Candidate serum biomarkers for prostate adenocarcinoma identified by mRNA differences in prostate tissue and verified with protein measurements in tissue and blood.

BACKGROUND: Improved tests are needed for detection and management of prostate cancer. We hypothesized that differential gene expression in prostate tissue could help identify candidate blood biomarkers for prostate cancer and that blood from men with advanced prostate disease could be used to verify the biomarkers presence in circulation. METHODS: We identified candidate markers using mRNA expression patterns from laser-capture microdissected prostate tissue and confirmed tissue expression using immunohistochemistry (IHC) for the subset of candidates having commercial antisera. We analyzed tissue extracts with tandem mass spectrometry (MS/MS) and measured blood concentrations using immunoassays and MS/MS of trypsin-digested, immunoextracted peptides. RESULTS: We selected 35 novel candidate prostate adenocarcinoma biomarkers. For all 13 markers having commercial antisera for IHC, tissue expression was confirmed; 6 showed statistical discrimination between nondiseased and malignant tissue, and only 5 were detected in tissue extracts by MS/MS. Sixteen of the 35 candidate markers were successfully assayed in blood. Four of 8 biomarkers measured by ELISA and 3 of 10 measured by targeted MS showed statistically significant increases in blood concentrations of advanced prostate cancer cases, compared with controls. CONCLUSIONS: Seven novel biomarkers identified by gene expression profiles in prostate tissue were shown to have statistically significant increased concentrations in blood from men with advanced prostate adenocarcinoma compared with controls: apolipoprotein C1, asporin, cartilage oligomeric matrix protein, chemokine (C-X-C motif) ligand 11 (CXCL11), CXCL9, coagulation factor V, and proprotein convertase subtilisin/kexin 6.

Development and Application of Mass Spectroscopy Assays for Nε-(1-Carboxymethyl)-L-Lysine and Pentosidine in Renal Failure and Diabetes.

BACKGROUND: Advanced glycation end products (AGEs) are formed via the nonenzymatic glycation of sugars with amino acids. Two AGEs, Nε-(1-carboxymethyl)-L-Lysine (CML) and pentosidine, have been observed to be elevated in subjects suffering from a multitude of chronic disease states, and accumulation of these compounds may be related to the pathophysiology of disease progression and aging. METHODS: We describe here the development and validation of a specific and reproducible LC-MS/MS method to quantify CML and pentosidine in human serum with lower limits of quantitation of 75 ng/mL and 5 ng/mL, respectively. The analyte calibration curve exhibited excellent linearity at a range of 0-10 900 ng/mL for CML and 0-800 ng/mL for pentosidine. High-low linearity of 5 serum pairs was assessed, with a mean recovery of 103% (range 94-116%) for CML, and 104% (range 97-116%) for pentosidine. RESULTS: Serum concentrations of CML and pentosidine were quantified in 30 control and 30 subjects with chronic renal insufficiency. A significant increase in both analytes was observed in renal failure compared to control subjects (2.1-fold and 8.4-fold, respectively; P < 0.001 for both). In a separate cohort of 49 control versus 95 subjects with type 2 diabetes mellitus (T2DM), serum CML but not serum pentosidine, was significantly elevated in the T2DM patients, and CML was also correlated with glycemic control, as assessed by hemoglobin A1c (r = 0.34, P < 0.001). CONCLUSIONS: These mass spectroscopy-based assays for serum CML and pentosidine should be useful in accurately evaluating circulating levels of these key AGEs in various disease states.

Accelerated osteocyte senescence and skeletal fragility in mice with type 2 diabetes.

The worldwide prevalence of type 2 diabetes (T2D) is increasing. Despite normal to higher bone density, patients with T2D paradoxically have elevated fracture risk resulting, in part, from poor bone quality. Advanced glycation endproducts (AGEs) and inflammation as a consequence of enhanced receptor for AGE (RAGE) signaling are hypothesized culprits, although the exact mechanisms underlying skeletal dysfunction in T2D are unclear. Lack of inducible models that permit environmental (in obesity) and temporal (after skeletal maturity) control of T2D onset has hampered progress. Here, we show in C57BL/6 mice that a onetime pharmacological intervention (streptozotocin, STZ) initiated in adulthood combined with high-fat diet-induced (HFD-induced) obesity caused hallmark features of human adult-onset T2D, including prolonged hyperglycemia, insulin resistance, and pancreatic ß cell dysfunction, but not complete destruction. In addition, HFD/STZ (i.e., T2D) resulted in several changes in bone quality that closely mirror those observed in humans, including compromised bone microarchitecture, reduced biomechanical strength, impaired bone material properties, altered bone turnover, and elevated levels of the AGE CML in bone and blood. Furthermore, T2D led to the premature accumulation of senescent osteocytes with a unique proinflammatory signature. These findings highlight the RAGE pathway and senescent cells as potential targets to treat diabetic skeletal fragility.

Interleukins 6 and 8 and abdominal fat depots are distinct correlates of lipid moieties in healthy pre- and postmenopausal women.

Available data associate lipids concentrations in men with body mass index, anabolic steroids, age, and certain cytokines. Data were less clear in women, especially across the full adult lifespan, and when segmented by premenopausal and postmenopausal status. SUBJECTS: 120 healthy women (60 premenopausal and 60 postmenopausal) in Olmsted County, MN, USA, a stable well studied clinical population. Dependent variables: measurements of 10 h fasting high-density lipoprotein cholesterol, total cholesterol, low-density lipoprotein cholesterol, and triglycerides. INDEPENDENT VARIABLES: testosterone, estrone, estradiol, 5-alpha-dihydrotestosterone, and sex-hormone binding globulin (by mass spectrometry); insulin, glucose, and albumin; abdominal visceral, subcutaneous, and total abdominal fat [abdominal visceral fat, subcutaneous fat, total abdominal fat by computerized tomography scan]; and a panel of cytokines (by enzyme-linked immunosorbent assay). Multivariate forward-selection linear-regression analysis was applied constrained to P < 0.01. Lifetime data: High-density lipoprotein cholesterol was correlated jointly with age (P < 0.0001, positively), abdominal visceral fat (P < 0.0001, negatively), and interleukin-6 (0.0063, negatively), together explaining 28.1 % of its variance (P = 2.3 × 10-8). Total cholesterol was associated positively with multivariate age only (P = 6.9 × 10-4, 9.3 % of variance). Triglycerides correlated weakly with sex-hormone binding globulin (P = 0.0115), and strongly with abdominal visceral fat (P < 0.0001), and interleukin-6 (P = 0.0016) all positively (P = 1.6 × 10-12, 38.9 % of variance). Non high-density lipoprotein cholesterol and low-density lipoprotein cholesterol correlated positively with both total abdominal fat and interleukin-8 (P = 2.0 × 10-5, 16.9 % of variance; and P = 0.0031, 9.4 % of variance, respectively). Premenopausal vs. postmenopausal comparisons identified specific relationships that were stronger in premenopausal than postmenopausal individuals, and vice versa. Age was a stronger correlate of low-density lipoprotein cholesterol; interleukin-6 of triglycerides and high-density lipoprotein; and both sex-hormone binding globulin and total abdominal fat of non high-density lipoprotein cholesterol in premenopausal than postmenopausal women. Conversely, sex-hormone binding globulin, abdominal visceral fat, interleukin-8, adiponectin were stronger correlates of triglycerides; abdominal visceral fat, and testosterone of high-density lipoprotein cholesterol; and age of both non high-density lipoprotein and low-density lipoprotein in postmenopausal than premenopausal women. Our data delineate correlations of total abdominal fat and interleukin-8 (both positively) with non high-density lipoprotein cholesterol and low-density lipoprotein cholesterol in healthy women across the full age range of 21-79 years along with even more specific associations in premenopausal and postmenopausal individuals. Whether some of these outcomes reflect causal relationships would require longitudinal and interventional or genetic studies.

Serum concentrations of prostate-specific antigen measured using immune extraction, trypsin digestion, and tandem mass spectrometry quantification of LSEPAELTDAVK peptide.

CONTEXT: Prostate-specific antigen (PSA) is a 34-kDa glycoprotein with chymotrypsin-like enzyme activity that circulates both in free forms and complexed to various enzyme inhibitors including antichymotrypsin and α2-macroglobulin. Prostate-specific antigen bound to α2-macroglobulin is not detected by commercial PSA immunoassays. OBJECTIVE: To develop a mass spectrometry assay that detects the same forms of PSA as the immunoassays, which could serve as a reference for harmonizing PSA immunoassays. DESIGN: Prostate-specific antigen was immune extracted from serum, trypsin was digested, and the LSEPAELTDAVK peptide was quantitated on an API 5000 spectrometer. Calibrators were made by adding 10% free and 90% antichymotrypsin-bound PSA to female sera. The assay was standardized to the World Health Organization 96/670 reference standard. Validation of clinical utility and comparisons with 2 immunoassays (Roche cobas and Beckman Access) were performed using frozen sera aliquots from 100 men undergoing prostate biopsy (50 negative, 50 with cancer) and 5 serial samples collected over time from 5 men with advanced prostate cancer. RESULTS: The antibody extraction efficiency was greater than 99%. The assay has an analytic range from 1.2 to 76 ng/mL, with precision ranging from 8.6% at 1.5 ng/mL to 5.4% at 27 ng/mL. The mass spectrometry assay correlated well with 2 immunoassays. All 3 assays showed statistically equivalent separation of prostate cancer from benign disease using receiver operating characteristic curve analysis. CONCLUSIONS: This mass spectrometry assay can reliably measure PSA concentrations in human serum and could serve as a reference standard for harmonizing PSA immunoassays.

Mass spectrometry measurements of prostate-specific antigen (PSA) peptides derived from immune-extracted PSA provide a potential strategy for harmonizing immunoassay differences.

OBJECTIVES: Harmonization of prostate-specific antigen (PSA) immunoassays is important for good patient care. The specificity of the antibodies used to detect circulating PSA could cause differences in the PSA measurements. METHODS: We used mass spectrometry (MS) to quantitate the concentration of five peptides cleaved from trypsin digestion of PSA and compared these measurements with six automated immunoassays. Linear regression and a mixed-effects model were used to analyze the results. RESULTS: PSA measurements from the immunoassays and the five MS peptide assays were highly correlated (R(2) > 0.99), but the recovery of the World Health Organization standard and the regression slopes differed across assays. The same relative patterns of immunoassay differences were seen in comparing their results with each of the five MS peptide measurements from different parts of the circulating PSA molecules. CONCLUSIONS: Mass spectrometry quantitation of peptides derived from trypsin digestion of immune-extracted PSA could be used to harmonize PSA immunoassays.

Immunological and mass spectrometric assays of SHBG: consistent and inconsistent metabolic associations in healthy men.

CONTEXT: SHBG concentrations correlate inconsistently with metabolic parameters. HYPOTHESIS: SHBG assay platforms contribute to nonuniformities according to the literature. DESIGN: The design of the study was a noninterventional quantification of SHBG by two immuno- and two mass spectrometric assays and abdominal visceral fat by computed tomography scan. SETTING: The study was conducted at the Center for Translational Science Activities. PARTICIPANTS: Healthy men (n=120) aged 18-80 years with a body mass index of 20-43 kg/m2 participated I the study. OUTCOMES: Outcomes of the study included a correlation of log SHBG with age, metabolic surrogates [body mass index, albumin, glucose, insulin, abdominal (total and visceral) fat, homeostasis model assessment insulin resistance index], sex steroids (estrone, 17ß-estradiol, T, and dihydrotestosterone by mass spectrometry), and adipocytokines (IL-1ß, IL-6, IL-8, IL-10 and IL-12, TNF-α, and adiponectin). RESULTS: By univariate regression, age (P<10(-4)), dihydrotestosterone (P<10(-4)), T (P≤.00022), and adiponectin (P≤.0084) were positive correlates, and insulin and homeostasis model assessment insulin resistance index were negative correlates (P≤.0060) of SHBG in all four assays. Stepwise multivariate analysis unveiled that age and T together could explain 38.1%-52.5% of the statistical variance in SHBG in all assays (P<10(-11)). Multivariate regression without sex steroids unveiled that age (P<10(-5)) and insulin (P<10(-3)) are jointly associated with SHBG levels in the four assays with overall R2=0.215-0.293 and P<10(-6). In one immunological SHBG assay each, abdominal visceral fat and adiponectin were weak multivariates also. CONCLUSION: Immunological and mass spectrometric SHBG assays yield both consistent and inconsistent correlations with key metabolic variables in healthy men, thereby potentially explaining earlier inconsistencies in the literature.

Immunologic and mass-spectrometric estimates of SHBG concentrations in healthy women.

OBJECTIVE: Sex-hormone binding globulin (SHBG) concentrations across the adult female lifespan are not well defined. To address this knowledge gap, SHBG was quantified by both immunological and criterion methods, viz, mass spectrometry (MS). SETTING: Center for Translational Science Activities (CTSA). PARTICIPANTS: Healthy nonpregnant women (N=120) ages 21 to 79 years. OUTCOMES: SHBG, testosterone (T), estradiol (E2) and estrone (E1) each determined by MS. Uni- and multivariate regression of SHBG concentrations on age, body mass index (BMI), total and visceral abdominal fat (TAF, AVF), albumin, glucose, insulin, sex steroids, selected cytokines, blood pressure, and lipids. RESULTS: By univariate regression, MS-estimated SHBG correlated negatively with BMI, TAF, AVF, insulin, free T and bioavailable T (bio T) (each P≤10(-4)), but not with blood pressure or lipids. By stepwise multivariate regression analysis, free and total T (both positive) and bio T (negative) were correlated with SHBG in all 4 assays (each P<10(-15), R(2)≥0.481). In addition, TAF and BMI were negatively associated with SHBG (P≤0.0066) in 2 SHBG assays, and estrone and IL-8 with SHBG weakly (P≤0.035) in one SHBG assay each. When nonsignificant cytokines were excluded, SHBG was jointly associated with AVF, total T and HDL (P<10(-9), R(2)=0.358). CONCLUSION: According to MS, three metabolic factors, T, AVF and HDL, together explain more than one-third of the interindividual variation in SHBG levels. We speculate that these measures reflect insulin action.

LC-MS/MS quantification of Zn-alpha2 glycoprotein: a potential serum biomarker for prostate cancer.

BACKGROUND: Zn-alpha2 glycoprotein (ZAG) is a relatively abundant glycoprotein that has potential as a biomarker for prostate cancer. We present a high-flow liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for measuring serum ZAG concentrations by proteolytic cleavage of the protein and quantification of a unique peptide. METHODS: We selected the ZAG tryptic peptide (147)EIPAWVPEDPAAQITK(162) as the intact protein for quantification and used a stable isotope-labeled synthetic peptide with this sequence as an internal standard. Standards using recombinant ZAG in bovine serum albumin, 50 g/L, and a pilot series of patient sera were denatured, reduced, alkylated, and digested with trypsin. The concentration of ZAG was calculated from a dose-response curve of the ratio of the relative abundance of the ZAG tryptic peptide to internal standard. RESULTS: The limit of detection for ZAG in serum was 0.08 mg/L, and the limit of quantification was 0.32 mg/L with a linear dynamic range of 0.32 to 10.2 mg/L. Replicate digests from pooled sera run during a period of 3 consecutive days showed intraassay imprecision (CV) of 5.0% to 6.3% and interassay imprecision of 4.4% to 5.9%. Mean (SD) ZAG was higher in 25 men with prostate cancer [7.59 (2.45) mg/L] than in 20 men with nonmalignant prostate disease [6.21 (1.65) mg/L, P = 0.037] and 6 healthy men [3.65 (0.71) mg/L, P = 0.0007]. CONCLUSIONS: This LC-MS/MS assay is reproducible and can be used to evaluate the clinical utility of ZAG as a cancer biomarker.