatocellular carcinoma

Validated biomarkers of prognosis and response to drug have not been identified for patients with hepatocellular carcinoma (HCC). One of the objectives of the phase III, randomized, controlled Sorafenib HCC Assessment Randomized Protocol (SHARP) trial was to explore the ability of plasma biomarkers to predict prognosis and therapeutic efficacy.

Screening and testing for endocrine disruption in fish-biomarkers as "signposts," not "traffic lights," in risk assessment

Biomarkers are currently best used as mechanistic "signposts" rather than as "traffic lights" in the environmental risk assessment of endocrine-disrupting chemicals (EDCs). In field studies, biomarkers of exposure [e.g., vitellogenin (VTG) induction in male fish] are powerful tools for tracking single substances and mixtures of concern. Biomarkers also provide linkage between field and laboratory data, thereby playing an important role in directing the need for and design of fish chronic tests for EDCs. It is the adverse effect end points (e.g., altered development, growth, and/or reproduction) from such tests that are most valuable for calculating adverseNOEC (no observed effect concentration) or adverseEC10 (effective concentration for a 10% response) and subsequently deriving predicted no effect concentrations (PNECs). With current uncertainties, biomarkerNOEC or biomarkerEC10 data should not be used in isolation to derive PNECs. In the future, however, there may be scope to increasingly use biomarker data in environmental decision making, if plausible linkages can be made across levels of organization such that adverse outcomes might be envisaged relative to biomarker responses. For biomarkers to fulfil their potential, they should be mechanistically relevant and reproducible (as measured by interlaboratory comparisons of the same protocol). VTG is a good example of such a biomarker in that it provides an insight to the mode of action (estrogenicity) that is vital to fish reproductive health. Interlaboratory reproducibility data for VTG are also encouraging; recent comparisons (using the same immunoassay protocol) have provided coefficients of variation (CVs) of 38-55% (comparable to published CVs of 19-58% for fish survival and growth end points used in regulatory test guidelines). While concern over environmental xenoestrogens has led to the evaluation of reproductive biomarkers in fish, it must be remembered that many substances act via diverse mechanisms of action such that the environmental risk assessment for EDCs is a broad and complex issue. Also, biomarkers such as secondary sexual characteristics, gonadosomatic indices, plasma steroids, and gonadal histology have significant potential for guiding interspecies assessments of EDCs and designing fish chronic tests. To strengthen the utility of EDC biomarkers in fish, we need to establish a historical control database (also considering natural variability) to help differentiate between statistically detectable versus biologically significant responses. In conclusion, as research continues to develop a range of useful EDC biomarkers, environmental decision-making needs to move forward, and it is proposed that the "biomarkers as signposts" approach is a pragmatic way forward in the current risk assessment of EDCs.

Classification and selection of biomarkers in genomic data using LASSO

High-throughput gene expression technologies such as microarrays have been utilized in a variety of scientific applications. Most of the work has been on assessing univariate associations between gene expression with clinical outcome (variable selection) or on developing classification procedures with gene expression data (supervised learning). We consider a hybrid variable selection/classification approach that is based on linear combinations of the gene expression profiles that maximize an accuracy measure summarized using the receiver operating characteristic curve. Under a specific probability model, this leads to consideration of linear discriminant functions. We incorporate an automated variable selection approach using LASSO. An equivalence between LASSO estimation with support vector machines allows for model fitting using standard software. We apply the proposed method to simulated data as well as data from a recently published prostate cancer study.

Quantifying and Comparing the Accuracy of Binary Biomarkers When Predicting a Failure Time Outcome

The positive and negative predictive value are standard measures used to quantify the predictive accuracy of binary biomarkers when the outcome being predicted is also binary. When the biomarkers are instead being used to predict a failure time outcome, there is no standard way of quantifying predictive accuracy. We propose a natural extension of the traditional predictive values to accommodate censored survival data. We discuss not only quantifying predictive accuracy using these extended predictive values, but also rigorously comparing the accuracy of two biomarkers in terms of their predictive values. Using a marginal regression framework, we describe how to estimate differences in predictive accuracy and how to test whether the observed difference is statistically significant.

How reliable and robust are current biomarkers for copper status?

Cu is an essential nutrient for man, but can be toxic if intakes are too high. In sensitive populations, marginal over- or under-exposure can have detrimental effects. Malnourished children, the elderly, and pregnant or lactating females may be susceptible for Cu deficiency. Cu status and exposure in the population can currently not be easily measured, as neither plasma Cu nor plasma cuproenzymes reflect Cu status precisely. Some blood markers (such as ceruloplasmin) indicate severe Cu depletion, but do not inversely respond to Cu excess, and are not suitable to indicate marginal states. A biomarker of Cu is needed that is sensitive to small changes in Cu status, and that responds to Cu excess as well as deficiency. Such a marker will aid in monitoring Cu status in large populations, and will help to avoid chronic health effects (for example, liver damage in chronic toxicity, osteoporosis, loss of collagen stability, or increased susceptibility to infections in deficiency). The advent of high-throughput technologies has enabled us to screen for potential biomarkers in the whole proteome of a cell, not excluding markers that have no direct link to Cu. Further, this screening allows us to search for a whole group of proteins that, in combination, reflect Cu status. The present review emphasises the need to find sensitive biomarkers for Cu, examines potential markers of Cu status already available, and discusses methods to identify a novel suite of biomarkers.

Radiation metabolomics. 1. Identification of minimally invasive urine biomarkers for gamma-radiation exposure in mice

Gamma-radiation exposure has both short- and long-term adverse health effects. The threat of modern terrorism places human populations at risk for radiological exposures, yet current medical countermeasures to radiation exposure are limited. Here we describe metabolomics for gamma-radiation biodosimetry in a mouse model. Mice were gamma-irradiated at doses of 0, 3 and 8 Gy (2.57 Gy/min), and urine samples collected over the first 24 h after exposure were analyzed by ultra-performance liquid chromatography-time-of-flight mass spectrometry (UPLC-TOFMS). Multivariate data were analyzed by orthogonal partial least squares (OPLS). Both 3- and 8-Gy exposures yielded distinct urine metabolomic phenotypes. The top 22 ions for 3 and 8 Gy were analyzed further, including tandem mass spectrometric comparison with authentic standards, revealing that N-hexanoylglycine and beta-thymidine are urinary biomarkers of exposure to 3 and 8 Gy, 3-hydroxy-2-methylbenzoic acid 3-O-sulfate is elevated in urine of mice exposed to 3 but not 8 Gy, and taurine is elevated after 8 but not 3 Gy. Gene Expression Dynamics Inspector (GEDI) self-organizing maps showed clear dose-response relationships for subsets of the urine metabolome. This approach is useful for identifying mice exposed to gamma radiation and for developing metabolomic strategies for noninvasive radiation biodosimetry in humans.

Evaluating the potential of IP-10 and MCP-2 as biomarkers for the diagnosis of tuberculosis

The aim of the present study was to evaluate the potential of diagnostic tests based on interferon-gamma inducible protein (IP)-10 and monocyte chemotactic protein (MCP)-2, and compare the performance with the QuantiFERON TB Gold In-Tube (QFT-IT; Cellestis, Carnagie, Australia) test. IP-10 and MCP-2 were determined in supernatants from whole blood stimulated with Mycobacterium tuberculosis-specific antigens. Samples were obtained from 80 patients with culture- and/or PCR-proven tuberculosis (TB), and 124 unexposed healthy controls: 86 high school students and 38 high school staff. IP-10 and MCP-2 test cut-offs were established based on receiver operating characteristic curve analysis. TB patients produced significantly higher levels (median) of IP-10 (2158 pg x mL(-1)) and MCP-2 (379 pg x mL(-1)) compared with interferon (IFN)-gamma (215 pg x mL(-1)). The QFT-IT, IP-10 and MCP-2 tests detected 81, 83 and 71% of the TB patients; 0, 3 and 0% of the high school students and 0, 16 and 3% of the staff, respectively. Agreement between tests was high (>89%). By combining IP-10 and IFN-gamma tests, the detection rate increased among TB patients to 90% without a significant increase in positive responders among the students. In conclusion, interferon-gamma inducible protein-10 and monocyte chemotactic protein-2 responses to Mycobacterium tuberculosis-specific antigens could be used to diagnose infection. Combining interferon-gamma inducible protein-10 and interferon-gamma may be a simple approach to increase the detection rate of the Mycobacterium tuberculosis-specific in vitro tests.

Effects of gender and dementia severity on Alzheimer's disease caregivers' sleep and biomarkers of coagulation and inflammation

BACKGROUND: Being a caregiver for a spouse with Alzheimer's disease is associated with increased risk for cardiovascular illness, particularly for males. This study examined the effects of caregiver gender and severity of the spouse's dementia on sleep, coagulation, and inflammation in the caregiver. METHODS: Eighty-one male and female spousal caregivers and 41 non-caregivers participated (mean age of all participants 70.2 years). Full-night polysomnography (PSG) was recorded in each participants home. Severity of the Alzheimer's disease patient's dementia was determined by the Clinical Dementia Rating (CDR) scale. The Role Overload scale was completed as an assessment of caregiving stress. Blood was drawn to assess circulating levels of D-dimer and Interleukin-6 (IL-6). RESULTS: Male caregivers who were caring for a spouse with moderate to severe dementia spent significantly more time awake after sleep onset than female caregivers caring for spouses with moderate to severe dementia (p=.011), who spent a similar amount of time awake after sleep onset to caregivers of low dementia spouses and to non-caregivers. Similarly, male caregivers caring for spouses with worse dementia had significantly higher circulating levels of D-dimer (p=.034) than females caring for spouses with worse dementia. In multiple regression analysis (adjusted R(2)=.270, p<.001), elevated D-dimer levels were predicted by a combination of the CDR rating of the patient (p=.047) as well as greater time awake after sleep onset (p=.046). DISCUSSION: The findings suggest that males caring for spouses with more severe dementia experience more disturbed sleep and have greater coagulation, the latter being associated with the disturbed sleep. These findings may provide insight into why male caregivers of spouses with Alzheimer's disease are at increased risk for illness, particularly cardiovascular disease.

Simultaneous quantitative detection of relevant biomarkers in breast cancer by quantitative real-time PCR

The assessment of ERa, PgR and HER2 status is routinely performed today to determine the endocrine responsiveness of breast cancer samples. Such determination is usually accomplished by means of immunohistochemistry and in case of HER2 amplification by means of fluorescent in situ hybridization (FISH). The analysis of these markers can be improved by simultaneous measurements using quantitative real-time PCR (Qrt-PCR). In this study we compared Qrt-PCR results for the assessment of mRNA levels of ERa, PgR, and the members of the human epidermal growth factor receptor family, HER1, HER2, HER3 and HER4. The results were obtained in two independent laboratories using two different methods, SYBR Green I and TaqMan probes, and different primers. By linear regression we demonstrated a good concordance for all six markers. The quantitative mRNA expression levels of ERa, PgR and HER2 also strongly correlated with the respective quantitative protein expression levels prospectively detected by EIA in both laboratories. In addition, HER2 mRNA expression levels correlated well with gene amplification detected by FISH in the same biopsies. Our results indicate that both Qrt-PCR methods were robust and sensitive tools for routine diagnostics and consistent with standard methodologies. The developed simultaneous assessment of several biomarkers is fast and labor effective and allows optimization of the clinical decision-making process in breast cancer tissue and/or core biopsies.

Bone mineral density and circulating biomarkers in the BIG 1-98 trial comparing adjuvant letrozole, tamoxifen and their sequences.

The purpose of the study is to determine the effects of the BIG 1-98 treatments on bone mineral density. BIG 1-98 compared 5-year adjuvant hormone therapy in postmenopausal women allocated to four groups: tamoxifen (T); letrozole (L); 2-years T, 3-years L (TL); and 2-years L, 3-years T (LT). Bone mineral density T-score was measured prospectively annually by dual energy X-ray absorption in 424 patients enrolled in a sub-study after 3 (n = 150), 4 (n = 200), and 5 years (n = 74) from randomization, and 1 year after treatment cessation. Prevalence of osteoporosis and the association of C-telopeptide, osteocalcin, and bone alkaline phosphatase with T-scores were assessed. At 3 years, T had the highest and TL the lowest T-score. All arms except for LT showed a decline up to 5 years, with TL exhibiting the greatest. At 5 years, there were significant differences on lumbar T-score only between T and TL, whereas for femur T-score, differences were significant for T versus L or TL, and L versus LT. The 5-year prevalence of spine and femur osteoporosis was the highest on TL (14.5 %, 7.1 %) then L (4.3 %, 5.1 %), LT (4.2 %, 1.4 %) and T (4 %, 0). C-telopeptide and osteocalcin were significantly associated with T-scores. While adjuvant L increases bone mineral density loss compared with T, the sequence LT has an acceptable bone safety profile. C-telopeptide and osteocalcin are useful markers of bone density that may be used to monitor bone health during treatment. The sequence LT may be a valid treatment option in patients with low and intermediate risk of recurrence.

Changes in biomarkers of liver disease during successful combination antiretroviral therapy in HIV/HCV-coinfected individuals

Background: We investigated changes in biomarkers of liver disease in HIV–HCV-coinfected individuals during successful combination antiretroviral therapy (cART) compared to changes in biomarker levels during untreated HIV infection and to HIV-monoinfected individuals. Methods: Non-invasive biomarkers of liver disease (hyaluronic acid [HYA], aspartate aminotransferase-to-platelet ratio index [APRI], Fibrosis-4 [FIB-4] index and cytokeratin-18 [CK-18]) were correlated with liver histology in 49 HIV–HCV-coinfected patients. Changes in biomarkers over time were then assessed longitudinally in HIV–HCV-coinfected patients during successful cART (n=58), during untreated HIV-infection (n=59), and in HIV-monoinfected individuals (n=17). The median follow-up time was 3.4 years on cART. All analyses were conducted before starting HCV treatment. Results: Non-invasive biomarkers of liver disease correlated significantly with the histological METAVIR stage (P<0.002 for all comparisons). The mean ±sd area under the receiver operating characteristic (AUROC) curve values for advanced fibrosis (≥F3 METAVIR) for HYA, APRI, FIB-4 and CK-18 were 0.86 ±0.05, 0.84 ±0.08, 0.80 ±0.09 and 0.81 ±0.07, respectively. HYA, APRI and CK-18 levels were higher in HIV–HCV-coinfected compared to HIV-monoinfected patients (P<0.01). In the first year on cART, APRI and FIB-4 scores decreased (-35% and -33%, respectively; P=0.1), mainly due to the reversion of HIV-induced thrombocytopaenia, whereas HYA and CK-18 levels remained unchanged. During long-term cART, there were only small changes (<5%) in median biomarker levels. Median biomarker levels changed <3% during untreated HIV-infection. Overall, 3 patients died from end-stage liver disease, and 10 from other causes. Conclusions: Biomarkers of liver disease highly correlated with fibrosis in HIV–HCV-coinfected individuals and did not change significantly during successful cART. These findings suggest a slower than expected liver disease progression in many HIV–HCV-coinfected individuals, at least during successful cART.